Golden aspect ratio for ion transport simulation in nanopores

Access resistance indicates how well current carriers from a bulk medium canconverge to a pore or opening, and is an important concept in nanofluidicdevices and in cell physiology. In simplified scenarios, when the bulkdimensions are infinite in all directions, it depends only on the resistivityand pore radius. These conditions are not valid in all-atom molecular dynamics(MD) simulations of transport, due to the computational cost of largesimulation cells, and can even break down in micro- and nano-scale systems dueto strong confinement. Here, we examine a scaling theory for the accessresistance that predicts a special simulation cell aspect ratio -- the goldenaspect ratio -- where finite size effects are eliminated. Using both continuumand all-atom simulations, we demonstrate that this golden aspect ratio existsand that it takes on a universal value in linear response and moderateconcentrations. Outside of linear response, it gains an apparent dependence oncharacteristics of the transport scenario (concentration, voltages, etc.) forsmall simulation cells, but this dependence vanishes at larger length scales.These results will enable the use of all-atom molecular dynamics simulations tostudy contextual properties of access resistance -- its dependence on proteinand molecular-scale fluctuations, the presence of charges, and other functionalgroups -- and yield the opportunity to quantitatively compare computed andmeasured resistances.

Beam-Energy Dependence of Directed Flow of $\Lambda$, $\bar{\Lambda}$, $K^\pm$, $K^0_s$ and $\phi$ in Au+Au Collisions

Rapidity-odd directed flow measurements at midrapidity are presented for$\Lambda$, $\bar{\Lambda}$, $K^\pm$, $K^0_s$ and $\phi$ at $\sqrt{s_{NN}} =$7.7, 11.5, 14.5, 19.6, 27, 39, 62.4 and 200 GeV in Au+Au collisions recorded bythe STAR detector at the Relativistic Heavy Ion Collider. These measurementsgreatly expand the scope of data available to constrain models with differingprescriptions for the equation of state of quantum chromodynamics. Results showgood sensitivity for testing a picture where flow is assumed to be imposedbefore hadron formation and the observed particles are assumed to form viacoalescence of constituent quarks. The pattern of departure from acoalescence-inspired sum-rule can be a valuable new tool for probing thecollision dynamics.

Inter-Landau-level Andreev Reflection at the Dirac Point in a Graphene Quantum Hall State Coupled to a NbSe2 Superconductor

Superconductivity and quantum Hall effect are distinct states of matteroccurring in apparently incompatible physical conditions. Recent theoreticaldevelopments suggest that the coupling of quantum Hall effect with asuperconductor can provide a fertile ground for realizing exotic topologicalexcitations such as non-abelian Majorana fermions or Fibonacci particles. As astep toward that goal, we report observation of Andreev reflection at thejunction of a quantum Hall edge state in a single layer graphene and aquasi-two dimensional niobium diselenide (NbSe2) superconductor. Our principalfinding is the observation of an anomalous finite-temperature conductance peaklocated precisely at the Dirac point, providing a definitive evidence forinter-Landau level Andreev reflection in a quantum Hall system. Ourobservations are well supported by detailed numerical simulations, which offeradditional insight into the role of the edge states in Andreev physics. Thisstudy paves the way for investigating analogous Andreev reflection in afractional quantum Hall system coupled to a superconductor to realize exoticquasiparticles.

Low-$p_T$ $e^{+}e^{-}$ pair production in Au$+$Au collisions at $\sqrt{s_{NN}}$ = 200 GeV and U$+$U collisions at $\sqrt{s_{NN}}$ = 193 GeV at STAR

We report first measurements of $e^{+}e^{-}$ pair production in the massregion 0.4 $<M_{ee}<$ 2.6 GeV/$c^{2}$ at low transverse momentum ($p_T<$ 0.15GeV/$c$) in non-central Au$+$Au collisions at $\sqrt{s_{NN}}$ = 200 GeV andU$+$U collisions at $\sqrt{s_{NN}}$ = 193 GeV. Significant enhancement factors,expressed as ratios of data over known hadronic contributions, are observed inthe 40-80% centrality of these collisions. The excess yields peak distinctly atlow-$p_T$ with a width ($\sqrt{\langle p^2_T\rangle}$) between 40 to 60MeV/$c$. The absolute cross section of the excess depends weakly on centralitywhile those from a theoretical model calculation incorporating an in-mediumbroadened $\rho$ spectral function and radiation from a Quark Gluon Plasma orhadronic cocktail contributions increase dramatically with increasing number ofparticipant nucleons. Model calculations of photon-photon interactionsgenerated by the initial projectile and target nuclei describe the observedexcess yields but fail to reproduce the $p^{2}_{T}$ distributions.

Erratum: Observation of D0 Meson Nuclear Modifications in Au+Au Collisions at s<…

Investment Behaviour

Active Control of Chatter in Milling Process Using Intelligent PD/PID Control

Chatter is an obstacle for achieving high-quality machining process and high production rate in industries. Chatter is an unstable self-exciting phenomenon that leads to tool wear, poor surface finish, and downgrade the milling operations. A novel active control strategy to attenuate the chatter vibration is proposed. PD/PID controllers in combination with Type-2 Fuzzy logic were utilized as a control strategy. The main control actions were generated by PD/PID controllers, whereas the Type-2 Fuzzy logic system was used to compensate the involved nonlinearities. The Lyapunov stability analysis was utilized to validate the stability of Fuzzy PD/PID controllers. The theoretical concepts and results are proved using numerical simulations. Although PD/PID controllers have been used for chatter control in machining process, the importance of stability along with the implementation of Type-2 Fuzzy logic system for nonlinearity compensation was the main contribution. In addition, active control using an Active Vibration Damper placed in an effective position is entirely a new approach with promising practical results.

Semi-Supervised and Transfer Learning Approaches for Low Resource Sentiment Classification

Sentiment classification involves quantifying the affective reaction of a human to a document, media item or an event. Although researchers have investigated several methods to reliably infer sentiment from lexical, speech and body language cues, training a model with a small set of labeled datasets is still a challenge. For instance, in expanding sentiment analysis to new languages and cultures, it may not always be possible to obtain comprehensive labeled datasets. In this paper, we investigate the application of semi- supervised and transfer learning methods to improve performances on low resource sentiment classification tasks. We experiment with extracting dense feature representations, pre-training and manifold regularization in enhancing the performance of sentiment classification systems. Our goal is a coherent implementation of these methods and we evaluate the gains achieved by these methods in matched setting involving training and testing on a single corpus setting as well as two cross corpora settings. In both the cases, our experiments demonstrate that the proposed methods can significantly enhance the model performance against a purely supervised approach, particularly in cases involving a handful of training data.

AirScript - Creating Documents in Air

This paper presents a novel approach, called AirScript, for creating, recognizing and visualizing documents in air. We present a novel algorithm, called 2-DifViz, that converts the hand movements in air (captured by a Myo-armband worn by a user) into a sequence of x, y coordinates on a 2D Cartesian plane, and visualizes them on a canvas. Existing sensor-based approaches either do not provide visual feedback or represent the recognized characters using prefixed templates. In contrast, AirScript stands out by giving freedom of movement to the user, as well as by providing a real-time visual feedback of the written characters, making the interaction natural. AirScript provides a recognition module to predict the content of the document created in air. To do so, we present a novel approach based on deep learning, which uses the sensor data and the visualizations created by 2-DifViz. The recognition module consists of a Convolutional Neural Network (CNN). and two Gated Recurrent Unit (GRU) Networks. The output from these three networks is fused to get the final prediction about the characters written in air. AirScript can be used in highly sophisticated environments like a smart classroom, a smart factory or a smart laboratory, where it would enable people to annotate pieces of texts wherever they want without any reference surface. We have evaluated AirScript against various well-known learning models (HMM, KNN, SVM, etc.) on the data of 12 participants. Evaluation results show that the recognition module of AirScript largely outperforms all of these models by achieving an accuracy of 91.7% in a person independent evaluation and a 96.7% accuracy in a person dependent evaluation.

Drishtikon: An advanced navigational aid system for visually impaired people

Today, many of the aid systems deployed for visually impaired people are mostly made for a single purpose. Be it navigation, object detection, or distance perceiving. Also, most of the deployed aid systems use indoor navigation which requires a pre-knowledge of the environment. These aid systems often fail to help visually impaired people in the unfamiliar scenario. In this paper, we propose an aid system developed using object detection and depth perceivement to navigate a person without dashing into an object. The prototype developed detects 90 different types of objects and compute their distances from the user. We also, implemented a navigation feature to get input from the user about the target destination and hence, navigate the impaired person to his/her destination using Google Directions API. With this system, we built a multi-feature, high accuracy navigational aid system which can be deployed in the wild and help the visually impaired people in their daily life by navigating them effortlessly to their desired destination.