Maximum Resilience of Artificial Neural Networks

The deployment of Artificial Neural Networks (ANNs) in safety-critical applications poses a number of new verification and certification challenges. In particular, for ANN-enabled self-driving vehicles it is important to establish properties about the resilience of ANNs to noisy or even maliciously manipulated sensory input. We are addressing these challenges by defining resilience properties of ANN-based classifiers as the maximal amount of input or sensor perturbation which is still tolerated. This problem of computing maximal perturbation bounds for ANNs is then reduced to solving mixed integer optimization problems (MIP). A number of MIP encoding heuristics are developed for drastically reducing MIP-solver runtimes, and using parallelization of MIP-solvers results in an almost linear speed-up in the number (up to a certain limit) of computing cores in our experiments. We demonstrate the effectiveness and scalability of our approach by means of computing maximal resilience bounds for a number of ANN benchmark sets ranging from typical image recognition scenarios to the autonomous maneuvering of robots.Comment: Timestamp research work conducted in the project. version 2: fix some typos, rephrase the definition, and add some more existing wor

Dzyaloshinskii-Moriya Interaction and Spiral Order in Spin-orbit Coupled Optical Lattices

We show that the recent experimental realization of spin-orbit coupling in ultracold atomic gases can be used to study different types of spin spiral order and resulting multiferroic effects. Spin-orbit coupling in optical lattices can give rise to the Dzyaloshinskii-Moriya (DM) spin interaction which is essential for spin spiral order. By taking into account spin-orbit coupling and an external Zeeman field, we derive an effective spin model in the Mott insulator regime at half filling and demonstrate that the DM interaction in optical lattices can be made extremely strong with realistic experimental parameters. The rich finite temperature phase diagrams of the effective spin models for fermions and bosons are obtained via classical Monte Carlo simulations.Comment: 7 pages, 5 figure

Role of Linker Functionality in Polymers Exhibiting Main-Chain Thermally Activated Delayed Fluorescence

Excellent performance has been reported for organic light‐emitting diodes (OLEDs) based on small molecule emitters that exhibit thermally activated delayed fluorescence. However, the necessary vacuum processing makes the fabrication of large‐area devices based on these emitters cumbersome and expensive. Here, the authors present high performance OLEDs, based on novel, TADF polymers that can be readily processed from a solution. These polymers are based on the acridine‐benzophenone donor–acceptor motif as main‐chain TADF chromophores, linked by various conjugated and non‐conjugated spacer moieties. The authors’ extensive spectroscopic and electronic analysis shows that in particular in case of alkyl spacers, the properties and performance of the monomeric TADF chromophores are virtually left unaffected by the polymerization. They present efficient solution‐processed OLEDs based on these TADF polymers, diluted in oligostyrene as a host. The devices based on the alkyl spacer‐based TADF polymers exhibit external quantum efficiencies (EQEs) ≈12%, without any outcoupling‐enhancing measures. What's more, the EQE of these devices does not drop substantially upon diluting the polymer down to only ten weight percent of active material. In contrast, the EQE of devices based on the monomeric chromophore show significant losses upon dilution due to loss of charge percolation

Development of Photonic Crystal Fiber Based Gas/ Chemical Sensors

The development of highly-sensitive and miniaturized sensors that capable of real-time analytes detection is highly desirable. Nowadays, toxic or colorless gas detection, air pollution monitoring, harmful chemical, pressure, strain, humidity, and temperature sensors based on photonic crystal fiber (PCF) are increasing rapidly due to its compact structure, fast response and efficient light controlling capabilities. The propagating light through the PCF can be controlled by varying the structural parameters and core-cladding materials, as a result, evanescent field can be enhanced significantly which is the main component of the PCF based gas/chemical sensors. The aim of this chapter is to (1) describe the principle operation of PCF based gas/ chemical sensors, (2) discuss the important PCF properties for optical sensors, (3) extensively discuss the different types of microstructured optical fiber based gas/ chemical sensors, (4) study the effects of different core-cladding shapes, and fiber background materials on sensing performance, and (5) highlight the main challenges of PCF based gas/ chemical sensors and possible solutions

Interplay between Side Chain Density and Polymer Alignment: Two Competing Strategies for Enhancing the Thermoelectric Performance of P3HT Analogues

A series of polythiophenes with varying side chain density was synthesized, and their electrical and thermoelectric properties were investigated. Aligned and non-aligned thin films of the polymers were characterized in the neutral and chemically doped states. Optical and diffraction measurements revealed an overall lower order in the thin films with lower side chain density, also confirmed using polarized optical experiments on aligned thin films. However, upon doping the non-aligned films, a sixfold increase in electrical conductivity was observed for the polythiophene with the lowest side chain density compared to poly(3-hexylthiophene) (P3HT). We found that the improvement in conductivity was not due to a larger charge carrier density but an increase in charge carrier mobility after doping with 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F4TCNQ). On the other hand, doped aligned films did not show the same trend; lower side chain density instead led to a lower conductivity and Seebeck coefficient compared to those for P3HT. This was attributed to the poorer alignment of the polymer thin films with lower side chain density. The study demonstrates that optimizing side chain density is a synthetically simple and effective way to improve electrical conductivity in polythiophene films relevant to thermoelectric applications

Death of a tumor: targeting CCN in pancreatic cancer

The matricellular protein CCN2 (connective tissue growth factor, CTGF) has been previously implicated in tumorigenesis. In pancreatic cancer cells, CCN2 expression occurs downstream of ras/MEK/ERK. Direct evidence that CCN2 mediates tumor progression in pancreatic cancer has been lacking. An exciting recent report by Bennewith et al. (Cancer Res 69:775–784, 2009) has used shRNA knockdown of CCN2 to illustrate that CCN2 contributes to growth of pancreatic tumor cells, both in vitro and in vivo. This report briefly summarizes these findings

Estimation of the main dimensions of the traction permanent magnet-assisted synchronous reluctance motor

Goal. The goal of the research is to develop an algorithm for selecting the main dimensions of a traction permanent magnet-assisted synchronous reluctance motor. Methodology. A method for determining the main dimensions of the motor, which combines the analytical selection of stator parameters and numerical field calculations for the selection of rotor parameters. The need to check the mechanical strength of a rotor with permanent NdFeB magnets in flux barriers is shown. Results. The article proposes an algorithm for selecting the main dimensions of a traction permanent magnet-assisted synchronous reluctance motor, which combines analytical expressions for selecting stator parameters and numerical field calculations for selecting rotor parameters. It is determined that analytical methods for calculating the magnetic circuit need to be developed in order to reduce the time to select the main dimensions of the motor. Originality. For the first time the sizes of active parts of the permanent magnet-assisted synchronous reluctance motor with power of 180 kW for the drive of wheels of the trolleybus are defined. Practical significance. As a result of research the sizes of active parts, stator winding data and a design of a rotor of the electric motor are defined. The obtained results can be applied when creating an electric motor for a trolleybus

Оцінка головних розмірів тягового синхронно-реактивного електродвигуна з постійними магнітами

Goal. The goal of the research is to develop an algorithm for selecting the main dimensions of a traction permanent magnet-assisted synchronous reluctance motor. Methodology. A method for determining the main dimensions of the motor, which combines the analytical selection of stator parameters and numerical field calculations for the selection of rotor parameters. The need to check the mechanical strength of a rotor with permanent NdFeB magnets in flux barriers is shown. Results. The article proposes an algorithm for selecting the main dimensions of a traction permanent magnet-assisted synchronous reluctance motor, which combines analytical expressions for selecting stator parameters and numerical field calculations for selecting rotor parameters. It is determined that analytical methods for calculating the magnetic circuit need to be developed in order to reduce the time to select the main dimensions of the motor. Originality. For the first time the sizes of active parts of the permanent magnet-assisted synchronous reluctance motor with power of 180 kW for the drive of wheels of the trolleybus are defined. Practical significance. As a result of research the sizes of active parts, stator winding data and a design of a rotor of the electric motor are defined. The obtained results can be applied when creating an electric motor for a trolleybus.У статті розглянуті питання проектування тягового синхронно-реактивного електродвигуна з постійними магнітами потужністю 180 кВт для приводу коліс тролейбуса. Запропоновано спосіб визначення головних розмірів електродвигуна, який поєднує аналітичний вибір параметрів статора та чисельно-польові розрахунки для вибору параметрів ротора. Показана необхідність перевірки механічної міцності ротора, в якому розташовано постійні магніти NdFeB у потокових бар’єрах. У результаті дослідження визначено розміри активних частин, обмоткові дані статора та конструктив ротора електродвигуна

Integrative analyses identify modulators of response to neoadjuvant aromatase inhibitors in patients with early breast cancer

Introduction Aromatase inhibitors (AIs) are a vital component of estrogen receptor positive (ER+) breast cancer treatment. De novo and acquired resistance, however, is common. The aims of this study were to relate patterns of copy number aberrations to molecular and proliferative response to AIs, to study differences in the patterns of copy number aberrations between breast cancer samples pre- and post-AI neoadjuvant therapy, and to identify putative biomarkers for resistance to neoadjuvant AI therapy using an integrative analysis approach. Methods Samples from 84 patients derived from two neoadjuvant AI therapy trials were subjected to copy number profiling by microarray-based comparative genomic hybridisation (aCGH, n = 84), gene expression profiling (n = 47), matched pre- and post-AI aCGH (n = 19 pairs) and Ki67-based AI-response analysis (n = 39). Results Integrative analysis of these datasets identified a set of nine genes that, when amplified, were associated with a poor response to AIs, and were significantly overexpressed when amplified, including CHKA, LRP5 and SAPS3. Functional validation in vitro, using cell lines with and without amplification of these genes (SUM44, MDA-MB134-VI, T47D and MCF7) and a model of acquired AI-resistance (MCF7-LTED) identified CHKA as a gene that when amplified modulates estrogen receptor (ER)-driven proliferation, ER/estrogen response element (ERE) transactivation, expression of ER-regulated genes and phosphorylation of V-AKT murine thymoma viral oncogene homolog 1 (AKT1). Conclusions These data provide a rationale for investigation of the role of CHKA in further models of de novo and acquired resistance to AIs, and provide proof of concept that integrative genomic analyses can identify biologically relevant modulators of AI response