Influence of wall charge distribution on time lag of address discharge in AC plasma display panels

The influence of wall charge distribution on the time lag of address discharge in an AC plasma display panel is investigated using two different reset waveforms: one (typical reset) induces both face and surface discharges and the other (TR reset) induces face discharges only. The measured formative time lag and statistical time lag of address discharge for TR were 21–31 ns and 31–74 ns shorter than the one for the typical reset, respectively. The TR reset resulted in much less increase of statistical time lag than the typical reset when the reset-to-address time interval was increased, and 70 ns smaller deviation of the statistical time lag among different color cells. Calculations show that the TR reset forms a much smoother wall charge profile, which is less susceptible to cell parameter variations, than the typical reset. The observed differences in the time lags of address discharge between different scan lines and color cells are strongly correlated to the differences of the wall charge profile, indicating that a smooth wall charge profile formed by the reset using face discharges only reduces the time lag of address discharge and minimizes the susceptibility of address discharge to cell parameter variation.     

Invited article: development of high-field superconducting Ioffe magnetic traps

We describe the design, construction, and performance of three generations of superconducting Ioffe magnetic traps. The first two are low current traps, built from four racetrack shaped quadrupole coils and two solenoid assemblies. Coils are wet wound with multifilament NbTi superconducting wires embedded in epoxy matrices. The magnet bore diameters are 51 and 105 mm with identical trap depths of 1.0 T at their operating currents and at 4.2 K. A third trap uses a high current accelerator-type quadrupole magnet and two low current solenoids. This trap has a bore diameter of 140 mm and tested trap depth of 2.8 T. Both low current traps show signs of excessive training. The high current hybrid trap, on the other hand, exhibits good training behavior and is amenable to quench protection.     

Portable and Efficient Implementation of CRYSTALS-Kyber Based on WebAssembly

With the rapid development of quantum computers capable of realizing Shor’s algorithm, existing public key-based algorithms face a significant security risk. Crystals-Kyber has been selected as the only key encapsulation mechanism (KEM) algorithm in the National Institute of Standards and Technology (NIST) Post-Quantum Cryptography (PQC) competition. In this study, we present a portable and efficient implementation of a Crystals-Kyber post-quantum KEM based on WebAssembly (Wasm), a recently released portable execution framework for high-performance web applications. Until now, most Kyber implementations have been developed with native programming languages such as C and Assembly. Although there are a few previous Kyber implementations based on JavaScript for portability, their performance is significantly lower than that of implementations based on native programming languages. Therefore, it is necessary to develop a portable and efficient Kyber implementation to secure web applications in the quantum computing era. Our Kyber software is based on JavaScript and Wasm to provide portability and efficiency while ensuring quantum security. Namely, the overall software is written in JavaScript, and the performance core parts (secure hash algorithm-3-based operations and polynomial multiplication) are written in Wasm. Furthermore, we parallelize the number theoretic transform (NTT)-based polynomial multiplication using single instruction multiple data (SIMD) functionality, which is available in Wasm. The three steps in the NTT-based polynomial multiplication have been parallelized with Wasm SIMD intrinsic functions. Our software outperforms the latest reference implementation of Kyber developed in JavaScript by ×4.02 (resp. ×4.32 and ×4.1), ×3.42 (resp. ×3.52 and ×3.44), and ×3.41 (resp. ×3.44 and ×3.38) in terms of key generation, encapsulation, and decapsulation on Google Chrome (resp. Firefox, and Microsoft Edge). As far as we know, this is the first software implementation of Kyber with Wasm technology in the web environment.     

Android IoT Lifelog System and Its Application to Motion Inference

In social science, health care, digital therapeutics, etc., smartphone data have played important roles to infer users’ daily lives. However, smartphone data collection systems could not be used effectively and widely because they did not exploit any Internet of Things (IoT) standards (e.g., oneM2M) and class labeling methods for machine learning (ML) services. Therefore, in this paper, we propose a novel Android IoT lifelog system complying with oneM2M standards to collect various lifelog data in smartphones and provide two manual and automated class labeling methods for inference of users’ daily lives. The proposed system consists of an Android IoT client application, an oneM2M-compliant IoT server, and an ML server whose high-level functional architecture was carefully designed to be open, accessible, and internationally recognized in accordance with the oneM2M standards. In particular, we explain implementation details of activity diagrams for the Android IoT client application, the primary component of the proposed system. Experimental results verified that this application could work with the oneM2M-compliant IoT server normally and provide corresponding class labels properly. As an application of the proposed system, we also propose motion inference based on three multi-class ML classifiers (i.e., k nearest neighbors, Naive Bayes, and support vector machine) which were created by using only motion and location data (i.e., acceleration force, gyroscope rate of rotation, and speed) and motion class labels (i.e., driving, cycling, running, walking, and stilling). When compared with confusion matrices of the ML classifiers, the k nearest neighbors classifier outperformed the other two overall. Furthermore, we evaluated its output quality by analyzing the receiver operating characteristic (ROC) curves with area under the curve (AUC) values. The AUC values of the ROC curves for all motion classes were more than 0.9, and the macro-average and micro-average ROC curves achieved very high AUC values of 0.96 and 0.99, respectively.     

5 nm Silver Nanoparticles Amplify Clinical Features of Atopic Dermatitis in Mice by Activating Mast Cells

The triggering effect of silver nanoparticles (NPs) on the induction of allergic reactions is evaluated, by studying the activation of mast cells and the clinical features of atopic dermatitis in a mouse model. Granule release is induced in RBL‐2H3 mast cells by 5 nm, but not 100 nm silver NPs. Increases in the levels of reactive oxygen species (hydrogen peroxide and mitochondrial superoxide) and intracellular Ca⁺⁺ in mast cells are induced by 5 nm silver NPs. In a mouse model of atopic dermatitis induced by a mite allergen, the skin lesions are more severe and appear earlier in mice treated simultaneously with 5 nm silver NPs and allergen compared with mice treated with allergen alone or 100 nm silver NPs and allergen. The histological findings reveal that number of tryptase‐positive mast cells and total IgE levels in the serum increase in mice treated with 5 nm silver NPs and allergen. The results in this study indicate that cotreatment with 5 nm silver NPs stimulates mast cell degranulation and induces earlier and more severe clinical alterations in allergy‐prone individuals.     

Silver Nanoflower Decorated Graphene Oxide Sponges for Highly Sensitive Variable Stiffness Stress Sensors

Soft conductive materials should enable large deformation while keeping high electrical conductivity and elasticity. The graphene oxide (GO)‐based sponge is a potential candidate to endow large deformation. However, it typically exhibits low conductivity and elasticity. Here, the highly conductive and elastic sponge composed of GO, flower‐shaped silver nanoparticles (AgNFs), and polyimide (GO‐AgNF‐PI sponge) are demonstrated. The average pore size and porosity are 114 µm and 94.7%, respectively. Ag NFs have thin petals (8–20 nm) protruding out of the surface of a spherical bud (300–350 nm) significantly enhancing the specific surface area (2.83 m² g^?1). The electrical conductivity (0.306 S m^?1 at 0% strain) of the GO‐AgNF‐PI sponge is increased by more than an order of magnitude with the addition of Ag NFs. A nearly perfect elasticity is obtained over a wide compressive strain range (0–90%). The strain‐dependent, nonlinear variation of Young's modulus of the sponge provides a unique opportunity as a variable stiffness stress sensor that operates over a wide stress range (0–10 kPa) with a high maximum sensitivity (0.572 kPa^?1). It allows grasping of a soft rose and a hard bottle, with the minimal object deformation, when attached on the finger of a robot gripper.