3D height-alternant island arrays for stretchable OLEDs with high active area ratio and maximum strain.

Stretchable optoelectronic devices are typically realized through a 2D integration of rigid components and elastic interconnectors to maintain device performance under stretching deformation. However, such configurations inevitably sacrifice the area ratio of active components to enhance the maximum interconnector strain. We herein propose a 3D buckled height-alternant architecture for stretchable OLEDs that enables the high active-area ratio and the enhanced maximum strain simultaneously.

Stretchable OLEDs based on a hidden active area for high fill factor and resolution compensation.

Stretchable organic light-emitting diodes (OLEDs) have emerged as promising optoelectronic devices with exceptional degree of freedom in form factors. However, stretching OLEDs often results in a reduction in the geometrical fill factor (FF), that is the ratio of an active area to the total area, thereby limiting their potential for a broad range of applications. To overcome these challenges, we propose a three-dimensional (3D) architecture adopting a hidden active area that serves a dual role as both an emitting area and an interconnector.

Social context modulates multibrain broadband dynamics and functional brain-to-brain coupling in the group of mice.

Although mice are social, multiple animals' neural activities are rarely explored. To characterise the neural activities during multi-brain interaction, we simultaneously recorded local field potentials (LFP) in the prefrontal cortex of four mice. The social context and locomotive states predominately modulated the entire LFP structure.

Ultrasensitive Carbon Monoxide Gas Sensor at Room Temperature Using Fluorine-Graphdiyne.

Currently, most carbon monoxide (CO) gas sensors work at high temperatures of over 150 °C. Developing CO gas sensors that operate at room temperature is challenging because of the sensitivity trade-offs. Here, we report an ultrasensitive CO gas sensor at room temperature using fluorine-graphdiyne (F-GDY) in which electrons are increased by light.

Analysis and Validation of Cross-Modal Generative Adversarial Network for Sensory Substitution.

Visual-auditory sensory substitution has demonstrated great potential to help visually impaired and blind groups to recognize objects and to perform basic navigational tasks. However, the high latency between visual information acquisition and auditory transduction may contribute to the lack of the successful adoption of such aid technologies in the blind community; thus far, substitution methods have remained only laboratory-scale research or pilot demonstrations. This high latency for data conversion leads to challenges in perceiving fast-moving objects or rapid environmental changes.

Accelerating On-Device Learning with Layer-Wise Processor Selection Method on Unified Memory.

Recent studies have applied the superior performance of deep learning to mobile devices, and these studies have enabled the running of the deep learning model on a mobile device with limited computing power. However, there is performance degradation of the deep learning model when it is deployed in mobile devices, due to the different sensors of each device. To solve this issue, it is necessary to train a network model specific to each mobile device.

Ultraflexible and transparent electroluminescent skin for real-time and super-resolution imaging of pressure distribution.

The ability to image pressure distribution over complex three-dimensional surfaces would significantly augment the potential applications of electronic skin. However, existing methods show poor spatial and temporal fidelity due to their limited pixel density, low sensitivity, or low conformability. Here, we report an ultraflexible and transparent electroluminescent skin that autonomously displays super-resolution images of pressure distribution in real time.

An Energy-Efficient Method for Human Activity Recognition with Segment-Level Change Detection and Deep Learning.

Human activity recognition (HAR), which is important in context awareness services, needs to occur continuously in daily life, owing to which an energy-efficient method is needed. However, because human activities have a longer cycle than HAR methods, which have analysis cycles of a few seconds, continuous classification of human activities using these methods is computationally and energy inefficient. Therefore, we propose segment-level change detection to identify activity change with very low computational complexity.

SCENet: Secondary Domain Intercorrelation Enhanced Network for Alleviating Compressed Poisson Noises.

In real image coding systems, block-based coding is often applied on images contaminated by camera sensor noises such as Poisson noises, which cause complicated types of noises called compressed Poisson noises. Although many restoration methods have recently been proposed for compressed images, they do not provide satisfactory performance on the challenging compressed Poisson noises. This is mainly due to (i) inaccurate modeling regarding the image degradation, (ii) the signal-dependent noise property, and (iii) the lack of analysis on intercorrelation distortion.

A Micro-Level Data-Calibrated Agent-Based Model: The Synergy between Microsimulation and Agent-Based Modeling.

Artificial life (ALife) examines systems related to natural life, its processes, and its evolution, using simulations with computer models, robotics, and biochemistry. In this article, we focus on the computer modeling, or "soft," aspects of ALife and prepare a framework for scientists and modelers to be able to support such experiments. The framework is designed and built to be a parallel as well as distributed agent-based modeling environment, and does not require end users to have expertise in parallel or distributed computing.

Ultrasensitive and highly selective graphene-based single yarn for use in wearable gas sensor.

Electric components based on fibers or textiles have been investigated owing to their potential applications in wearable devices. High performance on response to gas, drape-ability and washing durability are of important for gas sensors based on fiber substrates. In this report, we demonstrate the bendable and washable electronic textile (e-textile) gas sensors composed of reduced graphene oxides (RGOs) using commercially available yarn and molecular glue through an electrostatic self-assembly.

Origin of degradation phenomenon under drain bias stress for oxide thin film transistors using IGZO and IGO channel layers.

Top-gate structured thin film transistors (TFTs) using In-Ga-Zn-O (IGZO) and In-Ga-O (IGO) channel compositions were investigated to reveal a feasible origin for degradation phenomenon under drain bias stress (DBS). DBS-driven instability in terms of V(TH) shift, deviation of the SS value, and increase in the on-state current were detected only for the IGZO-TFT, in contrast to the IGO-TFT, which did not demonstrate V(TH) shift. These behaviors were visually confirmed via nanoscale transmission electron microscopy and energy-dispersive x-ray spectroscopy observations.