Wearable, Ultrawide-Range, and Bending-Insensitive Pressure Sensor Based on Carbon Nanotube Network-Coated Porous Elastomer Sponges for Human Interface and Healthcare Devices

Flexible and wearable pressure sensors have attracted a tremendous amount of attention due to their wider applications in human interfaces and healthcare monitoring. However, achieving accurate pressure detection and stability against external stimuli (in particular, bending deformation) over a wide range of pressures from tactile to body weight levels is a great challenge. Here, we introduce an ultrawide-range, bending-insensitive, and flexible pressure sensor based on a carbon nanotube (CNT) network-coated thin porous elastomer sponge for use in human interface devices. The integration of the CNT networks into three-dimensional microporous elastomers provides high deformability and a large change in contact between the conductive CNT networks due to the presence of micropores, thereby improving the sensitivity compared with that obtained using CNT-embedded solid elastomers. As electrical pathways are continuously generated up to high compressive strain (∼80%), the pressure sensor shows an ultrawide pressure sensing range (10 Pa to 1.2 MPa) while maintaining favorable sensitivity (0.01–0.02 kPa–1) and linearity (R2 ∼ 0.98). Also, the pressure sensor exhibits excellent electromechanical stability and insensitivity to bending-induced deformations. Finally, we demonstrate that the pressure sensor can be applied in a flexible piano pad as an entertainment human interface device and a flexible foot insole as a wearable healthcare and gait monitoring device

Avian species survey with citizen-science data in Janghang Wetland, Goyang, Republic of Korea

Monitoring of avian populations in Janghang Wetland, Goyang, Republic of Korea (ROK) is based on citizen science (also called community-based monitoring). This monitoring data can be used to track avian density, population status and waterbird census at local, national and regional levels. The Ministry of Environment (MoE) ROK has surveyed since 1999, including Odusan Unification Tower to Ilsan Bride, which connects the cities of Gimpo and Goyang along the Han River estuary. However, it has not covered Janghang Wetland, which is located in the Han River estuary at the transboundary between the two Koreas. The Janghang Wetland is a protected wetland in the Demilitarized Zone (DMZ) between the two Koreas. In 2019, Janghang Wetland was designated as a Flyway Network Site by Goyang City and the East Asian-Australasian Flyway Partnership. This Network site is a voluntary collaboration and includes many internationally significant wetlands for waterbirds that still lack formal national protection. In addition, it was designated as a Ramsar site in 2021. The wetland currently supports wintering population of White-naped Crane (Grus vipio), species listed as vulnerable and Tundra Bean Goose (Anser cygnoides), spring-autumn migration population of Swan Goose (Anser cygnoid), species listed as vulnerable and a breeding population of Black-faced Spoonbill (Platalea minor), species listed as endangered in summer.We provide data that the Janghang Wetland is a significant area for migration and breeding for waterbirds; and that Han River estuary is also internationally important for waterbirds during the migratory bird season. We observed 14 orders, 42 families and 132 species. The surveys also observed the critically-endangered Black-faced Spoonbill (Platalea minor), Swan Goose (Anser cygnoides), White-naped Crane (Grus vipio), Whooper Swan (Cygnus cygnus) and Peregrine Falcon (Falco peregrinus). We also observed the Black-faced Spoonbill, Great Egret, Little Egret, Great Cormorant, Eastern Spot-billed Duck, Pheasant and Brown-eared Bulbul at the sensor camera point and White-naped Crane, Hooded Crane, Bean Goose, White-fronted Goose, Snow Goose, Swan Goose, Great Cormorant and Eastern Spot-billed Duck at the closed-circuit television camera point from the camera-trap surveys. Based on the species recorded, the survey area is of clear importance for biodiversity conservation

Updates on the genetic variations of Norovirus in sporadic gastroenteritis in Chungnam Korea, 2009-2010

Previously, we explored the epidemic pattern and molecular characterization of noroviruses (NoVs) isolated in Chungnam, Korea in 2008, and the present study extended these observations to 2009 and 2010. In Korea, NoVs showed the seasonal prevalence from late fall to spring, and widely detected in preschool children and peoples over 60 years of age. Epidemiological pattern of NoV was similar in 2008 and in 2010, but pattern in 2009 was affected by pandemic influenza A/H1N1 2009 virus. NoV-positive samples were subjected to sequence determination of the capsid gene region, which resolved the isolated NoVs into five GI (2, 6, 7, 9 and 10) and eleven GII genotypes (1, 2, 3, 4, 6, 7, 8, 12, 13, 16 and 17). The most prevalent genotype was GII.4 and occupied 130 out of 211 NoV isolates (61.6%). Comparison of NoV GII.4 of prevalent genotype in these periods with reference strains of the same genotype was conducted to genetic analysis by a phylogenetic tree. The NoV GII.4 strains were segregated into seven distinct genetic groups, which are supported by high bootstrap values and previously reported clusters. All Korean NoV GII.4 strains belonged to either VI cluster or VII cluster. The divergence of nucleotide sequences within VI and VII intra-clusters was > 3.9% and > 3.5%, respectively. The "Chungnam(06-117)/2010" strain which was isolated in June 2010 was a variant that did not belong to cluster VI or VII and showed 5.8-8.2%, 6.2-8.1% nucleotide divergence with cluster VI and VII, respectively

Low-threshold optically pumped lasing in highly strained Ge nanowires

The integration of efficient, miniaturized group IV lasers into CMOS architecture holds the key to the realization of fully functional photonic-integrated circuits. Despite several years of progress, however, all group IV lasers reported to date exhibit impractically high thresholds owing to their unfavorable bandstructures. Highly strained germanium with its fundamentally altered bandstructure has emerged as a potential low-threshold gain medium, but there has yet to be any successful demonstration of lasing from this seemingly promising material system. Here, we demonstrate a low-threshold, compact group IV laser that employs germanium nanowire under a 1.6% uniaxial tensile strain as the gain medium. The amplified material gain in strained germanium can sufficiently surmount optical losses at 83 K, thus allowing the first observation of multimode lasing with an optical pumping threshold density of ~3.0 kW cm^-^2. Our demonstration opens up a new horizon of group IV lasers for photonic-integrated circuits.Comment: 31 pages, 9 figure

Towards Single 2D Image-Level Self-Supervision for 3D Human Pose and Shape Estimation

Three-dimensional human pose and shape estimation is an important problem in the computer vision community, with numerous applications such as augmented reality, virtual reality, human computer interaction, and so on. However, training accurate 3D human pose and shape estimators based on deep learning approaches requires a large number of images and corresponding 3D ground-truth pose pairs, which are costly to collect. To relieve this constraint, various types of weakly or self-supervised pose estimation approaches have been proposed. Nevertheless, these methods still involve supervision signals, which require effort to collect, such as unpaired large-scale 3D ground truth data, a small subset of 3D labeled data, video priors, and so on. Often, they require installing equipment such as a calibrated multi-camera system to acquire strong multi-view priors. In this paper, we propose a self-supervised learning framework for 3D human pose and shape estimation that does not require other forms of supervision signals while using only single 2D images. Our framework inputs single 2D images, estimates human 3D meshes in the intermediate layers, and is trained to solve four types of self-supervision tasks (i.e., three image manipulation tasks and one neural rendering task) whose ground-truths are all based on the single 2D images themselves. Through experiments, we demonstrate the effectiveness of our approach on 3D human pose benchmark datasets (i.e., Human3.6M, 3DPW, and LSP), where we present the new state-of-the-art among weakly/self-supervised methods.</p&gt

Methods and Experiments for Understanding Two Interacting Hands

Graduate School of Artificial IntelligenceThree dimensional hand pose estimation has reached a level of maturity, enabling real-world applications for single-hand cases. However, accurate estimation of the pose of two closely interacting hands still remains a challenge as in this case, one hand often occludes the other. We present a new algorithm that accurately estimates hand poses in such a challenging scenario. The crux of our algorithm lies in a framework that jointly trains the estimators of interacting hands, leveraging their inter-dependence. Further, we employ a GAN-type discriminator of interacting hand pose that helps avoid physically implausible configurations, e.g. intersecting fingers, and exploit the visibility of joints to improve intermediate 2D pose estimation. We incorporate them into a single model that learns to detect hands and estimate their pose based on a unified criterion of pose estimation accuracy. To our knowledge, this is the first attempt to build an end-to-end network that detects and estimates the pose of two closely interacting hands (as well as single hands). In the experiments with three datasets representing challenging realworld scenarios, our algorithm demonstrated significant and consistent performance improvements over state-of-the-arts.ope

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School of Energy and Chemical Engineering (Energy Engineering (Battery Science and Technology))ope