Effect of virtual reality-based biofeedback for depressive and anxiety symptoms: Randomized controlled study.

BACKGROUND: The use of virtual reality (VR)-based biofeedback (BF), a relatively new intervention, is a non-pharmacological treatment of depressive and anxiety symptoms. However, studies on VR-based BF are lacking and inconclusive. METHODS: A total of 131 adults were recruited from the community. Participants who scored ≥10 on the Patient Health Questionnaire-9 (PHQ-9) or ≥9 on the Panic Disorder Severity Scale (PDSS) were included in the group with depressive or anxiety symptoms (DAS group), and others as the healthy control group (HC group). Participants from the DAS group were randomly assigned to VR-based or conventional BF intervention. All individuals visited at three times (weeks 0, 2, and 4), and completed the Montgomery-Asberg Depression Rating Scale (MADRS), the State-Trait Anxiety Inventory (STAI), and a visual analog scale (VAS) before and after the intervention, and PHQ-9 at the beginning and final visit. RESULTS: The analysis included a total of 118 participants (DAS/VR: 40, DAS/BF: 38, HC/VR: 40). There was no significant difference in demographic variables among the three groups. After the intervention, the DAS/VR group exhibited significant decreases in MADRS (70.0 %), PHQ-9 (64.1 %), STAI (29.5 %), and VAS (61.7 %) scores compared to the baseline (p <0.001). There were no significant differences between the effects of VR-based BF and conventional BF with a therapist. The HC group also showed significant decreases in the measures of depression and anxiety after receiving VR-based BF. CONCLUSION: VR-based BF was effective in reducing depressive and anxiety symptoms, even for subthreshold depression and anxiety symptoms in the HC group.

Network coding on heterogeneous multi-core processors for wireless sensor networks.

While network coding is well known for its efficiency and usefulness in wireless sensor networks, the excessive costs associated with decoding computation and complexity still hinder its adoption into practical use. On the other hand, high-performance microprocessors with heterogeneous multi-cores would be used as processing nodes of the wireless sensor networks in the near future. To this end, this paper introduces an efficient network coding algorithm developed for the heterogenous multi-core processors. The proposed idea is fully tested on one of the currently available heterogeneous multi-core processors referred to as the Cell Broadband Engine.

Mitrofanovite, Layered Platinum Telluride, for Active Hydrogen Evolution.

Two-dimensional (2D) layered catalysts have been considered as a class of ideal catalysts for hydrogen evolution reaction (HER) because of their abundant active sites with almost zero Gibbs energy change for hydrogen adsorption. Despite the promising performance, the design of stable and economic electrochemical catalyst based on 2D materials remains to be resolved for industrial-scale hydrogen production. Here, we report layered platinum tellurides, mitrofanovite Pt3Te4, which serves as an efficient and stable catalyst for HER with an overpotential of 39.6 mV and a Tafel slope of 32.7 mV/dec together with a high current density exceeding 7000 mA/cm2. Pt3Te4 was synthesized as nanocrystals on a metallic molybdenum ditelluride (MoTe2) template by a rapid electrochemical method. X-ray diffraction and high-resolution transmission microscopy revealed that the Pt3Te4 nanocrystals have a unique layered structure with repeated monolayer units of PtTe and PtTe2. Theoretical calculations exhibit that Pt3Te4 with numerous edges shows near-zero Gibbs free-energy change of hydrogen adsorption, which shows the excellent HER performance as well as the extremely large exchange current density for massive hydrogen production.

Bio-inspired, Moisture-Powered Hybrid Carbon Nanotube Yarn Muscles.

Hygromorph artificial muscles are attractive as self-powered actuators driven by moisture from the ambient environment. Previously reported hygromorph muscles have been largely limited to bending or torsional motions or as tensile actuators with low work and energy densities. Herein, we developed a hybrid yarn artificial muscle with a unique coiled and wrinkled structure, which can be actuated by either changing relative humidity or contact with water. The muscle provides a large tensile stroke (up to 78%) and a high maximum gravimetric work capacity during contraction (2.17 kJ kg(-1)), which is over 50 times that of the same weight human muscle and 5.5 times higher than for the same weight spider silk, which is the previous record holder for a moisture driven muscle. We demonstrate an automatic ventilation system that is operated by the tensile actuation of the hybrid muscles caused by dew condensing on the hybrid yarn. This self-powered humidity-controlled ventilation system could be adapted to automatically control the desired relative humidity of an enclosed space.