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The spectral wave model WAM (Cycle 6) is a commonly-used code package for ocean wave modeling. However, it is still a challenge to include it into the long-term earth system modeling due to huge computing requirement. In this study we have successfully developed a GPU-accelerated version of the WAM model that can run all its computing-demanding components on GPUs, with a significant performance increase compared with its original CPU version. The power of GPU computing has been unleashed through substantial efforts of code refactoring, which reduces the computing time of a 7-day global 1/10° wave modeling to 7.6 minutes in a revolutionary way. The study provides an approach to energy-efficient computing for ocean wave modeling. A preliminary evaluation suggests that approximately 90 % of power can be saved. [ABSTRACT FROM AUTHOR]

Strain and temperature are important physiological parameters for health monitoring, providing access to the respiration state, movement of joints, and inflammation processes. The challenge for smart wearables is to unambiguously discriminate strain and temperature using a single sensor element assuring a high degree of sensor integration. Here, a dual‐mode sensor with two electrodes and tubular mechanically heterogeneous structure enabling simultaneous sensing of strain and temperature without cross‐talk is reported. The sensor structure consists of a thermocouple coiled around an elastic strain‐to‐magnetic induction conversion unit, revealing a giant magnetoelastic effect, and accommodating a magnetic amorphous wire. The thermocouple provides access to temperature and its coil structure allows to measure impedance changes caused by the applied strain. The dual‐mode sensor also exhibits interference‐free temperature sensing performance with high coefficient of 54.49 µV °C−1, low strain and temperature detection limits of 0.05% and 0.1 °C, respectively. The use of these sensors in smart textiles to monitor continuously breathing, body movement, body temperature, and ambient temperature is demonstrated. The developed multifunctional wearable sensor is needed for applications in early disease prevention, health monitoring, and interactive electronics as well as for smart prosthetics and intelligent soft robotics. [ABSTRACT FROM AUTHOR]

BACKGROUND: To improve the aroma of kiwi wine through the utilization of Wickerhamomyces anomalus, kiwi juice was fermented using a selected W. anomalus strain in pure culture and mixed fermentations with Saccharomyces cerevisiae, which was inoculated simultaneously and sequentially. The physicochemical indices, volatile compounds and aroma properties of the kiwi wines were assessed. RESULTS: The study suggested that the ethanol, color indices and organic acids of the wines were closely related to the method of inoculation. Compared with the pure S. cerevisiae fermentation, the mixed fermentations produced more varieties and concentrations of volatiles. The sequential fermentations increased the concentrations of esters and terpenes, improving the flower and sweet fruit notes of the wines. The simultaneous inoculation enhanced the contents of esters and aldehydes, intensifying the flower, sweet and sour fruit of the wines. Partial least‐squares regression analysis showed that esters and terpenes contributed greatly to the flower and sweet fruit aroma, whereas aldehydes were the major contributors to the sour note. CONCLUSION: Based on our results, the mixed fermentations not only enriched the types and concentrations of volatiles, but also had better sensory properties. © 2021 Society of Chemical Industry [ABSTRACT FROM AUTHOR]