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  • 1
    In: Advanced Functional Materials, Wiley
    Abstract: In the pursuit of tactile sensation resembling human skin, the electronic skin (E‐skin) has long been a subject of interest and inspires the exploration of various biomimetic structures. Nevertheless, the exceptional functionality of living organisms arises from the synergistic interplay of multiple internal factors, i.e. the coupling enhancement effect, which has received limited attention in existing studies. Here, a tactile E‐skin featuring a multicoupled biomimetic structure that mimics three coupling elements found in the skin: Stratum spinosum, Meissner corpuscle, and Piezo2 protein, is proposed. By amalgamating their distinguishing characteristics, this bionic E‐skin surpasses the performance of conventional counterparts such as sensitivity as high as 388.5 kPa −1 , hysteresis as low as 0.76%, and response times as short as 10 ms. Furthermore, its fabrication methodology of efficient 3D printing shows great advantages in terms of production cost and customization. Finally, the sensor is expanded to a 9 × 9 pixels array for a machine learning‐assisted intellisense system to recognize the fruits as a human does, achieving an accuracy of 91.4%. All of these prove the promising potential of this multicoupled biomimetic structure in wearable electronics, human–machine interface, soft robotics, and artificial sensing.
    Type of Medium: Online Resource
    ISSN: 1616-301X , 1616-3028
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2029061-5
    detail.hit.zdb_id: 2039420-2
    SSG: 11
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  • 2
    In: Arthritis Care & Research, Wiley, Vol. 75, No. 2 ( 2023-02), p. 220-230
    Abstract: Recognizing that the interrelationships between chronic conditions that complicate rheumatoid arthritis (RA) are poorly understood, we aimed to identify patterns of multimorbidity and to define their prevalence in RA through machine learning. Methods We constructed RA and age‐ and sex‐matched (1:1) non‐RA cohorts within a large commercial insurance database (MarketScan) and the Veterans Health Administration (VHA). Chronic conditions (n = 44) were identified from diagnosis codes from outpatient and inpatient encounters. Exploratory factor analysis was performed separately in both databases, stratified by RA diagnosis and sex, to identify multimorbidity patterns. The association of RA with different multimorbidity patterns was determined using conditional logistic regression. Results We studied 226,850 patients in MarketScan (76% female) and 120,780 patients in the VHA (89% male). The primary multimorbidity patterns identified were characterized by the presence of cardiopulmonary, cardiometabolic, and mental health and chronic pain disorders. Multimorbidity patterns were similar between RA and non‐RA patients, female and male patients, and patients in MarketScan and the VHA. RA patients had higher odds of each multimorbidity pattern (odds ratios [ORs] 1.17–2.96), with mental health and chronic pain disorders being the multimorbidity pattern most strongly associated with RA (ORs 2.07–2.96). Conclusion Cardiopulmonary, cardiometabolic, and mental health and chronic pain disorders represent predominant multimorbidity patterns, each of which is overrepresented in RA. The identification of multimorbidity patterns occurring more frequently in RA is an important first step in progressing toward a holistic approach to RA management and warrants assessment of their clinical and predictive utility.
    Type of Medium: Online Resource
    ISSN: 2151-464X , 2151-4658
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2016713-1
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  • 3
    Online Resource
    Online Resource
    Wiley ; 2023
    In:  IEEJ Transactions on Electrical and Electronic Engineering Vol. 18, No. 9 ( 2023-09), p. 1427-1438
    In: IEEJ Transactions on Electrical and Electronic Engineering, Wiley, Vol. 18, No. 9 ( 2023-09), p. 1427-1438
    Abstract: Energy internet zones (EIZ) supply multiple energy carriers to customers in certain regions. They can achieve high energy efficiency by energy cascade utilization. In mid‐term, they participate in the wholesale market and retail market simultaneously. Customers can shift their energy use among different hours and energy carriers to satisfy demand according to the retail prices. Unfortunately, multiple energy systems and markets bring various uncertainties on demand and prices. In this paper, the weekly bidding strategy for the EIZ is proposed to determine the optimal bilateral contracts to sign and the optimal energy retail prices. In retail market, the satisfaction degree and elasticity matrix describe customers' response. Distributionally robust optimization is adopted to consider the distributional uncertainties of random variables and Worst‐case Conditional Value‐at‐Risk is employed for risk management. The distributional uncertainties of pool prices and elasticity matrix are discussed in this paper. An EIZ in Shanghai, China is adopted to illustrate the proposed strategy. The results have great resistance to distributional uncertainties. The risk aversion and satisfaction degree affect the EIZ's strategy in wholesale market and retail market, respectively. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.
    Type of Medium: Online Resource
    ISSN: 1931-4973 , 1931-4981
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2241861-1
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