Flexible sensors, friendly interfaces, and intelligent recognition are important in the research of novel human-computer interaction and the development of smart devices. However, major challenges are still encountered in designing user-centered smart devices with natural, convenient, and efficient interfaces. Inspired by the characteristics of textile-based flexible electronic sensors, in this article, we report a braided electronic cord with a low-cost, and automated fabrication to realize imperceptible, designable, and scalable user interfaces. The braided electronic cord is in a miniaturized form, which is suitable for being integrated with various occasions in life. To achieve high-precision interaction, a multi-feature fusion algorithm is designed to recognize gestures of different positions, different contact areas, and different movements performed on a single braided electronic cord. The recognized action results are fed back to varieties of interactive terminals, which show the diversity of cord forms and applications. Our braided electronic cord with the features of user friendliness, excellent durability and rich interaction mode will greatly promote the development of human-machine integration in the future. 

/pdf/imperceptible-designable-and-scalable-braided-electronic-3o77rjs8.pdf

Imperceptible, designable, and scalable braided electronic cord

Endowing flexible and adaptable fiber devices with light-emitting capabilities has the potential to revolutionize the current design philosophy of intelligent, wearable interactive devices. However, significant challenges remain in developing fiber devices when it comes to achieving uniform and customizable light effects while utilizing lightweight hardware. Here, we introduce a mass-produced, wearable, and interactive photochromic fiber that provides uniform multicolored light control. We designed independent waveguides inside the fiber to maintain total internal reflection of light as it traverses the fiber. The impact of excessive light leakage on the overall illuminance can be reduced by utilizing the saturable absorption effect of fluorescent materials to ensure light emission uniformity along the transmission direction. In addition, we coupled various fluorescent composite materials inside the fiber to achieve artificially controllable spectral radiation of multiple color systems in a single fiber. We prepared fibers on mass-produced kilometer-long using the thermal drawing method. The fibers can be directly integrated into daily wearable devices or clothing in various patterns and combined with other signal input components to control and display patterns as needed. This work provides a new perspective and inspiration to the existing field of fiber display interaction, paving the way for future human-machine integration. 

Wearable and interactive multicolored photochromic fiber display

Unmanned aerial vehicle(UAV)-enabled mobile edge computing(MEC) networks provide ubiquitous communication and computing capacity for mobile users compared with terrestrial networks. In crowd management, the UAV base station(UAV-BS) collect computation tasks from the Internet of Things (IoT) devices and process tasks with terrestrial MEC networks cooperatively. However, energy efficiency(EE) and user mobility are the bottlenecks of UAV performance. Therefore, it is crucial to maximizing the energy efficiency(EE) of UAVs. In this paper, we propose an energy-efficient UAV-enabled MEC network composed of IoT devices, the UAV-BS, edge cloud, and the data center, and propose a Green-UAV-CoCaCo algorithm to jointly optimize communications, caching, and computation for EE of UAV. Specifically, we design a UAV trajectory model based on a greedy algorithm to predict the user’s coordinates and choose the proper edge server for task offloading. Then, the UAV-CoCaCo algorithm is proposed to maximize the EE of the task caching and offloading. Simulation results demonstrate the effectiveness of the proposed algorithm. 

Energy Efficient Task Caching and Offloading in UAV-Enabled Crowd Management

With the large-scale commercialization of 5G, the global industry has started the exploration of the next generation mobile communication technology (6G). From mobile Internet, to IoT, and then to the smart connection of everything, 6G will transform from 5G’s service objects of people and things to the intelligent networking of agent that supports human–machine–object. 6G networks should have the characteristics of ubiquitous intelligence and ubiquitous perception, which poses challenges for 6G network construction. Therefore, we propose a 6G Semantic Communication Scheme based on Intelligent Fabrics for transportation in-cabin scenarios (6GSCS-IF), which can provide senseless intelligent interaction in transportation in-cabin environment through widely and flexibly deployed intelligent fabrics, demonstrating the superiority of intelligent fabrics in realizing human–machine–object intelligent sensory interaction. Then, we propose a Deep Learning-based Semantic Communication Model for Time-series data (DL-SCMT), and use deep learning for semantic sensing and information extraction to build an end-to-end semantic communication system. The experimental results show that the semantic communication services provided by this model can achieve better signal reconstruction and higher-order intelligent services compared with traditional communication methods.

Intelligent Fabric Enabled 6G Semantic Communication System for In-Cabin Scenarios

Breathable and comfortable sensing textiles that can detect multi-biomarkers existing in human sweat are a promising way to achieve comprehensive health monitoring in our daily life. However, current wearable and flexible electrochemical textiles lack stretchability, which can result in unstable signals or device damage during movement. Additionally, these textiles have limited integration of multiple indicators, needing a large surface area and a significant amount of sweat to activate the sensors. Herein, we report an integrated all-in-one multifunctional electrochemical biosensor fiber constructed with a helical core-sheath structure, offering the stretchability and ability to detect biomarkers with trace amounts of sweat. The biosensor was fabricated by arranging multi-functionalized carbon nanotube strips in a spiral pattern alongside a pre-stretched polymer fiber core acting as microelectrodes with robust interface. Additionally, a super-hydrophilic sheath layer is incorporated to enhance the sweat capture efficiency of the biosensor. The biosensor has the capability to simultaneously monitor six biomarkers including pH, K+, Na+, glucose, lactate and uric acid, demonstrating stable sensing performance under 300% strain. Merely 1 of sweat is needed to initiate the detection of all six biomarkers. The resulting textile sensing system presents continuous and real-time monitoring of multi-biomarker information, allowing for the assessment of our health condition. 

一体化可拉伸的多功能电化学传感纤维构建微量汗 液健康监测织物

Medical education plays an important role in promoting the development of global medical science. Nevertheless, the intrinsic gap existing between institutional medical teaching and practical clinical tasks causes low education efficiency and students’ weak initiative. Recent developments of sensing fabric and embedded computing, along with the advances in Artificial intelligence (AI) and digital twin technology are paving the way for the transformation of medical research towards digitization. In this work, we present an intelligent fabric space based on novel functional fabric materials and digital twin networking enabled by 5G and Internet of Things (IoT) technologies. In this space, medical students can learn knowledge with collaborative mapping of the digital and real world, cyber-physical interaction and real-time tactile feedback. And the proposed service system will evaluate and feedback students’ operational behaviors to improve their experimental skills. We provide four typical applications of intelligent fabric space for medical education, including medical education training, health and behavior tracking, operation playback and reproduction, as well as medical knowledge popularization. The proposed intelligent fabric space has the potential to promote innovative technologies for training cutting-edge medical students by effective and efficient ways.

https://www.nso-journal.org/articles/nso/pdf/2022/01/nso220005s.pdf

Digital Medical Education Empowered by Intelligent Fabric Space

A review of the current research on in vivo and in vitro detection for alpha-synuclein: a biomarker of Parkinson’s disease

Background Increasing studies demonstrated the importance of activation of neutrophils in the pathogenesis of antineutrophil cytoplasmic autoantibody (ANCA)-associated vasculitis (AAV). Previous studies showed that annexin A1 (ANXA1) inhibited the recruitment, transendothelial migration and respiratory burst of neutrophils and induced apoptosis of neutrophils. The current study aimed to investigate the plasma and renal levels of ANXA1 as well as their association with the disease severity in AAV patients. Methods Thirty-one AAV patients in active stage and 35 AAV patients in remission stage were recruited. The expression of ANXA1 in renal specimens was assessed by immunohistochemistry. The co-localization of ANXA1 with renal intrinsic and infiltrating cells was detected by double immunofluorescence. The plasma levels of ANXA1 were determined by ELISA. The association of plasma and renal levels of ANXA1 with clinicopathological parameters was further analyzed. Results Plasma levels of ANXA1 were significantly higher in active AAV patients than those in AAV patients in remission as well as healthy controls. The renal expression of ANXA1 was significantly higher in active AAV patients than in healthy controls and disease controls. Double immunofluorescence assay showed that ANXA1 was expressed in glomerular endothelial cells, mesangial cells, podocytes, proximal tubular epithelial cells, neutrophils, monocytes/macrophages and T cells in AAV patients. The mean optical density of ANXA1 in glomeruli was correlated with serum creatinine levels (r = −0.491, P = 0.005) and eGFR (r = 0.492, P = 0.005) at renal biopsy and the proportion of crescents (r = −0.423, P = 0.018) in renal specimens of AAV patients. The expression of ANXA1 in glomeruli of AAV patients achieving complete renal recovery was significantly higher than those achieving partial renal recovery. Conclusion In AAV patients, the renal expression of ANXA1 was associated with the severity of renal injury.

/pdf/renal-expression-of-annexin-a1-is-associated-with-the-1s4qv5mv.pdf

Renal Expression of Annexin A1 Is Associated With the Severity of Renal Injury in Antineutrophil Cytoplasmic Autoantibody-Associated Vasculitis

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Digital Medical Education Empowered by Intelligent Fabric Space

A review of the current research on in vivo and in vitro detection for alpha-synuclein: a biomarker of Parkinson’s disease

Renal Expression of Annexin A1 Is Associated With the Severity of Renal Injury in Antineutrophil Cytoplasmic Autoantibody-Associated Vasculitis