Recently, wearable devices have been attracting significantly increased interest in human motion detection and human physiological signal monitoring. Currently, it is still a great challenge to fabricate strain sensors with high performance and good fit to the human body. In this work, we fabricated a close-fitting and wearable graphene textile strain sensor based on a graphene textile without polymer encapsulation. Graphene oxide acts as a colorant to dye the polyester fabric and is reduced at high temperature, which endows the graphene textile strain sensor with excellent performance. Compared with the previously reported strain sensors, our strain sensor exhibits a distinctive negative resistance variation with increasing strain. In addition, the sensor also demonstrates fascinating performance, including high sensitivity, long-term stability, and great comfort. Based on its superior performance, the graphene textile strain sensor can be knitted on clothing for detecting both subtle and large human motions, showing the tremendous potential for applications in wearable electronics.

Intraocular pressure (IOP) is the prime indicator for the diagnosis and treatment of glaucoma. IOP has circadian rhythm changes and is dependent on body gestures; therefore, a single measurement in the clinic can be misleading for diagnosis. Herein, few-layer graphene is utilized to develop non-invasive sensors with high transparency, sensitivity, linearity, and biocompatibility for 24 h continuous IOP monitoring. The graphene Wheatstone bridge consisting of two strain gauges and two compensating resistors is designed to improve the sensitivity and accuracy of IOP measurement. Testing results on a silicone eyeball indicate that the output voltage of the sensor is proportional to the IOP fluctuation. Under the various ranges and speeds of IOP fluctuation, the sensor exhibits excellent performance of dynamic cycles and step responses with an average sensitivity of 150 μV/mmHg. With the linear relationship, the average relative error between the calibrated IOP and the standard pressure is maintained at about 5%. More than 100 cycles and interval time measurements illustrate that the sensor possesses significant stability, durability, and reliability. Furthermore, a wireless system is designed for the sensor to realize IOP monitoring using a mobile phone. This sensor, with the average transparency of 85% and its ease of fabrication, as well as its portability for continuous IOP monitoring, brings new promise to the diagnosis and treatment of glaucoma.

Recently, flexible and wearable mechanical sensors have attracted great attention because of their potential applications in monitoring various physiological signals. However, conventional mechanical sensors rarely have both pressure and strain sensing abilities that can meet the demands of both subtle and large human motion detection. Besides, the mechanical sensors with tunable sensitivity or measuring range are also essential for their practical applications. Herein, the graphene ink dip-coating method with merits of time saving, low cost, and large scale was used to fabricate the foam-structured graphene sensors with both pressure and strain sensing performance. Because of high elasticity of styrene butadiene rubber (SBR) substrates and stacked graphene flakes, the tunable mechanical sensors exhibit a high gauge factor (GF) and large measuring range for specific human motion detection. The pressure sensor shows a GF of 2.02 kPa −1 with a pressure range up to 172 kPa, and the strain sensor displays a GF of 250 with a strain range up to 86%. On the one hand, various detections of subtle vital signals with small strain change were demonstrated by the pressure sensor because of its flexibility and high sensitivity. On another hand, the strain sensor with large strain change shows excellent ability to detect various large human motions including the bending of neck, finger, wrist, and knee. Interestingly, both the pressure sensor and strain sensor exhibit great capability for recognizing 26 letters written by hand. The working mechanism based on the contact area variation was also investigated by the morphology evolution and resistance model. We suppose that the foam-structured graphene mechanical sensors would be promising in wearable electronics for human healthcare and activity monitoring in the future.

This paper describes the technology and an experiment of subcategorization acquisition for Chinese verbs. The SCF hypotheses are generated by means of linguistic heuristic information and filtered via statistical methods. Evaluation on the acquisition of 20 multi-pattern verbs shows that our experiment achieved the similar precision and recall with former researches. Besides, simple application of the acquired lexicon to a PCFG parser indicates great potentialities of subcategorization information in the fields of NLP. Credits

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Hyperspectral images are of high spectral resolution and have been widely used in many applications, but the imaging process to achieve high spectral resolution is at the expense of spatial resolution. This paper aims to construct a high-spatial-resolution hyperspectral (HHS) image from a highspatial-resolution RGB image, by proposing a novel class-based spectral super-resolution method. With the help of a set of RGB and HHS image-pairs, our proposed method learns nonlinear spectral mappings between RGB and HHS image-pairs using class-based back propagation neural networks (BPNNs). In the training stage, unsupervised clustering is used to divide an RGB image into several classes according to spectral correlation, and the spectrum-pairs from the classified RGB images and the corresponding HHS images are used to train the BPNNs, to establish the nonlinear spectral mapping for each class. In the spectral super-resolution stage, a supervised classification is used to classify the given RGB image into the classes determined during the training stage, and the final HHS image is reconstructed from the classified given RGB image using the trained BPNNs. Comparisons on three standard datasets, ICVL, CAVE and NUS, demonstrate that, our proposed method achieves a better spectral super-resolution quality than related state-of-the-art methods.

Photochromism, fluorescence, and ultra‐long room temperature phosphorescence (URTP) are attractive phenomena in photonics. However, achieving multiple optical properties such as photochromism, fluorescence, and URTP on one material still remains a challenge. Here, the authors report a multifunctional optical polymeric film with photochromic, fluorescent, and URTP properties, fabricated by simply doping the naphthopyran molecule into epoxy polymer with 3D network. When the polymer network is loose, the naphthopyran‐doped film exhibits photochromic property but no fluorescence and phosphorescence. When the polymer network becomes dense, the film shows fluorescent and URTP behaviors but no photochromic property. It is noted that the room temperature phosphorescence lifetime is as high as 604 ms. Based on the excellent optical properties of reversible photochromism, fluorescence, and URTP, an advanced sixfold encryption application has been successfully established. This work not only opens up a new direction in design and fabrication of multifunctional optical materials but also offers principles for developing organic optical materials toward multilevel information encryption and data storage.

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