Keywords given by authors of scientific articles in database descriptors

This paper analyses the keywords given by authors of scientific articles and the descriptors assigned to the articles in order to ascertain the presence of the keywords in the descriptors. 640 INSPEC, CAB abstracts, ISTA and LISA database records were consulted. After detailed comparisons it was found that keywords provided by authors have an important presence in the database descriptors studied, since nearly 25% of all the keywords appeared in exactly the same form as descriptors, with another 21% while normalized, are still detected in the descriptors. This means that almost 46% of keywords appear in the descriptors, either as such or after normalization. Elsewhere, three distinct indexing policies appear, one represented by INSPEC and LISA (indexers seem to have freedom to assign the descriptors they deem necessary); another is represented by CAB (no record has fewer than four descriptors and, in general, a large number of descriptors is employed; in contrast, in ISTA, a certain institutional code towards economy in indexing, since 84% of records contain only four descriptors

CSAC-Net: Fast Adaptive sEMG Recognition through Attention Convolution Network and Model-Agnostic Meta-Learning

Gesture recognition through surface electromyography (sEMG) provides a new method for the control algorithm of bionic limbs, which is a promising technology in the field of human–computer interaction. However, subject specificity of sEMG along with the offset of the electrode makes it challenging to develop a model that can quickly adapt to new subjects. In view of this, we introduce a new deep neural network called CSAC-Net. Firstly, we extract the time-frequency feature from the raw signal, which contains rich information. Secondly, we design a convolutional neural network supplemented by an attention mechanism for further feature extraction. Additionally, we propose to utilize model-agnostic meta-learning to adapt to new subjects and this learning strategy achieves better results than the state-of-the-art methods. By the basic experiment on CapgMyo and three ablation studies, we demonstrate the advancement of CSAC-Net

Imaging GPCR Dimerization in Living Cells with Cucurbit[7]uril and Hemicyanine as a “Turn-On” Fluorescence Probe

Although multiple forms of dimers have been described for GPCR, their dynamics and function are still controversially discussed field. Fluorescence microscopy allows GPCR to be imaged within their native context; however, a key challenge is to site-specifically incorporate reporter moieties that can produce high-quality signals upon formation of GPCR dimers. To this end, we propose a supramolecular sensor approach to detect agonist-induced dimer formation of μ-opioid receptors (μORs) at the surface of intact cells. With the macrocyclic host cucurbit[7]uril and its guest hemicyanine dye tethered to aptamer strands directed against the histidine residues, the sensing module is assembled by host–guest complexation once the histidine-tagged μORs dimerize and bring the discrete supramolecular units into close proximity. With the enhanced sensitivity attributed by the “turn-on” fluorescence emission and high specificity afforded by the intermolecular recognition, in situ visualization of dynamic GPCR dimerization was realized with high precision, thereby validating the supramolecular sensing entity as a sophisticated and versatile strategy to investigate GPCR dimers, which represent an obvious therapeutic target