Spatial-temporal Transformers for EEG Emotion Recognition

Electroencephalography (EEG) is a popular and effective tool for emotion recognition. However, the propagation mechanisms of EEG in the human brain and its intrinsic correlation with emotions are still obscure to researchers. This work proposes four variant transformer frameworks~(spatial attention, temporal attention, sequential spatial-temporal attention and simultaneous spatial-temporal attention) for EEG emotion recognition to explore the relationship between emotion and spatial-temporal EEG features. Specifically, spatial attention and temporal attention are to learn the topological structure information and time-varying EEG characteristics for emotion recognition respectively. Sequential spatial-temporal attention does the spatial attention within a one-second segment and temporal attention within one sample sequentially to explore the influence degree of emotional stimulation on EEG signals of diverse EEG electrodes in the same temporal segment. The simultaneous spatial-temporal attention, whose spatial and temporal attention are performed simultaneously, is used to model the relationship between different spatial features in different time segments. The experimental results demonstrate that simultaneous spatial-temporal attention leads to the best emotion recognition accuracy among the design choices, indicating modeling the correlation of spatial and temporal features of EEG signals is significant to emotion recognition

Measurement and Analysis of the Swarm Social Network With Tens of Millions of Nodes

Social graphs have been widely used for representing the relationship among users in online social networks (OSNs). As crawling an entire OSN is resource-and time-consuming, most of the existing works only pick a sampled subgraph for study. However, this may introduce serious inaccuracy into the analytic results, not to mention that some important metrics cannot even be calculated. In this paper, we crawl the entire social network of Swarm, a leading mobile social app with more than 60 million users, using a distributed approach. Based on the crawled massive user data, we conduct a data-driven study to get a comprehensive picture of the whole Swarm social network. This paper provides a deep analysis of social interactions between Swarm users, and reveals the relationship between social connectivity and check-in activities.Peer reviewe

Transdifferentiation of pancreatic stromal tumor into leiomyosarcoma with metastases to liver and peritoneum: a case report

Follow-up ultrasound and abdominal CT radiographs at 6-month (A), 10-month (B, C, D) and 13-month follow-up (E, F) examination. CT, computed tomography. (TIF 2862 kb

Energy transfer in zinc porphyrin–phthalocyanine heterotrimer and heterononamer studied by fluorescence resonance energy transfer (FRET)

Two or eight zinc triphenyl porphyrins were conjugated with Zn-phthalocyanine or H2-phthalocyanine to form ZnPc–(ZnTPP)2, ZnPc–(ZnTPP)8, H2Pc–(ZnTPP)2 and H2Pc–(ZnTPP)8. Energy transfers from the porphyrin moiety to phthalocyanine part were quantitatively studied with the modality of fluorescence resonance energy transfer (FRET). By measuring the fluorescence increment from the phthalocyanine moiety and the decrease from porphyrin part under selective excitation at the B band of the porphyrin part in those conjugated compounds and their equimolar mixture of compositions, energy transfer efficiencies were estimated to be 90% for H2Pc–(ZnTPP)8 and ZnPc–(ZnTPP)8, and 60%, 30% for ZnPc–(ZnTPP)2 and H2Pc–(ZnTPP)2, respectively

Thundercloud induced spatial ion flow in the neighborhood of rotating wind turbine and impact mechanism on corona inception

Lightning accidents seriously threaten the safe operation of wind turbines due to the unclear initiation mechanism of the airborne lightning-induced discharges on turbine blades, in which turbine rotation is one of the principal influencing factors. To study the impact mechanism of wind turbine rotation on corona discharge inception, a numerical model with the dynamic meshing of charged ions in the neighboring space of a large-scale rotating wind turbine during a thunderstorm was established in this article, and the validity of the model was verified by long gap discharge experiments on a scaled wind turbine. Based on the proposed model, the spatial and temporal distributions of charged particles in the neighboring area of the rotating wind turbine and the space charge-caused local electric field distortion scenario were obtained. The influence mechanism of blade rotation on corona discharge inception was further analyzed and elucidated accordingly. The results indicate that the charged particles are unevenly distributed near the rotating blade tip, and the contours present a strip-like shape, the critical area of which may facilitate corona discharge inception. As the blade speed increases from 6 to 20 rpm, the E-field extremum at the blade tip increases by 38%, causing the blade tip prone to initiate corona discharge. The critical rotating speeds corresponding to corona inception probability were calculated under different thundercloud-determined field strengths, and a safe boundary was defined, by which it is recommended that wind turbines operate at a reduced speed below 8 rpm under thundercloud conditions

Integrative analysis of the metabolome and transcriptome reveals the molecular mechanism of chlorogenic acid synthesis in peach fruit

As the most abundant phenolic acid in peach fruit, chlorogenic acid (CGA) is an important entry point for the development of natural dietary supplements and functional foods. However, the metabolic and regulation mechanisms underlying its accumulation in peach fruits remain unclear. In this study, we evaluated the composition and content of CGAs in mature fruits of 205 peach cultivars. In peach fruits, three forms of CGA (52.57%), neochlorogenic acid (NCGA, 47.13%), and cryptochlorogenic acid (CCGA, 0.30%) were identified. During the growth and development of peach fruits, the content of CGAs generally showed a trend of rising first and then decreasing. Notably, the contents of quinic acid, shikimic acid, p-coumaroyl quinic acid, and caffeoyl shikimic acid all showed similar dynamic patterns to that of CGA, which might provide the precursor material basis for the accumulation of CGA in the later stage. Moreover, CGA, lignin, and anthocyanins might have a certain correlation and these compounds work together to maintain a dynamic balance. By the comparative transcriptome analysis, 8 structural genes (Pp4CL, PpCYP98A, and PpHCT) and 15 regulatory genes (PpMYB, PpWRKY, PpERF, PpbHLH, and PpWD40) were initially screened as candidate genes of CGA biosynthesis. Our findings preliminarily analyzed the metabolic and molecular regulation mechanisms of CGA biosynthesis in peach fruit, which provided a theoretical basis for developing high-CGA content peaches in future breeding programs