Construction of Smart Grid Load Forecast Model by Edge Computing

This research aims to minimize the unnecessary resource consumption by intelligent Power Grid Systems (PGSs). Edge Computing (EC) technology is used to forecast PGS load and optimize the PGS load forecasting model. Following a literature review of EC and Internet of Things (IoT)-native edge devices, an intelligent PGS-oriented Resource Management Scheme (RMS) and PGS load forecasting model are proposed based on task offloading. Simultaneously, an online delay-aware power Resource Allocation Algorithm (RAA) is developed for EC architecture. Finally, comparing three algorithms corroborate that the system overhead decreases significantly with the model iteration. From the 40th iteration, the system overhead stabilizes. Moreover, given no more than 50 users, the average user delay of the proposed delay-aware power RAA is less than 13 s. The average delay of the proposed algorithm is better than that of the other two algorithms. This research contributes to optimizing intelligent PGS in smart cities and improving power transmission efficiency

VGSG: Vision-Guided Semantic-Group Network for Text-based Person Search

Text-based Person Search (TBPS) aims to retrieve images of target pedestrian indicated by textual descriptions. It is essential for TBPS to extract fine-grained local features and align them crossing modality. Existing methods utilize external tools or heavy cross-modal interaction to achieve explicit alignment of cross-modal fine-grained features, which is inefficient and time-consuming. In this work, we propose a Vision-Guided Semantic-Group Network (VGSG) for text-based person search to extract well-aligned fine-grained visual and textual features. In the proposed VGSG, we develop a Semantic-Group Textual Learning (SGTL) module and a Vision-guided Knowledge Transfer (VGKT) module to extract textual local features under the guidance of visual local clues. In SGTL, in order to obtain the local textual representation, we group textual features from the channel dimension based on the semantic cues of language expression, which encourages similar semantic patterns to be grouped implicitly without external tools. In VGKT, a vision-guided attention is employed to extract visual-related textual features, which are inherently aligned with visual cues and termed vision-guided textual features. Furthermore, we design a relational knowledge transfer, including a vision-language similarity transfer and a class probability transfer, to adaptively propagate information of the vision-guided textual features to semantic-group textual features. With the help of relational knowledge transfer, VGKT is capable of aligning semantic-group textual features with corresponding visual features without external tools and complex pairwise interaction. Experimental results on two challenging benchmarks demonstrate its superiority over state-of-the-art methods.Comment: Accepted to IEEE TI

A quasi-droplet optofluidic ring resonator laser using a micro-bubble

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98697/1/ApplPhysLett_99_091102.pd

Tunable single mode lasing from an on-chip optofluidic ring resonator laser

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98677/1/ApplPhysLett_98_061103.pd

Effect of hyperbaric oxygen therapy on cognitive impairment after aneurysm subarachnoid hemorrhage

Purpose: To evaluate the effect of hyperbaric oxygen therapy (HBOT) on cognitive impairment after aneurysm subarachnoid hemorrhage (aSAH). Methods: The current study was carried out in a regional neurosurgical center in Taiyuan, Shanxi Province of China from January 2019 to September 2020. A total of 150 patients with persistent cognitive dysfunction at 3 months after aSAH onset were enrolled, which were randomly classified into group A (HBOT) and group B (control) via the random number table method. The outcome was evaluated by Montreal cognitive assessment (MoCA). Results: There were no significant differences between group A and group B with regard to MoCA score and proportions of normal MoCA patients at 3 months after HBOT (p > 0.05). Both groups showed no significant differences in proportions of normal MoCA patients at 6 months after HBOT (p > 0.05). However, there were significant differences between group A and group B with MoCA score of patients at 6 months after HBOT (p < 0.05). There were also significant differences in MoCA score and proportions of normal MoCA patients at 9 months after HBOT. Conclusion: HBOT alleviates cognitive impairment after aSAH, and thus may be used to manage cognitive impairment in patients after aSAH. However, further clinical trials are required prior to application in clinical practice

Dihydromyricetin attenuates depressive-like behaviors in mice by inhibiting the AGE-RAGE signaling pathway

Depression is a complex mental disorder, affecting approximately 280 million individuals globally. The pathobiology of depression is not fully understood, and the development of new treatments is urgently needed. Dihydromyricetin (DHM) is a natural flavanone, mainly distributed in Ampelopsis grossedentata. DHM has demonstrated a protective role against cardiovascular disease, diabetes, liver disease, cancer, kidney injury and neurodegenerative disorders. In the present study, we examined the protective effect of DHM against depression in a chronic depression mouse model induced by corticosterone (CORT). Animals exposed to CORT displayed depressive-like behaviors; DHM treatment reversed these behaviors. Network pharmacology analyses showed that DHM’s function against depression involved a wide range of targets and signaling pathways, among which the inflammation-linked targets and signaling pathways were critical. Western blotting showed that CORT-treated animals had significantly increased levels of the advanced glycation end product (AGE) and receptor of AGE (RAGE) in the hippocampus, implicating activation of the AGE-RAGE signaling pathway. Furthermore, enzyme-linked immunosorbent assay (ELISA) detected a marked increase in the production of proinflammatory cytokines, interleukin-1 beta (IL-1β), IL-6 and tumor necrosis factor-alpha (TNFα) in the hippocampus of CORT-treated mice. DHM administration significantly counteracted these CORT-induced changes. These findings suggest that protection against depression by DHM is mediated by suppression of neuroinflammation, predominantly via the AGE-RAGE signaling pathway