Time Series Data Augmentation for Energy Consumption Data Based on Improved TimeGAN.

Predicting the time series energy consumption data of manufacturing processes can optimize energy management efficiency and reduce maintenance costs for enterprises. Using deep learning algorithms to establish prediction models for sensor data is an effective approach; however, the performance of these models is significantly influenced by the quantity and quality of the training data. In real production environments, the amount of time series data that can be collected during the manufacturing process is limited, which can lead to a decline in model performance.

Early functional and structural hippocampal impairment in a bilateral common carotid artery stenosis mouse model.

Background: Subcortical ischemic vascular dementia (SIVD) is a common subtype of vascular dementia. Currently, the bilateral common carotid artery stenosis (BCAS) mouse model is the most suitable SIVD rodent model. In this study, we investigated the functional and structural impairments in the hippocampus 1 month after BCAS.

Comparing the Rates of Further Resection After Intraoperative MRI Visualisation of Residual Tumour Between Brain Tumour Subtypes: A 17-Year Single-Centre Experience.

Background: Maximal safe resection is the objective of most neuro-oncological operations. Intraoperative magnetic resonance imaging (iMRI) may guide the surgeon to improve the extent of safe resection. There is limited evidence comparing the impact of iMRI on the rates of further resection between tumour types.

Comparing the efficacy of 3D-printing-assisted surgery with traditional surgical treatment of fracture: an umbrella review.

Background: The objective of this review is to evaluate the methodological quality of meta-analyses and observe the consistency of the evidence they generated to provide comprehensive and reliable evidence for the clinical use of three-dimensional (3D) printing in surgical treatment of fracture.

Methods: We searched three databases (PubMed, Embase, and Web of Science) up until August 2024. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards were adhered to in this review.

Astragalin inhibits neuronal excitability and activates neuronal autophagy in the ACC and LH of CFA mice to alleviate inflammatory pain and pain-related emotions.

Astragalin (AST), a natural flavonoid, exhibits anti-inflammatory, anti-cancer, and antioxidant properties. However, its effects and molecular mechanisms in inflammatory pain remain unclear. Therefore, this study aims to investigate the impact of AST on a Complete Freund's Adjuvant (CFA)-induced inflammatory pain mouse model and to elucidate its potential mechanisms.