Authors: Yan, Zhiyu | Lv, Shuang
Article Type: Research Article
Abstract: Accurate prediction of traffic flow is of great significance for alleviating urban traffic congestions. Most previous studies used historical traffic data, in which only one model or algorithm was adopted by the whole prediction space and the differences in various regions were ignored. In this context, based on time and space heterogeneity, a Classification and Regression Trees-K-Nearest Neighbor (CART-KNN) Hybrid Prediction model was proposed to predict short-term taxi demand. Firstly, a concentric partitioning method was applied to divide the test area into discrete small areas according to its boarding density level. Then the CART model was used to divide the …dataset of each area according to its temporal characteristics, and KNN was established for each subset by using the corresponding boarding density data to estimate the parameters of the KNN model. Finally, the proposed method was tested on the New York City Taxi and Limousine Commission (TLC) data, and the traditional KNN model, backpropagation (BP) neural network, long-short term memory model (LSTM) were used to compare with the proposed CART-KNN model. The selected models were used to predict the demand for taxis in New York City, and the Kriging Interpolation was used to obtain all the regional predictions. From the results, it can be suggested that the proposed CART-KNN model performed better than other general models by showing smaller mean absolute percentage error (MAPE) and root mean square error (RMSE) value. The improvement of prediction accuracy of CART-KNN model is helpful to understand the regional demand pattern to partition the boarding density data from the time and space dimensions. The partition method can be extended into many models using traffic data. Show more
Keywords: Short-term taxi demand forecast, CART-KNN hybrid prediction model, spatial and temporal heterogeneity, concentric partitioning, time series
DOI: 10.3233/JIFS-210872
Citation: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 2, pp. 4175-4186, 2021
Authors: Zhang, Shujuan | Wei, Dongfeng | Lv, Shuang | Wang, Lei | An, Haiting | Shao, Wen | Wang, Yun | Huang, Yaping | Peng, Dantao | Zhang, Zhanjun
Article Type: Research Article
Abstract: Background: Scutellarin, a flavonoid purified from the Chinese herb Erigeron breviscapus , has been reported to prevent Alzheimer’s disease (AD) by affecting Aβ assembly. Given the low brain uptake rate of scutellarin, we hypothesize that the microbiota-gut-brain axis may be a potential route by which scutellarin prevents AD. Objective: This study aimed to explore the microbiota-gut-brain mechanism by which scutellarin prevented AD. Methods: Scutellarin was administrated to APP/PS1 mouse model of AD for two months, and the behaviors, pathological changes as well as gut microbial changes in APP/PS1 mice were evaluated after scutellarin treatment. Results: This study found that scutellarin …improved Aβ pathology, neuroinflammation, and cognitive deficits in APP/PS1 mice. It elucidated the effects of scutellarin on the diversity and activity of gut microbiota in APP/PS1 mice and these findings promoted us to focus on inflammation-related bacteria and short-chain fatty acids (SCFAs). Cognitive behaviors were significantly associated with inflammatory cytokines and inflammation-related bacteria, suggesting that microbiota-gut-brain axis was involved in this model and that inflammatory pathway played a crucial role in this axis. Moreover, we observed that cAMP-PKA-CREB-HDAC3 pathway downstream of SCFAs was activated in microglia of AD and inactivated by scutellarin. Furthermore, by chromatin immunoprecipitation (ChIP) assays, we found that the increased association between acetylated histone 3 and interleukin-1β (IL-1β) promoter in AD mice was reversed by scutellarin, leading to a decreased level of IL-1β in scutellarin-treated AD mice. Conclusion: Scutellarin reverses neuroinflammation and cognitive impairment in APP/PS1 mice via beneficial regulation of gut microbiota and cAMP-PKA-CREB-HDAC3 signaling in microglia. Show more
Keywords: Alzheimer’s disease, cAMP-response element binding protein (CREB), cyclic adenosine monophosphate (cAMP), gut microbiota, histone deacetylase, interleukin, protein kinase, scutellarin
DOI: 10.3233/JAD-220532
Citation: Journal of Alzheimer's Disease, vol. 89, no. 3, pp. 955-975, 2022