34 research outputs found
Quantifying the heterogeneous impacts of the urban built environment on traffic carbon emissions: New insights from machine learning techniques
No full textThe configuration of the urban built environment is critical for promoting sustainability and achieving carbon neutrality. However, existing studies mostly use linear and spatial econometric models to investigate the relationship between urban built environments and traffic carbon dioxide (CO2) emissions, in-depth studies exploring the heterogeneous impacts of related features on traffic CO2 emission by interpretive machine learning models are scarce. Hence, we extract four dimensionless features to depict the size, compactness, irregularity, and isolation of built-up areas, and road network-related features (i.e., average cluster coefficient, road topological density, and road geometric density), respectively. Subsequently, we develop an interpretive machine learning framework based on the extracted features related to the urban built-up areas and road networks. The interpretive results of the proposed framework uncover that urban morphological features, especially population density (POP), GDP per capita (GDPpc), and urban physical compactness (UPC), have a heterogeneous impact on the per capita traffic emission (PCCE) across different cities. GDPpc is more like a linear relationship with PCCE, and UPC has a significant influence on PCCE when its value is between 62% and 78%. Our results also reveal the nonlinear relationships and interactive effects between these features, providing the implications of urban morphological planning and carbon emission reduction.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and Plannin
Model and Data-Driven Combination: A Fault Diagnosis and Localization Method for Unknown Fault Size of Quadrotor UAV Actuator Based on Extended State Observer and Deep Forest
No full textThe rotor is an essential actuator of quadrotor UAV, and is prone to failure due to high speed rotation and environmental disturbances. It is difficult to diagnose rotor faults and identify the fault localization simultaneously. In this paper, we propose a fault diagnosis and localization scheme based on the Extended State Observer (ESO) and Deep Forest (DF). This scheme can accurately complete the fault diagnosis and localization for the quadrotor UAV actuator without knowing the fault size by combining the model-based and the data-driven methods. First, we obtain the angular acceleration residual signal of the quadrotor UAV by using ESO. The residual signal is the difference between the observed state of ESO and the true fault state. Then, we design the residual feature analysis method by considering the position distribution of the quadrotor UAV actuator. This method can embed the actuator fault localization information into the fault data by simultaneously considering pitch and roll of the quadrotor UAV. Finally, we complete the fault diagnosis and localization of the quadrotor UAV actuator by processing the fault data by using DF. This scheme has the advantages of straightforward observer modeling, strong generalization ability, adaptability to small sample data, and few hyperparameters. Our simulation results indicate that the accuracy of the proposed scheme reaches more than 99% for the unknown size of the quadrotor UAV actuator fault
Estimating the effect of air quality on Bike-Sharing usage in Shanghai, China: An instrumental variable approach
No full textRecent years have seen a surge in shared mobility. Amid various emerging shared mobility services, bike-sharing has received growing popularity for its economic affordability. Meanwhile, the “green” reputation of bike-sharing has also been widely acknowledged by the general public. The two-way causal relationship between environmental quality and bike-sharing posits a virtuous circle that environmental quality improvement leads to increasing bike-sharing demand, and more bike-sharing trips contribute to better environmental quality. While numerous efforts have been made to explore the environmental benefits of bike-sharing systems, relevant studies examining the impacts of environmental quality on bike-sharing behaviors are lacking. Given its importance in transportation and environmental sustainability, this study aims to examine the impacts of air quality on bike-sharing demand in Shanghai, China, in August 2016 through a fixed-effect two-stage least square (FE-2SLS) model, where wind speed and thermal inversion are innovatively adopted as the instrumental variables. The findings show that a unit decrease in PM2.5 concentrations is associated with a 2,517 increase in daily bike-sharing trips in Shanghai. Alternatively, an additional 0.78 million bike-sharing trips per month could be generated during summer seasons if Shanghai's summer-time PM2.5 levels could meet WHO's interim target of 10 μg/m3. Due to substantial economic, environmental, and public health benefits arising from bike-sharing trips and air quality improvements, our findings provide compelling evidence for policymakers to devote continued efforts to air pollution control and increased investments in bike-sharing systems.</p
WCN24-1965 CELLULAR PRION PROTEIN ATTENUATES RENAL FIBROSIS BY INTERACTING WITH TSPAN7 TO INDUCE FORMATION OF MIGRASOME
No full textMetro-line expansions and local air quality in Shenzhen: Focusing on network effects
No full textWe examine the air-quality effects of urban-rail development in Shenzhen, taking a difference-in-differences approach. This study is motivated by existing mixed evidence on the rail-pollution relationship, which we associate with the dynamic nature of the relationship itself. Our results demonstrate that the relationship varies by time, depending on network density and scale. New station openings had no significant impacts on local air quality or even worsened it until the 2010 metro-line extension, when Shenzhen’s metro network density was still low, with limited spatial service coverage. However, the 2016 extension significantly abated air pollution as the network grew denser and more comprehensive. The rail-driven anti-pollution effects tended to be further strengthened with externalities arising from improved network connectivity, spilling over the effects beyond newly opened stations to preexisting ones. Also, metro stations in proximity to neighborhoods that share key characteristics in transit-oriented development tended to generate a greater anti-pollution effect
Using geographical semi-variogram method to quantify the difference between NO2 and PM2.5 spatial distribution characteristics in urban areas
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Unraveling the Surrounding Drivers of Interprovincial Trade Embodied Energy Flow Based on the MRIO Model: A Case Study in China
No full textTo achieve the carbon neutrality target, China has proposed “dual control” policies on provincial energy consumption. However, inter-provincial trade drives significant embodied energy flows beyond local demand. How do we identify key energy consumers driving through other provinces? And how does energy, especially from coal, flow to other provinces? Current studies analyzed regional and sectoral energy flow, which are always separated. And seldom was attention paid to coal flow. Intending to identify the critical energy-consuming province in China and investigate how energy and coal flow out from it, this study applied the EE-MRIO model to measure energy and coal embodied in provincial trades. The results suggest the following: (1) The energy embodied in provincial trade was mostly from energy-rich regions to provinces that lacked energy but had developed economies. Shanxi is a critical embodied-energy export province; (2) neighboring provinces and economically developed provinces drive the most embodied energy from Shanxi, and embodied energy mainly flows from the energy sectors and high-energy-intensity sectors; and (3) the provincial and sectoral coal flow in Shanxi presents consistent characteristics of embodied energy flow. We contributed to understanding the energy equity affected by embodied energy flow and propose energy consumption as a relieving measure
Cordycepin Ameliorates Renal Interstitial Fibrosis by Inhibiting Drp1-Mediated Mitochondrial Fission
No full textYingxue Sun,1,* Shi Jin,1,* Jun Chen,2,* Jian Zhang,1 Yufei Lu,1 Qiuyu Gu,1 Zhixin Yan,1 Weize Chen,1 Annan Chen,1 Yi Fang,1 Wenye Geng,3 Xialian Xu,1 Nana Song1 1Department of Nephrology, Zhongshan Hospital, Fudan University; Shanghai Medical Center of Kidney; Shanghai Institute of Kidney and Dialysis; Shanghai Key Laboratory of Kidney and Blood Purification; Hemodialysis Quality Control Center of Shanghai, Shanghai, 200032, People’s Republic of China; 2Department of Pathology, Changzheng Hospital, Naval Military Medical University, Shanghai, 200003, People’s Republic of China; 3Scientific Research Department of Shanghai Medical College, Fudan Zhangjiang Institute, Fudan University, Shanghai, 201203, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xialian Xu; Nana Song, Division of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, People’s Republic of China, Tel +86-021-64041990-2138, Fax +86-021-64038038, Email [email protected]; [email protected]: This study aimed to investigate the mechanisms and specific targets of cordycepin in the treatment of renal fibrosis using a unilateral ischemia-reperfusion (UIR) model.Methods: A UIR mouse model was established, followed by intraperitoneal injections of cordycepin and Mdivi-1. Masson’s trichrome staining and PAS staining were used to identify renal tubulointerstitial fibrosis and assess the degree of renal injury. Fibrosis markers and mitochondrial dynamics-related proteins were evaluated using Western blotting, while differential gene expression and pathway enrichment were analyzed by RNA-seq. Molecular docking, molecular dynamics simulations and surface plasmon resonance were conducted to validate the specific binding sites of cordycepin on the target protein Drp1. Immunofluorescence and in vitro experiments further elucidated the therapeutic mechanism of cordycepin.Results: In vivo experiments showed that intraperitoneal injection of cordycepin significantly reduced renal inflammation and fibrosis, lowered serum creatinine levels, and decreased collagen deposition. Transcriptome analysis revealed that cordycepin treatment downregulated the mitochondrial fission pathway and upregulated the mitochondrial fusion pathway. Western blotting showed reduced levels of fibrosis markers α-SMA and FN, as well as downregulation of Drp1, MFF, and Fis1, and upregulation of OPA1 and Mfn2. In vitro, cordycepin inhibited TGF-β-induced injury in NRK-52E cells, reducing Drp1 expression and IL-6 secretion. Crosstalk experiments confirmed that decreased IL-6 levels were crucial for cordycepin anti-fibrotic effects by suppressing fibroblast activation.Conclusion: Cordycepin ameliorates renal fibrosis by targeting Drp1 to inhibit mitochondrial fission in injured renal tubular epithelial cells, reducing IL-6 secretion and inhibiting fibroblast activation.Keywords: cordycepin, Drp1, renal fibrosis, mitochondrial fission, UIR, IL-
