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  • Zheng, Hao  (9)
  • 2020-2024  (9)
  • 1
    Online Resource
    Online Resource
    Assessment of Building Physical Vulnerability in Earthquake-Debris Flow Disaster Chain
    Springer Science and Business Media LLC ; 2023
    In:  International Journal of Disaster Risk Science Vol. 14, No. 4 ( 2023-08), p. 666-679
    Details
    In: International Journal of Disaster Risk Science, Springer Science and Business Media LLC, Vol. 14, No. 4 ( 2023-08), p. 666-679
    Abstract: Large earthquakes not only directly damage buildings but also trigger debris flows, which cause secondary damage to buildings, forming a more destructive earthquake-debris flow disaster chain. A quantitative assessment of building vulnerability is essential for damage assessment after a disaster and for pre-disaster prevention. Using mechanical analysis based on pushover, a physical vulnerability assessment model of buildings in the earthquake-debris flow disaster chain is proposed to assess the vulnerability of buildings in Beichuan County, China. Based on the specific sequence of events in the earthquake-debris flow disaster chain, the seismic vulnerability of buildings is 79%, the flow impact and burial vulnerabilities of damaged buildings to debris flow are 92% and 28% respectively, and the holistic vulnerability of buildings under the disaster chain is 57%. By comparing different vulnerability assessment methods, we observed that the physical vulnerability of buildings under the disaster chain process is not equal to the statistical summation of the vulnerabilities to independent hazards, which implies that the structural properties and vulnerability of buildings have changed during the disaster chain process. Our results provide an integrated explanation of building vulnerability, which is essential for understanding building vulnerability in earthquake-debris flow disaster chain and building vulnerability under other disaster chains.
    Type of Medium: Online Resource
    ISSN: 2095-0055 , 2192-6395
    URL: Article
    DOI: 10.1007/s13753-023-00509-7
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2633158-5
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  • 2
    Online Resource
    Online Resource
    Evaluating seismic risk in small and medium-sized cities with the modified vulnerability index method, a case study in Jiangyou City, China
    Springer Science and Business Media LLC ; 2020
    In:  Bulletin of Earthquake Engineering Vol. 18, No. 4 ( 2020-03), p. 1303-1319
    Details
    In: Bulletin of Earthquake Engineering, Springer Science and Business Media LLC, Vol. 18, No. 4 ( 2020-03), p. 1303-1319
    Type of Medium: Online Resource
    ISSN: 1570-761X , 1573-1456
    URL: Article
    DOI: 10.1007/s10518-019-00757-3
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2098452-2
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  • 3
    Online Resource
    Online Resource
    An Addition of U0126 Protecting Heart Grafts From Prolonged Cold Ischemia-Reperfusion Injury in Heart Transplantation: A New Preservation Strategy
    Ovid Technologies (Wolters Kluwer Health) ; 2021
    In:  Transplantation Vol. 105, No. 2 ( 2021-02), p. 308-317
    Details
    In: Transplantation, Ovid Technologies (Wolters Kluwer Health), Vol. 105, No. 2 ( 2021-02), p. 308-317
    Abstract: Ischemia-reperfusion injury (IRI) is the major cause of primary graft dysfunction in organ transplantation. The mitogen-activated protein kinase/extracellular signal-regulated kinase (ERK) signaling pathway plays a crucial role in cell physiological and pathological processes including IRI. This study aims to investigate whether inhibition of ERK signaling with U0126 can prevent prolonged cold IRI in heart transplantation. Methods. Rat cardiac cell line H9c2 cells were treated with U0126 before exposure to hypothermic hypoxia/reoxygenation (H/R) conditions. The effect of U0126 on H9c2 cells in response to H/R stress was determined by measuring cell death, reactive oxygen species production, mitochondrial membrane potential, and ERK signaling activation. Mouse syngeneic heterotopic heart transplantation was conducted, where a donor heart was preserved in the University of Wisconsin (UW) solution supplemented with U0126 for 24 hours at 4°C before transplantation. Heart graft function, histopathologic changes, apoptosis, and fibrosis were measured to assess IRI. Results. Phosphorylated ERK was increased in both in vitro H/R-injured H9c2 cells and in vivo heart grafts with IRI. Pretreatment with U0126 inhibited ERK phosphorylation and prevented H9c2 cells from cell death, reactive oxygen species generation, and mitochondrial membrane potential loss in response to H/R. Preservation of donor hearts with U0126-supplemented solution improved graft function and reduced IRI by reductions in cell apoptosis/death, neutrophil infiltration, and fibrosis of the graft. Conclusions. Addition of U0126 to UW solution reduces ERK signal activation and attenuates prolonged cold IRI in a heart transplantation model. ERK inhibition with U0126 may be a useful strategy to minimize IRI in organ transplantation.
    Type of Medium: Online Resource
    ISSN: 0041-1337
    URL: Article
    DOI: 10.1097/TP.0000000000003402
    RVK:
    XA 10000
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2021
    detail.hit.zdb_id: 2035395-9
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  • 4
    Online Resource
    Online Resource
    DataSheet1.PDF
    Frontiers Media SA ; 2023
    In:  Frontiers in Earth Science Vol. 10 ( 2023-1-18)
    Details
    In: Frontiers in Earth Science, Frontiers Media SA, Vol. 10 ( 2023-1-18)
    Abstract: Global warming is inducing dramatic changes in fluvial geomorphology and reshaping the hydrological connections between rivers and lakes. The water level and area of the Salt Lake have increased rapidly since the outburst of the Zonag Lake in the Hoh Xil region of the Qinghai–Tibet Plateau in 2011, threatening the downstream infrastructure. However, fewer studies have focused on its spatiotemporal variation and overflow risk over long time series. Here, we used three machine learning algorithms: Classification and Regression Trees (CART), Random Forest (RF), and Support Vector Machine (SVM) to extract the area of the Salt Lake for a long time series, analyzed its spatiotemporal variation from 1973 to 2021, and finally assessed the overflow risk. The Kappa coefficient (KAPPA) and the overall accuracy (OA) were used to evaluate the performance of the models. The results showed that Random Forest performs superior in lake extraction (KAPPA = 0.98, overall accuracy = 0.99), followed by Classification and Regression Trees and Support Vector Machine. normalized difference water index is the relatively important feature variable in both RF and CART. Before the outburst event, the area change of the Salt Lake was consistent with the variation in precipitation; after that, it showed a remarkable area increase (circa 350%) in all orientations, and the main direction was the southeast. Without the construction of the emergency drainage channel, the simulation result indicated that the earliest and latest times of the Salt Lake overflow event are predicted to occur in 2020 and 2031, respectively. The results of this paper not only demonstrate that RF is more suitable for water extraction and help understand the water system reorganization event.
    Type of Medium: Online Resource
    ISSN: 2296-6463
    URL: Article
    URL: Article
    DOI: 10.3389/feart.2022.1084540
    DOI: 10.3389/feart.2022.1084540.s001
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2023
    detail.hit.zdb_id: 2741235-0
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  • 5
    Online Resource
    Online Resource
    Flood Risk Assessment Based on Fuzzy Synthetic Evaluation Method in the Beijing-Tianjin-Hebei Metropolitan Area, China
    MDPI AG ; 2020
    In:  Sustainability Vol. 12, No. 4 ( 2020-02-15), p. 1451-
    Details
    In: Sustainability, MDPI AG, Vol. 12, No. 4 ( 2020-02-15), p. 1451-
    Abstract: Flooding is one of the most devastating natural events and leads to enormous and recurring loss of life, properties, and resources around the globe. With climate change and accelerating urbanization, flood disasters in China have increasingly affected the sustainable development of metropolitan areas. Risk assessment is an essential step in flood management and disaster mitigation, which provide a quantitative measure of flood risk. However, the difficulty of flood risk zoning is dealing with the uncertainty of the evaluation process and the complicated non-linear relationship between indicators and risk levels. To address this issue, a fuzzy synthetic evaluation (FSE) method based on combined weight (CW) was utilized in this paper to generate flood risk maps at a grid-scale (1 × 1 km). For the case study in the Beijing-Tianjin-Hebei metropolitan area (BTH) in China, fourteen indicators were selected to construct the flood risk assessment model based on the FSE approach integrated with ArcGIS. The research demonstrates that moderate, high, and very high risk zones are distributed in the southeast fluvial plain of the BTH area, accounting for 31.36% of the total land area. Meanwhile, low and very-low risk zones occupy 68.64% of the total land area, and are primarily located in the high plateau and mountain regions in the northwest. We analyzed the risk level of each county and proposed risk mitigation measures based on field investigations. The verified risk assessment results were spatially consistent with the historical flood disaster records and loss positions, indicating the accuracy and reliability of the risk assessment map using the FSE approach. Compared with the IPCC (Intergovernmental Panel on Climate Change) TAR (Third Assessment Report) and AR5 (Fifth Assessment Report) methods, FSE has significant advantages in handling uncertainty, complexity, and the non-linear relationship between indices and risk grades. This study provides a novel quantitative method for flood risk assessment in metropolitan areas and practical implications for urban flood management.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su12041451
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2518383-7
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  • 6
    Online Resource
    Online Resource
    The Changes of Desertification and Its Driving Factors in the Gonghe Basin of North China over the Past 10 Years
    MDPI AG ; 2023
    In:  Land Vol. 12, No. 5 ( 2023-05-01), p. 998-
    Details
    In: Land, MDPI AG, Vol. 12, No. 5 ( 2023-05-01), p. 998-
    Abstract: Desertification is one of the most severe environmental and socioeconomic issues facing the world today. Gonghe Basin is located in the monsoon marginal zone of China, is a sensitive area of climate change in the northeastern of the Qinghai-Tibet Plateau in China, desertification issue has become very severe. Remote sensing monitoring provides an effective technical means for desertification control. In this study, we used Landsat images in 2010 and 2020 to extract desertification information to constructed the Albedo-NDVI feature space in the Gonghe Basin. And then analyzed temporal and spatial evolution of desertification and its driving factors using Geodetector in the Gonghe Basin from 2010 to 2020. The main conclusions are as follows: (1) Albedo-NDVI feature space method can accurately classify desertification information with accuracy of more than 90%, which was benefit to quantitative analysis of desertification. (2) The desertification situation in the Gonghe Basin had improved from 2010 to 2020, especially in the west of the basin, desertification land area decreased by 827.46 km2, and desertification intensity had been obviously reversed. (3) The changes of the desertification in the Gonghe Basin from 2010 to 2020 was affected by both natural and human factors, and the influence of human activities on desertification reversal had increased gradually. The results indicate that the desertification status in the Gonghe Basin had been effectively controlled, and can provide useful basis for the desertification combat in the Gonghe Basin.
    Type of Medium: Online Resource
    ISSN: 2073-445X
    URL: Article
    DOI: 10.3390/land12050998
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2682955-1
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  • 7
    Online Resource
    Online Resource
    Thermokarst lake susceptibility assessment using machine learning models in permafrost landscapes of the Arctic
    Elsevier BV ; 2023
    In:  Science of The Total Environment Vol. 900 ( 2023-11), p. 165709-
    Details
    In: Science of The Total Environment, Elsevier BV, Vol. 900 ( 2023-11), p. 165709-
    Type of Medium: Online Resource
    ISSN: 0048-9697
    URL: Article
    DOI: 10.1016/j.scitotenv.2023.165709
    RVK:
    AR 10100
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 1498726-0
    detail.hit.zdb_id: 121506-1
    SSG: 12
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  • 8
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    Online Resource
    Locomotion of Slope Geohazards Responding to Climate Change in the Qinghai-Tibetan Plateau and Its Adjacent Regions
    MDPI AG ; 2021
    In:  Sustainability Vol. 13, No. 19 ( 2021-09-22), p. 10488-
    Details
    In: Sustainability, MDPI AG, Vol. 13, No. 19 ( 2021-09-22), p. 10488-
    Abstract: Slope geohazards, which cause significant social, economic and environmental losses, have been increasing worldwide over the last few decades. Climate change-induced higher temperatures and shifted precipitation patterns enhance the slope geohazard risks. This study traced the spatial transference of slope geohazards in the Qinghai-Tibet Plateau (QTP) and investigated the potential climatic factors. The results show that 93% of slope geohazards occurred in seasonally frozen regions, 2.6% of which were located in permafrost regions, with an average altitude of 3818 m. The slope geohazards are mainly concentrated at 1493–1988 m. Over time, the altitude of the slope geohazards was gradually increased, and the mean altitude tended to spread from 1984 m to 2562 m by 2009, while the slope gradient varied only slightly. The number of slope geohazards increased with time and was most obvious in spring, especially in the areas above an altitude of 3000 m. The increase in temperature and precipitation in spring may be an important reason for this phenomenon, because the results suggest that the rate of air warming and precipitation at geohazard sites increased gradually. Based on the observation of the spatial location, altitude and temperature growth rate of slope geohazards, it is noted that new geohazard clusters (NGCs) appear in the study area, and there is still a possibility of migration under the future climate conditions. Based on future climate forecast data, we estimate that the low-, moderate- and high-sensitivity areas of the QTP will be mainly south of 30° N in 2030, will extend to the south of 33° N in 2060 and will continue to expand to the south of 35° N in 2099; we also estimate that the proportion of high-sensitivity areas will increase from 10.93% in 2030 to 14.17% in 2060 and 17.48% in 2099.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su131910488
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2518383-7
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  • 9
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    Online Resource
    Thermokarst Lake Susceptibility Assessment Induced by Permafrost Degradation in the Qinghai–Tibet Plateau Using Machine Learning Methods
    MDPI AG ; 2023
    In:  Remote Sensing Vol. 15, No. 13 ( 2023-06-29), p. 3331-
    Details
    In: Remote Sensing, MDPI AG, Vol. 15, No. 13 ( 2023-06-29), p. 3331-
    Abstract: The rapidly warming climate on the Qinghai–Tibet Plateau (QTP) leads to permafrost degradation, and the thawing of ice-rich permafrost induces land subsidence to facilitate the development of thermokarst lakes. Thermokarst lakes exacerbate the instability of permafrost, which significantly alters regional geomorphology and hydrology, affecting biogeochemical cycles. However, the spatial distribution and future changes in thermokarst lakes have rarely been assessed at large scales. In this study, we combined various conditioning factors and an inventory of thermokarst lakes to assess the spatial distribution of susceptibility maps using machine-learning algorithms. The results showed that the extremely randomized trees (EXT) performed the best in the susceptibility modeling process, followed by random forest (RF) and logistic regression (LR). According to the assessment based on EXT, the high- and very high-susceptibility area of the present (2000–2016) susceptibility map was 196,222 km2, covering 19.67% of the permafrost region of the QTP. In the future (the 2070s), the area of the susceptibility map was predicted to shrink significantly under various representative concentration pathway scenarios (RCPs). The susceptibility map area would be reduced to 37.06% of the present area in RCP 8.5. This paper also performed correlation and importance analysis on the conditioning factors and thermokarst lakes, which indicated that thermokarst lakes tended to form in areas with flat topography and high soil moisture. The uncertainty of the susceptibility map was further assessed by the coefficient of variation (CV). Our results demonstrate a way to study the spatial distribution of thermokarst lakes at the QTP scale and provide a scientific basis for understanding thermokarst processes in response to climate change.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    URL: Article
    DOI: 10.3390/rs15133331
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2513863-7
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