Two new dinosaur tracksites from the Jurassic Guizhou Province, China

2022 ◽  
pp. 1-9
Author(s):  
Lida Xing ◽  
Martin G. Lockley ◽  
Chen Li ◽  
Hendrik Klein ◽  
Jinwang Li ◽  
...  
Keyword(s):  
2016 ◽  
Vol 42 (12) ◽  
pp. 1817
Author(s):  
De-Qiang LUO ◽  
Shao-Hua WANG ◽  
Xue-Hai JIANG ◽  
Gang-Hua LI ◽  
Wei-Jia ZHOU ◽  
...  

2013 ◽  
Vol 38 (8) ◽  
pp. 1387-1396
Author(s):  
Mao LIN ◽  
Zheng-Qiang LI ◽  
Zhi-Hong ZHENG ◽  
Jian-Wei LÜ ◽  
Tian-Jin MA ◽  
...  

2020 ◽  
Author(s):  
Yushi Mo ◽  
Yan Luo ◽  
Hong Li ◽  
Dewei Xiao ◽  
Shuqing Liu ◽  
...  

BACKGROUND In face of the sudden epidemic of COVID-19, strict prevention and control measures had been urgently carried out all over China. Because of the long-term home quarantine, all kinds of people were affected by it. OBJECTIVE In order to understand the mental health of children during the pandemic of COVID-19, this study investigated the prevalence and characteristics of emotional and behavioral problems of children aged 1-11 in Guizhou. METHODS Based on the online survey platform, the survey link was pushed through Wechat in April 2020. Electronic questionnaires were used to investigate children's demographic characteristics, emotional or behavioral problems. RESULTS A total of 3505 valid questionnaires were received from 9 prefectures and cities in Guizhou Province. 39.67% of the children in the 1-2-year-old group had emotional problems. 17.63% of the children agd 3-5 years had behavioral or emotional problems. And 23.57% of the children agd 6-11 years havd behavioral problems. CONCLUSIONS During the home quarantine period of prevention and control of COVID-19, even young children were adversely affected. The prevalence of emotional and behavioral problems in children was high, which was mainly manifested as anxiety, difficulty in concentration and sleep problems.


Zootaxa ◽  
2019 ◽  
Vol 4658 (1) ◽  
pp. 183-188
Author(s):  
DAXING YANG ◽  
GUCHUN ZHOU ◽  
MAOFA YANG ◽  
XIANJIN PENG

Clubiona Latreille, 1804 comprises 503 species across the world, of which 122 species were reported from China. Nearly one-third of Chinese species have been described with single-sex (World Spider Catalog, 2018). Twenty-eight species have been reported from Guizhou Province (Wang et al. 2015; Wu et al. 2015; Li & Lin 2016; Yu et al. 2017; Wang et al. 2018; Zhang et al. 2018).


2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Jane-Heloise Nancarrow ◽  
Chen Yang ◽  
Jing Yang

AbstractThe application of digital technologies has greatly improved the efficiency of cultural heritage documentation and the diversity of heritage information. Yet the adequate incorporation of cultural, intangible, sensory or experimental elements of local heritage in the process of digital documentation, and the deepening of local community engagement, remain important issues in cultural heritage research. This paper examines the heritage landscape of tunpu people within the context of digital conservation efforts in China and the emergence of emotions studies as an evaluative tool. Using a range of data from the Ming-era village of Baojiatun in Guizhou Province, this paper tests an exploratory emotions-based approach and methodology, revealing shifting interpersonal relationships, experiential and praxiological engagement with the landscape, and emotional registers within tunpu culture and heritage management. The analysis articulates distinctive asset of emotional value at various scales and suggests that such approaches, applied within digital documentation contexts, can help researchers to identify multi-level heritage landscape values and their carriers. This methodology can provide more complete and dynamic inventories to guide digital survey and representation; and the emotions-based approach also supports the integration of disparate heritage aspects in a holistic understanding of the living landscape. Finally, the incorporation of community participation in the process of digital survey breaks down boundaries between experts and communities and leads to more culturally appropriate heritage records and representations.


2021 ◽  
Vol 13 (3) ◽  
pp. 441
Author(s):  
Han Fu ◽  
Bihong Fu ◽  
Pilong Shi

The South China Karst, a United Nations Educational, Scientific and Cultural Organization (UNESCO) natural heritage site, is one of the world’s most spectacular examples of humid tropical to subtropical karst landscapes. The Libo cone karst in the southern Guizhou Province is considered as the world reference site for these types of karst, forming a distinctive and beautiful landscape. Geomorphic information and spatial distribution of cone karst is essential for conservation and management for Libo heritage site. In this study, a deep learning (DL) method based on DeepLab V3+ network was proposed to document the cone karst landscape in Libo by multi-source data, including optical remote sensing images and digital elevation model (DEM) data. The training samples were generated by using Landsat remote sensing images and their combination with satellite derived DEM data. Each group of training dataset contains 898 samples. The input module of DeepLab V3+ network was improved to accept four-channel input data, i.e., combination of Landsat RGB images and DEM data. Our results suggest that the mean intersection over union (MIoU) using the four-channel data as training samples by a new DL-based pixel-level image segmentation approach is the highest, which can reach 95.5%. The proposed method can accomplish automatic extraction of cone karst landscape by self-learning of deep neural network, and therefore it can also provide a powerful and automatic tool for documenting other type of geological landscapes worldwide.


2021 ◽  
Vol 13 (9) ◽  
pp. 1614
Author(s):  
Boyi Liang ◽  
Timothy A. Quine ◽  
Hongyan Liu ◽  
Elizabeth L. Cressey ◽  
Ian Bateman

To meet the sustainable development goals in rocky desertified regions like Guizhou Province in China, we should maximize the crop yield with minimal environmental costs. In this study, we first calculated the yield gap for 6 main crop species in Guizhou Province and evaluated the quantitative relationships between crop yield and influencing variables utilizing ensembled artificial neural networks. We also tested the influence of adjusting the quantity of local fertilization and irrigation on crop production in Guizhou Province. Results showed that the total yield of the selected crops had, on average, reached over 72.5% of the theoretical maximum yield. Increasing irrigation tended to be more consistently effective at increasing crop yield than additional fertilization. Conversely, appropriate reduction of fertilization may even benefit crop yield in some regions, simultaneously resulting in significantly higher fertilization efficiency with lower residuals in the environment. The total positive impact of continuous intensification of irrigation and fertilization on most crop species was limited. Therefore, local stakeholders are advised to consider other agricultural management measures to improve crop yield in this region.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Liying Liu

AbstractThis paper presents the assessment of water resource security in the Guizhou karst area, China. A mean impact value and back-propagation (MIV-BP) neural network was used to understand the influencing factors. Thirty-one indices involving five aspects, the water quality subsystem, water quantity subsystem, engineering water shortage subsystem, water resource vulnerability subsystem, and water resource carrying capacity subsystem, were selected to establish an evaluation index of water resource security. In addition, a genetic algorithm and back-propagation (GA-BP) neural network was constructed to assess the water resource security of Guizhou Province from 2001 to 2015. The results show that water resource security in Guizhou was at a moderate warning level from 2001 to 2006 and a critical safety level from 2007 to 2015, except in 2011 when a moderate warning level was reached. For protection and management of water resources in a karst area, the modes of development and utilization of water resources must be thoroughly understood, along with the impact of engineering water shortage. These results are a meaningful contribution to regional ecological restoration and socio-economic development and can promote better practices for future planning.


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