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Article: Characterization of the health and irrigation risks and hydrochemical properties of groundwater: a case study of the Selian coal mine area, Ordos, Inner Mongolia

Li, Yaqiang / Zhang, Xueliang

Applied water science. 2022 Oct., v. 12, no. 10

2022

Abstract: Groundwater (GW) is an important source of freshwater in arid and semiarid areas. Some important industrial activities, such as coal mining, also consume GW. There have been few studies evaluating GW quality in the Selian coal mining area of Inner ... ...

Abstract	Groundwater (GW) is an important source of freshwater in arid and semiarid areas. Some important industrial activities, such as coal mining, also consume GW. There have been few studies evaluating GW quality in the Selian coal mining area of Inner Mongolia. This study aimed to identify the hydrochemical phases and the sources of main ions in the GW of the Selian coal mining area. Water quality analysis was performed on 20 shallow GW samples collected from the study area. Statistical correlation analysis was performed on these water quality data. The quality of irrigation water was evaluated based on water quality indices such as the sodium absorption rate and sodium percentage. The risk of nitrate pollution in the study area to human health was evaluated by GW nitrate content. The results show that the dominant GW chemistry types in the study area are the mixed and Ca–HCO₃ types. Correlation analysis indicates that rock weathering and leaching are the main natural drivers of GW hydrochemistry in this area. The irrigation risk analysis shows that GW in this area can be used for irrigation, although some caution is needed. The human health risk assessment shows that GW nitrate pollution poses more risk to children than to adults by a factor of 1.168. It is recommended that centralized treatment of drinking water is the optimal approach to managing this risk. The results of this study can act as a reference for the rational use of GW and for control of nitrate pollution in this area.
Keywords	absorption ; case studies ; coal ; freshwater ; groundwater ; health effects assessments ; human health ; irrigation ; irrigation water ; nitrates ; pollution ; risk ; risk analysis ; sodium ; water quality ; water quality analysis ; China
Language	English
Dates of publication	2022-10
Size	p. 236.
Publishing place	Springer International Publishing
Document type	Article
ZDB-ID	2594789-8
ISSN	2190-5495 ; 2190-5487
ISSN (online)	2190-5495
ISSN	2190-5487
DOI	10.1007/s13201-022-01762-9
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Global and regional epidemiology of psoriatic arthritis in patients with psoriasis: A comprehensive systematic analysis and modelling study.

Kang, Zijian / Zhang, Xueliang / Du, Yu / Dai, Sheng-Ming

Journal of autoimmunity

2024 Volume 145, Page(s) 103202

Abstract: Objectives: To provide a comprehensive analysis and modelling of the global epidemiology of psoriatic arthritis (PsA) in patients with psoriasis.: Methods: We reviewed and analysed PsA epidemiology studies over the past 45 years. A Bayesian ... ...

Abstract	Objectives: To provide a comprehensive analysis and modelling of the global epidemiology of psoriatic arthritis (PsA) in patients with psoriasis. Methods: We reviewed and analysed PsA epidemiology studies over the past 45 years. A Bayesian hierarchical linear mixed model was developed to provide comprehensive age- and sex-specific epidemiologic estimates in different countries and regions. Results: Three hundred and sixty-three studies were systematically reviewed. The incidence of PsA in patients with psoriasis varied from 2.31 per 1000 person-years in the United Kingdom to 74.00 per 1000 person-years in several Western European countries. The global prevalence of PsA in patients with psoriasis is estimated to be 17.58% (3.33%, 43.69%). Regionally, the overall prevalence of PsA in patients with psoriasis varies from 7.62% (4.18%, 12.28%) in Australasia to 26.59% (18.89%, 35.76%) in North America. The Caribbean and Central Latin America also have relatively high prevalence and are estimated at 23.14% (14.06%, 35.17%) and 22.81% (14.36%, 32.25%), respectively. The prevalence of PsA is higher in adults than children (23.93% vs 8.59%) and also slightly higher in females than males (19.14% vs 16.01%). Conclusions: This study provides valuable insights into the global epidemiology of PsA. It also serves as a useful resource for researchers in areas lacking relevant studies. These findings have important implications for clinicians managing the course of PsA and for health policymakers in resource allocation.
MeSH term(s)	Humans ; Arthritis, Psoriatic/epidemiology ; Prevalence ; Psoriasis/epidemiology ; Incidence ; Male ; Female ; Global Health ; Bayes Theorem
Language	English
Publishing date	2024-03-16
Publishing country	England
Document type	Journal Article ; Meta-Analysis ; Review
ZDB-ID	639452-8
ISSN	1095-9157 ; 0896-8411
ISSN (online)	1095-9157
ISSN	0896-8411
DOI	10.1016/j.jaut.2024.103202
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Article ; Online: Perturbed peer model with joint confidence for semi-supervised object-based classification in urban area

Wang, Wenye / Zhang, Xueliang / Xiao, Pengfeng / Su, Qi

International Journal of Remote Sensing. 2023 July 18, v. 44, no. 14 p.4417-4440

2023

Abstract: The application of deep learning (DL) improves the accuracy of object-based classification in urban area, but the huge numbers of labelled samples required for training DL models are difficult to obtain. To address that, we propose a novel semi- ... ...

Abstract	The application of deep learning (DL) improves the accuracy of object-based classification in urban area, but the huge numbers of labelled samples required for training DL models are difficult to obtain. To address that, we propose a novel semi-supervised object-based classification method that combines pseudo-labelling method and consistency regularization method, named as perturbed peer model (PPM). To evaluate the quality of unlabelled object samples, a new object-level joint confidence is designed to assess the confidence of the samples’ prediction, which provides guidance for selecting unlabelled object samples in semi-supervised object-based classification. Instead of only using the high-confidence samples as usual, both the high-confidence samples with discriminative power and the low-confidence samples with a large range of structural features are exploited using pseudo-labelling method and consistency regularization method, respectively, facilitating the fusion of the two methods in the proposed PPM. In addition, two types of perturbations, dropout and difference augmentation, are integrated into the model to drive the consistency regularization method as well as to enhance the difference to facilitate the pseudo-labelling method. Experimental results show that the classification accuracy of PPM is better than the widely-used self-training, co-training, noisy-student, unsupervised data augmentation for consistency training, and FreeMatch methods in urban area.
Keywords	models ; prediction ; urban areas ; Object-based classification ; semi-supervised learning ; convolutional neural networks ; high-spatial resolution remote sensing ; urban area
Language	English
Dates of publication	2023-0718
Size	p. 4417-4440.
Publishing place	Taylor & Francis
Document type	Article ; Online
ZDB-ID	1497529-4
ISSN	1366-5901 ; 0143-1161
ISSN (online)	1366-5901
ISSN	0143-1161
DOI	10.1080/01431161.2023.2235643
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Article: Comment on "Refracture risk and all-cause mortality after vertebral fragility fractures: Anti-osteoporotic medications matter".

Qu, Peng / Hao, Hongyan / Zhang, Xueliang

Journal of the Formosan Medical Association = Taiwan yi zhi

2023 Volume 122 Suppl 1, Page(s) S101–S102

Language	English
Publishing date	2023-07-18
Publishing country	Singapore
Document type	Letter
ZDB-ID	2096659-3
ISSN	1876-0821 ; 0929-6646
ISSN (online)	1876-0821
ISSN	0929-6646
DOI	10.1016/j.jfma.2023.07.008
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Article ; Online: Wound microenvironment regulatory poly(L-glutamic acid) composite hydrogels containing metal ion-coordinated nanoparticles for effective hemostasis and wound healing.

Chen, Yanzheng / Zhang, Xueliang / Wang, Qing / Du, Chang / Dong, Chang-Ming

Biomaterials science

2024 Volume 12, Issue 5, Page(s) 1211–1227

Abstract: Regulating the wound microenvironment to promote proliferation, vascularization, and wound healing is challenging for hemostats and wound dressings. Herein, polypeptide composite hydrogels have been simply fabricated by mixing a smaller amount of metal ... ...

Abstract	Regulating the wound microenvironment to promote proliferation, vascularization, and wound healing is challenging for hemostats and wound dressings. Herein, polypeptide composite hydrogels have been simply fabricated by mixing a smaller amount of metal ion-coordinated nanoparticles into dopamine-modified poly(L-glutamic acid) (PGA), which had a microporous size of 10-16 μm, photothermal conversion ability, good biocompatibility, and multiple biological activities.
MeSH term(s)	Rats ; Animals ; Glutamic Acid/pharmacology ; Hydrogels/pharmacology ; Wound Healing ; Hemostasis ; Peptides/pharmacology ; Nanoparticles ; Anti-Bacterial Agents/pharmacology
Chemical Substances	Glutamic Acid (3KX376GY7L) ; Hydrogels ; Peptides ; Anti-Bacterial Agents
Language	English
Publishing date	2024-02-27
Publishing country	England
Document type	Journal Article
ZDB-ID	2693928-9
ISSN	2047-4849 ; 2047-4830
ISSN (online)	2047-4849
ISSN	2047-4830
DOI	10.1039/d3bm01978k
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Article ; Online: Prognostic significance of natural killer cell depletion in predicting progressive fibrosing interstitial lung disease in idiopathic inflammatory myopathies.

Shao, Chenyi / Xia, Nana / Zhen, Yan / Zhang, Xueliang / Yan, Ninghui / Guo, Qiang

Frontiers in immunology

2024 Volume 15, Page(s) 1404828

Abstract: Objectives: Interstitial lung disease (ILD) is one of the common extramuscular involvement in idiopathic inflammatory myopathies (IIMs) (1). Several patients develop a progressive fibrosing ILD (PF-ILD) despite conventional treatment, resulting in a ... ...

Abstract	Objectives: Interstitial lung disease (ILD) is one of the common extramuscular involvement in idiopathic inflammatory myopathies (IIMs) (1). Several patients develop a progressive fibrosing ILD (PF-ILD) despite conventional treatment, resulting in a progressive deterioration in their quality of life (2). Here, we investigated the clinical and immune characteristics of IIM-ILD and risk factors for PF-ILD in IIM, mainly in anti-melanoma differentiation-associated protein 5 (anti-MDA5 Methods: Here, a prospective cohort of 156 patients with IIM-ILD were included in the longitudinal analysis and divided into the PF-ILD (n=65) and non-PF-ILD (n=91) groups, and their baseline clinical characteristics were compared. Univariate and multivariate Cox analyses were performed to identify the variables significantly associated with pulmonary fibrosis progression in the total cohort, then anti-MDA5 Results: Peripheral blood lymphocyte counts, including T, B, and NK cell counts, were significantly lower in the PF-ILD group than in the non-PF-ILD group. This characteristic is also present in the comparison between patients with anti-MDA5 Conclusions: Patients with anti-MDA5
MeSH term(s)	Humans ; Female ; Male ; Middle Aged ; Lung Diseases, Interstitial/immunology ; Lung Diseases, Interstitial/diagnosis ; Lung Diseases, Interstitial/etiology ; Killer Cells, Natural/immunology ; Myositis/immunology ; Myositis/blood ; Myositis/diagnosis ; Prognosis ; Disease Progression ; Aged ; Prospective Studies ; Adult ; Lymphocyte Depletion ; Interferon-Induced Helicase, IFIH1/immunology ; Risk Factors ; Pulmonary Fibrosis/etiology ; Pulmonary Fibrosis/immunology ; Lymphocyte Count ; Longitudinal Studies
Language	English
Publishing date	2024-04-30
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606827-8
ISSN	1664-3224 ; 1664-3224
ISSN (online)	1664-3224
ISSN	1664-3224
DOI	10.3389/fimmu.2024.1404828
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Article: Evaluating the different responses to climatic factors between snow water equivalent and snow cover area in the Central Tianshan Mountains

Wu, Senyao / Zhang, Xueliang / Du, Jinkang / Wang, Huadong

Theoretical and applied climatology. 2022 May, v. 148, no. 3-4

2022

Abstract: Alpine snow is an important part of the water cycle in arid/semiarid regions and has a great influence on runoff and ecosystems. In this study, both optical and passive microwave remote sensing data were used to characterize the vertical distribution of ... ...

Abstract	Alpine snow is an important part of the water cycle in arid/semiarid regions and has a great influence on runoff and ecosystems. In this study, both optical and passive microwave remote sensing data were used to characterize the vertical distribution of snow cover area (SCA) and snow water equivalent (SWE) on the north slope of Central Tianshan Mountain, northwest China, focusing on exploring the different spatial–temporal characteristics between SCA and SWE, as well as their different responses to climatic factors at different altitudes. The results show that (1) the SCA and SWE have similar vertical distribution characteristics but show different changing rates and changing directions over time at different altitudes. (2) In the snow accumulation period and snowmelt period, the correlation relationships between precipitation/temperature and SCA are the same (positive or negative) as those between precipitation/temperature and SWE at low-middle altitudes but opposite at high altitudes. (3) The influence of precipitation/temperature on SWE has a linear relationship with altitude but not with SCA. (4) The relative importance of precipitation/temperature for SCA is the same as that for SWE at different altitudes. The results illustrated the different vertical responses to climatic factors between SCA and SWE, which could be beneficial to predicting the changes in mountain snow under the climate change scenario.
Keywords	altitude ; climate change ; climatology ; hydrologic cycle ; runoff ; snow ; snowmelt ; snowpack ; spatial distribution ; temperature ; topographic slope ; China
Language	English
Dates of publication	2022-05
Size	p. 1563-1576.
Publishing place	Springer Vienna
Document type	Article
ZDB-ID	1463177-5
ISSN	1434-4483 ; 0177-798X
ISSN (online)	1434-4483
ISSN	0177-798X
DOI	10.1007/s00704-022-04009-4
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Article: Spectral index-driven FCN model training for water extraction from multispectral imagery

Li, Zhenshi / Zhang, Xueliang / Xiao, Pengfeng

ISPRS journal of photogrammetry and remote sensing. 2022 Aug. 19,

2022

Abstract: Terrestrial water is a fundamental component of the land surface. Accurate and robust water delineation of surface water is rather challenging due to the high intra-class variability and the spectral similarity with shadows and other dark surfaces. This ... ...

Abstract	Terrestrial water is a fundamental component of the land surface. Accurate and robust water delineation of surface water is rather challenging due to the high intra-class variability and the spectral similarity with shadows and other dark surfaces. This study proposes a new method called the water index-driven deep fully convolutional neural network (WIDFCN) for high-accuracy water delineation with no need to collect samples manually. We formulate water delineation as a semantic labeling problem and solve it by training a deep fully convolutional network (FCN), whose capability of effectively extracting multilevel spatial and spectral features is exploited for discriminating water from complex surroundings. The main obstacle of using FCN, which requires a large volume of labeled training samples, is settled by utilizing the water recognition ability of the water spectral index (WI). Specifically, the training samples are automatically generated from WI by extracting a high-precision but incomplete water mask at first, which is then expanded to enhance the completeness. This strategy ensures the high quality of the automatically generated training samples and thus the water extraction performance of the trained FCN model. Twelve test sites from Sentinel-2 imagery with various water delineation challenges all over the world are used to assess the performance relative to that of supervised and unsupervised classification methods and water spectral index thresholding methods, in terms of Kappa coefficient, precision, recall, and F1-score. Overall, WIDFCN can achieve the highest precision and comparable recall, leading to the best water delineation accuracy with Kappa coefficient 0.9673 and F1-score 0.9696, as well as the lowest fluctuation in terms of various test sites. The results further demonstrate that WIDFCN can effectively deal with the scale and spectra variance of surface water, and has distinct robustness with respect to different kinds of shadows, including building, mountain, and cloud shadows. The findings in this study demonstrate a novel, robust, low-cost, and manual labor-free water delineation method that performs well in terms of both precision and completeness. Moreover, the core idea could provide a reference for extraction of geographic information by utilizing FCN models with no needs of manually labeling costs. Code and data will be available at https://github.com/LZhenShi/WIDFCN.
Keywords	multispectral imagery ; neural networks ; photogrammetry ; spatial data ; surface water ; variance
Language	English
Dates of publication	2022-0819
Publishing place	Elsevier B.V.
Document type	Article
Note	Pre-press version
ZDB-ID	1007774-1
ISSN	0924-2716
ISSN	0924-2716
DOI	10.1016/j.isprsjprs.2022.08.019
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Article: Comparison of the shallow groundwater storage change estimated by a distributed hydrological model and GRACE satellite gravimetry in a well-irrigated plain of the Haihe River basin, China

Zhang, Xueliang / Ren, Li / Feng, Wei

Journal of hydrology. 2022 July, v. 610

2022

Abstract: Groundwater is a key component of the global hydrological cycle. Quantitative approaches to estimate the spatial and temporal changes in groundwater storage (GWS) could provide solid foundation for sustainable management. This study made a comprehensive ... ...

Abstract	Groundwater is a key component of the global hydrological cycle. Quantitative approaches to estimate the spatial and temporal changes in groundwater storage (GWS) could provide solid foundation for sustainable management. This study made a comprehensive comparison of GWS changes based on two independent approaches: the Soil and Water Assessment Tool (SWAT) hydrological model and Gravity Recovery and Climate Experiment (GRACE) satellite mission data. The feasibility of using these two estimation methods to quantify shallow groundwater variations in the Haihe River basin of China, a globally representative overexploited area, was assessed. The GRACE-derived GWS changes were calculated based on independent component analysis and a joint inversion method. The results showed that the GRACE-estimated shallow GWS anomalies during 2003–2012 agree well with the SWAT-simulated data. For the variations in the long-term GWS depletion rate, we found that heterogeneity at 22 subbasin (approximately 500 to 1500 km²) scales was detected by the GRACE data, and these results were spatially coherent with the SWAT simulations based on the distributed modeling units and multiple inputs. The GRACE estimates could adequately replicate the general trends of GWS depletion in the winter wheat (Triticum aestivum L.) growth period and recovery in the summer maize (Zea mays L.) growth period. Specifically, comparisons between GRACE-based and SWAT-simulated results indicated that the signals of pumping for winter wheat irrigation in several key water requirement periods in April, May and November were identified by GRACE, as were seasonal changes in shallow GWS (e.g., an obvious depletion in spring). Despite an overestimation of the scope of the fluctuations in GRACE estimates compared with those of SWAT simulations from the perspective of the water flux, the effective identification of the impact of anthropogenic exploitation on shallow GWS in GRACE suggests that this monitoring tool could be applied in the groundwater management of this plain. This study demonstrated a good agreement between SWAT-simulated and GRACE-based shallow GWS changes from the perspectives of long-term trends and variations in crop seasons. Additionally, satisfactory consistency was observed from the perspective of the water flux in this semiarid and semihumid study region considering the influence of human activities.
Keywords	Soil and Water Assessment Tool model ; Triticum aestivum ; Zea mays ; climate ; gravimetry ; groundwater ; humans ; hydrologic cycle ; independent component analysis ; irrigation ; satellites ; spring ; water management ; water requirement ; watersheds ; winter wheat ; China
Language	English
Dates of publication	2022-07
Publishing place	Elsevier B.V.
Document type	Article
ZDB-ID	1473173-3
ISSN	1879-2707 ; 0022-1694
ISSN (online)	1879-2707
ISSN	0022-1694
DOI	10.1016/j.jhydrol.2022.127799
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Article: DEM-FEM based numerical analysis on mechanical responses of sandy soil and pipeline to seepage erosion

Zhang, Dongmei / Zhang, Xueliang / Du, Weiwei

Engineering geology. 2022 Sept. 22,

2022

Abstract: Seepage erosion around the underground pipelines will produce various adverse influences on the stratum stability and the structural safety. It involves behaviours at three scales, that is, particle-scale, cell-scale and engineering-scale. The problem ... ...

Abstract	Seepage erosion around the underground pipelines will produce various adverse influences on the stratum stability and the structural safety. It involves behaviours at three scales, that is, particle-scale, cell-scale and engineering-scale. The problem relies on the fact that finding general equations for the granular media is difficult due to the changing nature of how solids flow, so that the continuous approach is unavailable to directly describe the phenomenon. Hence, DEM simulations are firstly conducted in this study to quantify the relationship between the fine particle loss (ΔFC = 0, 5%, 10%, 15%, 20%, 25%, 30%) and the mechanical properties of soil elements, upscaling particle to cell. Considering two initial fine grain contents (S6:4, S3:7), the empirical equations of soil mechanical parameters εᵥₑ, E₀, φ and c changing with the fine particle loss ΔFC are obtained by regression analysis. Then, based on the corresponding constitutive parameters of different erosional stages, FEM simulations at the engineering scale are conducted to analyse the structural mechanical response to the seepage erosion, upscaling cell to engineering. This study reveals the multiscale response of the seepage erosion in the sandy strata, and helps in providing the practical guidance for engineering application and the reference for the next multiscale parallel computation on this issue.
Keywords	regression analysis ; sandy soils ; seepage
Language	English
Dates of publication	2022-0922
Publishing place	Elsevier B.V.
Document type	Article
Note	Pre-press version
ISSN	0013-7952
DOI	10.1016/j.enggeo.2022.106868
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