Search

Your search keyword '"Gan, Lin"' showing total 222 results
Start Over Author "Gan, Lin" Publisher wiley
222 results on '"Gan, Lin"'

1. Achieving Sustainable Earth Futures in the Anthropocene by Including Local Communities in Critical Zone Science

Author

Larissa A. Naylor, Jennifer A. J. Dungait, Ying Zheng, Sarah Buckerfield, Sophie M. Green, David M. Oliver, Hongyan Liu, Jian Peng, Chenglong Tu, Gan‐lin Zhang, Xinyu Zhang, Tim A. Quine, Susan Waldron, and Paul D. Hallett

Subjects
Anthropocene, 3rd generation critical zone observatory, social science, sustainable development, local knowledge, critical zone science, Environmental sciences, GE1-350, Ecology, QH540-549.5
Abstract

Abstract Critical Zone Science (CZS) explores the deep evolution of landscapes from the base of the groundwater or the saprolite‐rock interface to the top of vegetation, the zone that supports all terrestrial life. Here we propose a framework for CZS to evolve further as a discipline, building on 1st generation CZOs in natural systems and 2nd generation CZOs in human‐modified systems, to incorporate human behaviour for more holistic understanding in a 3rd generation of CZOs. This concept was tested in the China‐UK CZO programme (2016–2020) that established four CZOs across China on different lithologies. Beyond conventional CZO insights into soil resources, biogeochemical cycling and hydrology across scales, surveys of farmers and local government officials led to insights into human‐environment interactions and key pressures affecting the socio‐economic livelihoods of local farmers. These learnings combined with the CZS data identified knowledge exchange (KE) opportunities to unravel diverse factors within the Land‐Water‐Food Nexus, that could directly improve local livelihoods and environmental conditions, such as reduction in fertilizer use, contributing toward Sustainable Development Goals (SDGs) and environmental policies. Through two‐way local KE, the local cultural context and socio‐economic considerations were more readily apparent alongside the environmental rationale for policy and local action to improve the sustainability of farming practices. Seeking solutions to understand and remediate CZ degradation caused by human‐decision making requires the co‐design of CZS that foregrounds human behavior and the opinions of those living in human modified CZOs. We show how a new transdisciplinary CZO approach for sustainable Earth futures can improve alignment of research with the practical needs of communities in stressed environments and their governments, supporting social‐ecological and planetary health research agendas and improving capacity to achieve SDGs.

Published
2023
Full Text
View/download PDF

2. Improving osteoporosis treatment rates in inpatients admitted with hip fracture: A healthcare improvement initiative in a tertiary referral hospital

Author

Andrew Gan Lin, Nargis Shaheen, Kirtan Ganda, John Cullen, Louise M. Waite, and Markus J. Seibel

Subjects
hip fracture, inpatient protocol, osteoporosis, quality improvement, Geriatrics, RC952-954.6
Abstract

Abstract Objective This healthcare improvement initiative was designed to increase inpatient osteoporosis treatment after hip fracture. Methods A new protocol was developed by Geriatric Medicine and Endocrinology departments at a tertiary care hospital in Sydney. Its aim was to standardize assessment and treatment of osteoporosis in patients admitted with hip fracture. Eligible inpatients would receive intravenous zoledronic acid during their admission. A 6‐month sample of hip fracture patients admitted after the protocol's implementation was compared to a group admitted before. Data collected included demographics, biochemistry, treatment rates, adverse effects, and admission survival. Results There was a considerable increase in osteoporosis treatment after introducing the protocol. Before the protocol's introduction, none of 36 eligible patients received treatment. After the intervention 79% (23 out of 29) of eligible patients were treated. All treated patients had renal function and serum calcium levels checked post‐infusion with no adverse outcomes. Eight patients developed flu‐like symptoms within 24 h of the infusion. There were no instances of arrhythmias, ocular inflammation, or death. The cost per patient treated was AUD $87. Conclusion Adopting a standardized protocol for osteoporosis treatment in patients admitted for hip fracture was effective in improving treatment rates whilst being relatively safe and inexpensive.

Published
2022
Full Text
View/download PDF

5. Dual role of GRHL3 in bladder carcinogenesis depending on histological subtypes

Author

Lammert, Franziska C., primary, Pannhausen, Julia, additional, Noetzel, Erik, additional, Friedland, Florian, additional, Wirtz, Julia, additional, Herfs, Yannick, additional, Leypold, Sophie, additional, Gan, Lin, additional, Weiskirchen, Ralf, additional, Schnitzler, Tician, additional, Knüchel, Ruth, additional, Maurer, Jochen, additional, Jonigk, Danny D., additional, Rose, Michael, additional, and Gaisa, Nadine T., additional

Published
2024
Full Text
View/download PDF

9. A network‐based predictive gene expression signature for recurrence risks in stage II colorectal cancer

Author

Wen‐Jing Yang, Hai‐Bo Wang, Wen‐Da Wang, Peng‐Yu Bai, Hong‐Xia Lu, Chang‐He Sun, Zi‐Shen Liu, Ding‐Kun Guan, Guo‐Wang Yang, and Gan‐Lin Zhang

Subjects
bioinformatics analysis, colorectal cancer, recurrence mechanisms, recurrence risks, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract The current criteria for defining the recurrence risks of stage II colorectal cancer (CRC) are not robust; therefore, we aimed to explore novel gene signatures to predict recurrence risks and to reveal the underlying mechanisms of stage II CRC. First, the gene expression profiles of 124 patients with stage II CRC from The Cancer Genome Atlas (TCGA) database were obtained to screen differentially expressed genes (DEGs). A total of 202 DEGs, including 128 upregulated and 74 downregulated, were identified in the recurrence group (n = 24) compared to the nonrecurrence group (n = 100). Furthermore, the top 5 DEGs (ZNF561, WFS1, SLC2A1, MFI2, and PTGR1) were identified by random forest variable hunting, and four (ZNF561, WFS1, SLC2A1, and PTGR1) were selected to create a four‐gene recurrent model (GRM), with an area under the curve (AUC) of 0.882 according to the receiver operating characteristic curve, and the robust diagnostic effectiveness of the GRM was further validated with another gene expression profiling dataset (GSE12032), with an AUC of 0.943. The diagnostic effectiveness of the GRM regarding recurrence was associated with poor disease‐free survival in all stages of CRC. In addition, gene ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses revealed 18 enriched functions and 6 enriched pathways. Four genes, ABCG2, CACNA1F, CYP19A1, and TF, were identified as hub genes by the protein‐protein interaction network, which further validated that these genes were correlated with a poor pathologic stage and overall survival in all stages of CRC. In conclusion, the GRM can effectively classify stage II CRC into groups of high and low risks of recurrence, thereby making up for the prognostic value of the traditional clinicopathological risk factors defined by the National Comprehensive Cancer Network guidelines. The hub genes may be useful therapeutic targets for recurrence. Thus, the GRM and hub genes could offer clinical value in directing individualized and precision therapeutic regimens for stage II CRC patients.

Published
2020
Full Text
View/download PDF

23. Ultrastable Fe–N–C Fuel Cell Electrocatalysts by Eliminating Non‐Coordinating Nitrogen and Regulating Coordination Structures at High Temperatures

Author

Xia, Dongsheng, primary, Tang, Xuan, additional, Dai, Sheng, additional, Ge, Rile, additional, Rykov, Alexander, additional, Wang, Junhu, additional, Huang, Tzu‐Hsi, additional, Wang, Kuan‐Wen, additional, Wei, Yinping, additional, Zhang, Kai, additional, Li, Jia, additional, Gan, Lin, additional, and Kang, Feiyu, additional

Published
2022
Full Text
View/download PDF

43. Three-Dimensional Mapping of Organic Carbon using Piecewise Depth Functions in the Red Soil Critical Zone Observatory

Author

Xinhua Peng, Jian Tian, Gan-Lin Zhang, Feng Liu, Xiaodong Song, Huayong Wu, Qi Cao, and Shun-Hua Yang

Subjects
Total organic carbon, Topsoil, geography, geography.geographical_feature_category, Mean squared error, Bedrock, Borehole, Soil Science, Soil science, 04 agricultural and veterinary sciences, 010501 environmental sciences, Spatial distribution, 01 natural sciences, 040103 agronomy & agriculture, Piecewise, 0401 agriculture, forestry, and fisheries, Environmental science, Red soil, 0105 earth and related environmental sciences
Abstract

Organic carbon (OC) plays a pivotal role in earth surface systems. However, current three-dimensional (3D) mapping studies usually focus on a soil depth of 1 m rather than the depth to the bedrock. A top-down method using piecewise depth functions was proposed to fit the OC vertical decline patterns in a subtropical catchment in southern China. The vertical variation in OC was greatly affected by the heterogeneous topsoil due to natural processes and anthropogenic disturbances. Thus, topsoil OC maps were produced and utilized as covariates to indicate the OC decline rates and to benefit the 3D OC simulation. A distribution map of the underground critical zone thickness (UCZT) was applied as a lower boundary for the 3D simulation. Six widely used mapping techniques were performed to predict the spatial distribution of topsoil OC and depth function parameters. The overall cross-validation results showed a root mean squared error (RMSE) of 1.7 g kg–¹ and a ratio of performance to deviation (RPD) of 1.82. Given limited boreholes, validation showed that the depth function performed better in the lower part (>1 m) than in the upper part (

Published
2019

44. How compatible are numerical classifications based on whole-profile vis-NIR spectra and the Chinese Soil Taxonomy?

Author

R. Zeng, Gan-Lin Zhang, and David G. Rossiter

Subjects
business.industry, Soil Science, Spectral space, Pattern recognition, Soil classification, 04 agricultural and veterinary sciences, 010501 environmental sciences, 01 natural sciences, Hierarchical clustering, Numerical taxonomy, Distance matrix, Similarity (network science), 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Hierarchical control system, Artificial intelligence, business, 0105 earth and related environmental sciences, USDA soil taxonomy, Mathematics
Abstract

Modern monothetic hierarchical soil classification systems such as the Chinese Soil Taxonomy (CST) are semi‐quantitative and their future development is likely to trend towards a fully quantitative system using the concepts of numerical taxonomy. Previous researchers have calculated the taxonomic distances between individual soils based on soil physiochemical properties, not, however, based on spectra of full soil profiles with different horizons. We hypothesized that numerical taxonomy implemented by cluster analysis of the taxonomic distance matrix based on vis–NIR spectra would accord with some CST Orders assigned by pedologists, and not with others, depending on how closely spectral features represent the diagnostic features used in the classification. Taxonomic distances in spectral space were computed for all pairs of 191 profiles, resulting in a distance matrix on which hierarchical cluster analysis was performed. Different indices were calculated to determine the optimum number of clusters, resulting in four spectral soil classes. These were then compared with CST Orders assigned to the profiles by expert allocation. The numerical classes and CST Orders matched poorly because of the completely different classification philosophies behind numerical taxonomy and the CST, which is based largely on presumed genesis and uses sharp thresholds leading to very similar soils being allocated to different classes. Thus, we consider the numerical classification as information that is complementary to the monothetic hierarchical system. Numerical classification can reveal the taxonomic objective aspects of the relation between the defined classes and can suggest new groupings. HIGHLIGHTS: Taxonomic distances can serve as an objective measure of soil similarity. Soil spectra are a good candidate for numerical classification based on taxonomic distances. The conceptual basis of Chinese Soil Taxonomy (CST) does not match that of taxonomic distance. Numerical classification based on spectra can suggest revisions to the CST.

Published
2019

45. Rapid determination of soil classes in soil profiles using vis–NIR spectroscopy and multiple objectives mixed support vector classification

Author

Wenjun Ji, Shuo Li, Gan-Lin Zhang, Dongyun Xu, Zhengli Shi, Songchao Chen, W. Ma, InfoSol (InfoSol), Institut National de la Recherche Agronomique (INRA), Institute of Agricultural Remote Sensing and Information Technology Application, College of Environmental and Resource Sciences, Zhejiang University, Ministry of Agriculture, Departement of Soil and Environment, Swedish University of Agricultural Sciences (SLU), State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, and Chinese Academy of Sciences [Changchun Branch] (CAS)

Subjects
Calibration (statistics), Soil texture, [SDV]Life Sciences [q-bio], Soil organic matter, Soil Science, Soil classification, Soil science, 04 agricultural and veterinary sciences, 010501 environmental sciences, 15. Life on land, 01 natural sciences, Support vector machine, Unified Soil Classification System, [SDE]Environmental Sciences, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Soil horizon, ComputingMilieux_MISCELLANEOUS, 0105 earth and related environmental sciences, Mathematics, USDA soil taxonomy
Abstract

Visible‐near infrared (vis–NIR) spectroscopy can reveal various soil properties and facilitate soil classification. However, few studies have attempted to classify vertical soil profiles that contain several genetic horizons. Here, we propose the ‘multiple objectives mixed support vector classification’ (MOM–SVC) method to classify soil profiles. A total of 130 soil profiles were collected from genetic horizons in Zhejiang Province, China. After laboratory analysis, soil profiles were classified according to the Chinese Soil Taxonomy system. Vis–NIR spectra were recorded from each genetic horizon of each soil profile and were then pre‐processed. We performed the MOM–SVC method as follows: (i) created a support vector machine (SVM) model (one‐versus‐one approach) using spectral data from all soil horizons in calibration profiles, (ii) applied the SVM model on each horizon of the profile to be predicted, (iii) extracted ‘votes’ from each horizon and mixed (or summarized) them into the votes of each profile to be predicted and (iv) classified each profile by the majority‐voting method. We also investigated whether the additional input of auxiliary soil information (e.g. moist soil colour, soil organic matter and soil texture), which could be measured easily or be well predicted by vis–NIR spectroscopy, could improve the accuracy of soil classification when combined with it. Independent validation results showed that the MOM–SVC method performed better at the soil order level than at the suborder level. Adding auxiliary soil information to the classification model improved the overall accuracy of classification at the soil order level. The proposed MOM–SVC method provides a fast objective diagnostic of soil classes for use in soil surveys and can help to update soil databases when a more objective soil classification system is developed. HIGHLIGHTS: The MOM–SVC method can be used to classify soil profiles objectively with a variety of soil horizons. Stratified random sampling was used to quantify prediction uncertainty in classification MOM–SVC can predict soil orders with greater accuracy than suborders. Adding auxiliary soil information into the classification model improved prediction accuracy.

Published
2018

Catalog

Books, media, physical & digital resources
See catalog results