Xin Liang

ORCID: 0000-0002-7276-5235
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About
Contact & Profiles
Research Areas
  • Landslides and related hazards
  • Dental Radiography and Imaging
  • Adsorption and biosorption for pollutant removal
  • Flood Risk Assessment and Management
  • Dam Engineering and Safety
  • Plant Molecular Biology Research
  • Heavy metals in environment
  • Orthodontics and Dentofacial Orthopedics
  • Biochemical and Molecular Research
  • Medical Imaging and Analysis
  • Medical Image Segmentation Techniques
  • Gene expression and cancer classification
  • Dental Implant Techniques and Outcomes
  • Cryospheric studies and observations
  • Fire effects on ecosystems
  • Plant Gene Expression Analysis
  • Neuroinflammation and Neurodegeneration Mechanisms
  • Plant and Fungal Species Descriptions
  • Enzyme Catalysis and Immobilization
  • Plant Stress Responses and Tolerance
  • AI in cancer detection
  • Microbial Metabolic Engineering and Bioproduction
  • dental development and anomalies
  • Plant Diversity and Evolution
  • Tryptophan and brain disorders

Sichuan University
2023-2025

Guangxi Normal University
2021-2024

China University of Geosciences
2021-2024

Beijing Technology and Business University
2024

State Key Laboratory of Hydraulics and Mountain River Engineering
2024

Sun Yat-sen University
2024

Chang'an University
2024

Harbin Medical University
2023

Chongqing Medical University
2021-2022

Hainan University
2020-2021

The advancement of single-cell sequencing has progressed our ability to solve biological questions. Cell type annotation is vital importance this process, allowing for the analysis and interpretation enormous datasets. At present, however, manual cell which predominant approach remains limited by both speed requirement expert knowledge.To address these challenges, we constructed a hierarchically organized marker map through manually curating over 26,000 entries from about 7000 publications....

10.1186/s13073-023-01249-5 article EN cc-by Genome Medicine 2023-11-03

Dental Panoramic radiography (DPR) image provides a potentially inexpensive source to evaluate bone density change through visual clue analysis on trabecular structure. However, dense overlapping of structures in DPR and scarcity labeled samples make learning accurate mapping from patches osteoporosis condition challenging. In this paper, we propose deep Octuplet Siamese Network (OSN) learn fuse discriminative features for prediction using multiple DRP patches. By exploring common features,...

10.1109/embc.2018.8512755 article EN 2018-07-01

Since the impoundment of Three Gorges Reservoir (TGR) in June 2003, fluctuation reservoir water level coupled with rainfall has resulted more than 2500 landslides this region. Among these instability problems, most colluvial exhibit slow-moving patterns and pose a significant threat to local people channel navigation. Advanced monitoring techniques are therefore implemented investigate landslide deformation provide insights for subsequent countermeasures. In study, development pattern large...

10.3390/rs13020224 article EN cc-by Remote Sensing 2021-01-11

Soil thickness, intended as depth to bedrock, is a key input parameter for many environmental models. Nevertheless, it often difficult obtain reliable spatially exhaustive soil thickness map in wide-area applications, and existing prediction models have been extensively applied only test sites with shallow depths. This study addresses this limitation by showing the results of an application section Wanzhou County (Three Gorges Reservoir Area, China), where varies from 0 ∼40 m. Two different...

10.1016/j.gsf.2022.101514 article EN cc-by-nc-nd Geoscience Frontiers 2022-11-25

A field study was conducted to compare FM-1 inoculation by irrigation and spraying for promoting Bidens pilosa L. phytoremediation of cadmium (Cd)-contaminated soil. Cascading relationships between bacterial soil properties, plant growth-promoting traits, biomass Cd concentrations in were explored based on the partial least squares path model (PLS-PM). The results indicated that with not only improved rhizosphere environment B. but also increased extracted from Moreover, Fe P leaves play...

10.1016/j.ecoenv.2023.114764 article EN cc-by-nc-nd Ecotoxicology and Environmental Safety 2023-03-10

Since the impoundment of Three Gorges Reservoir (TGR) in 2003, numerous slopes have experienced noticeable movement or destabilization owing to reservoir level changes and seasonal rainfall. One case is Outang landslide, a large-scale active on south bank Yangtze River. The latest monitoring data site investigations available are analyzed establish spatial temporal landslide deformation characteristics. Data mining technology, including two-step clustering Apriori algorithm, then used...

10.1016/j.jrmge.2023.09.030 article EN cc-by-nc-nd Journal of Rock Mechanics and Geotechnical Engineering 2024-01-21

Abstract Landslide-induced tsunamis in reservoirs often pose greater risks than landslides themselves. Existing studies and mitigation practices have prioritized increasing landslide stability to meet safety standards, incurring high costs lacking sustainability. More 5000 developed along the Three Gorges Reservoir banks China, some may trigger tsunamis. To effectively sustainably manage risk of landslide-tsunami hazard chains (LTHC), we propose a new framework (based on quantitative...

10.1007/s10346-024-02283-z article EN cc-by Landslides 2024-06-14

Abstract Large phylogenies derived from publicly available genetic sequences are becoming a popular and indispensable tool in addressing core questions ecology evolution, as well tackling challenging conservation issues. Optimizing taxonomic coverage data quality is essential for improving the precision reliability of phylogenetic reconstructions evolutionary inferences. Here we present PyNCBIminer, user‐friendly software that automates assembly large DNA sets GenBank reconstruction using...

10.1111/jse.13155 article EN Journal of Systematics and Evolution 2025-01-03

The power network has a long transmission span and passes through wide areas with complex topography setting various human engineering activities. They lead to frequent landslide hazards, which cause serious threats the safe operation of system. Thus, it is great significance carry out susceptibility assessment for disaster prevention mitigation network. We, therefore, undertake an extensive analysis comparison study between different data-driven methods using case from China. Several...

10.3390/rs13245068 article EN cc-by Remote Sensing 2021-12-14

To evaluate the accuracy of CBCT in assessing trabecular structures.Two human mandibles were scanned by micro-CT (Skyscan 1173 high-energy spiral scan micro-CT; Skyscan NV, Kontich, Belgium) and (3D Accuitomo 170; Morita, Japan). The images reconstructed with 0.5 1 mm thicknesses. condylar selected for registration. A parallel algorithm histogram computation was introduced to perform mutual information (MI) value used match between obtained from CBCT.In comparison image two samples,...

10.1259/dmfr.20160435 article EN Dentomaxillofacial Radiology 2017-03-28

Coordinated plant adaptation involves the interplay of multiple traits driven by habitat-specific selection pressures. Pleiotropic effects, wherein genetic variants a single gene control traits, can expedite such adaptations. Until present, only limited number genes have been reported to exhibit pleiotropy. Here, we create recombinant inbred line (RIL) population derived from two Arabidopsis thaliana (A. thaliana) ecotypes originating divergent habitats. Using this RIL population, identify...

10.1016/j.jgg.2023.08.004 article EN cc-by-nc-nd Journal of genetics and genomics/Journal of Genetics and Genomics 2023-08-24

A panoramic radiography image provides not only details of teeth but also rich information about trabecular bone. Recent studies have addressed the correlation between bone structure and osteoporosis. In this paper, we collect a dataset containing 40 images from different subjects, construct new methodology based on two-stage classification framework that combines multiple regions interest (ROIs) for osteoporosis prescreening. first stage, support vector machines (SVMs) are adopted to...

10.1109/isbi.2017.7950498 article EN 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) 2017-04-01

Background. Cancer of unknown primary (CUP) is a type malignant tumor, which histologically diagnosed as metastatic carcinoma while the tissue-of-origin cannot be identified. CUP accounts for roughly 5% all cancers. Traditional treatment primarily broad-spectrum chemotherapy; however, prognosis relatively poor. Thus, it clinical importance to accurately infer CUP. Methods. We developed gradient boosting framework trace 20 types solid tumors. Specifically, we downloaded expression profiles...

10.1155/2021/6653793 article EN cc-by BioMed Research International 2021-02-17

Some carcinomas show that one or more metastatic sites appear with unknown origins. The identification of primary tumor tissues is crucial for physicians to develop precise treatment plans patients. With origin sites, it challenging design specific Usually, those patients receive broad-spectrum chemotherapy, while still having poor prognosis though. Machine learning has been widely used and already achieved significant advantages in clinical practices. In this study, we classify predict a...

10.3389/fbioe.2020.607126 article EN cc-by Frontiers in Bioengineering and Biotechnology 2020-11-24

Osteoporosis is the common cause for a broken bone among senior citizens. Early diagnosis of osteoporosis requires routine examination which may be costly patients. A potential low cost to identify citizen at high risk by pre-screening during dental examination. Therefore, analysis using radiographs severs as key step in The aim this study localize landmarks are helpful assess evidence osteoporosis. We collect eight critical analysis. Our goal these automatically given radiographic image. To...

10.1117/12.2216455 article EN Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE 2016-03-21

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10.2139/ssrn.4798769 preprint EN 2024-01-01
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