A5075660642- Human Mobility and Location-Based Analysis
- Data Management and Algorithms
- Geographic Information Systems Studies
- Transportation Planning and Optimization
- Traffic Prediction and Management Techniques
- Urban Transport and Accessibility
- Data-Driven Disease Surveillance
- Land Use and Ecosystem Services
- COVID-19 epidemiological studies
- Advanced Computational Techniques and Applications
- Remote Sensing and Land Use
- Spatial and Panel Data Analysis
- Crime Patterns and Interventions
- Neural Networks and Applications
- Adaptive optics and wavefront sensing
- Adaptive Control of Nonlinear Systems
- Evacuation and Crowd Dynamics
- Adaptive Dynamic Programming Control
- Microbial Metabolic Engineering and Bioproduction
- Impact of Light on Environment and Health
- Automated Road and Building Extraction
- Data Mining Algorithms and Applications
- Anomaly Detection Techniques and Applications
- Optical measurement and interference techniques
- Maritime Navigation and Safety
Guangdong Research Institute of Water Resources and Hydropower
2025
Nanjing University
2025
University College London
2015-2024
Shenzhen Technology University
2018-2024
Institute of Optics and Electronics, Chinese Academy of Sciences
2017-2024
Shanghai Normal University
2024
Sichuan University
2024
Southwest University of Science and Technology
2024
Chinese Academy of Sciences
2012-2024
Washington University in St. Louis
2022-2024
N6-methyladenosine (m6A) is enriched in 3'untranslated region (3'UTR) and near stop codon of mature polyadenylated mRNAs mammalian systems has regulatory roles eukaryotic mRNA transcriptome switch. Significantly, the mechanism for this modification preference remains unknown, however. Herein we report a characterization full m6A methyltransferase complex HeLa cells identifying METTL3/METTL14/WTAP/VIRMA/HAKAI/ZC3H13 as key components, show that VIRMA mediates preferential methylation 3'UTR...
Landslides are one of the most destructive natural hazards; they can drastically alter landscape morphology, destroy man-made structures, and endanger people's life. Landslide susceptibility maps (LSMs), which show spatial likelihood landslide occurrence, crucial for environmental management, urban planning, minimizing economic losses. To date, majority research into data mining LSM uses small-scale case studies focusing on a single type landslide. This paper presents approach to producing...
Image-guided depth completion aims to generate dense maps with sparse measurements and corresponding RGB images. Currently, spatial propagation networks (SPNs) are the most popular affinity-based methods in completion, but they still suffer from representation limitation of fixed affinity over smoothing during iterations. Our solution is estimate independent matrices each SPN iteration, it over-parameterized heavy calculation.This paper introduces an efficient model that learns among...
The landscape in which people live is made up of many features, are named and have importance for cultural reasons. Prominent among these the naming upland features such as mountains, but mountains an enigmatic phenomenon do not bear precise repeatable definition. They a vague spatial extent, recent research has modelled classes fuzzy sets. We take specifically multi‐resolution approach to definition set membership morphometric landscape. explore this idea with respect identification...
Previous research and applications in construction resource optimization have focused on tracking the location of material equipment. There is a lack studies remote monitoring for improving safety health workforce. This paper presents new approach ergonomically safe unsafe behavior workers. The study relies methodology that utilizes fusion data from continuous workers' physiological status. To monitor workers activities, authors deployed nonintrusive real-time worker sensing (RTLS) status...
Understanding travel behaviour and demand is of constant importance to transportation communities agencies in every country. Nowadays, attempts have been made automatically infer modes from positional data, such as the data collected by using GPS devices so that cost time budget conventional diary survey could be significantly reduced. Some limitations, however, exist literature, aspects collection (sample size selected, duration study, granularity data), selection variables (or combination...
Background Every day, around 400 million tweets are sent worldwide, which has become a rich source for detecting, monitoring and analysing news stories special (disaster) events. Existing research within this field follows key words attributed to an event, temporal changes in word usage. However, method requires prior knowledge of the event order know follow, does not guarantee that chosen will be most appropriate monitor. Methods This paper suggests alternative methodology detection using...
Weather conditions may significantly impact a series of everyday human decisions and activities. As result, engineers seek to integrate weather-related data into traffic operations in order improve the current state practice. Travel times speeds are two elements transportation system that be greatly affected by weather resulting deterioration roadway network performance. This study aims investigate different intensities rain, snow temperature levels on macroscopic travel Greater London area...
Background When analytical techniques are used to understand and analyse geographical events, adjustments the datasets (e.g. aggregation, zoning, segmentation etc.) in both spatial temporal dimensions often carried out for various reasons. The ‘Modifiable Areal Unit Problem’ (MAUP), which is a consequence of dimension, has been widely researched. However, its counterpart generally ignored, especially space-time analysis. Methods In analogy MAUP, Modifiable Temporal Problem (MTUP) defined as...
Non-Recurrent Congestion events (NRCs) frustrate commuters, companies and traffic operators because they cause unexpected delays. Most existing studies consider NRCs to be an outcome of incidents on motorways. The differences between motorways urban road networks, the fact that are not only NRCs, limit usefulness automatic incident detection methods for identifying networks. In this paper we propose NRC methodology support accurate large To achieve this, substantially high Link Journey Time...
Decades of empirical research demonstrate that crime is concentrated at a range spatial scales, including street segments. Further, the degree clustering particular geographic units remains noticeably stable and consistent; finding Weisburd (Criminology 53:133-157, 2015) has recently termed 'law concentration places'. Such findings suggest future locations should-to some extent least-be predictable. To date, methods forecasting where most likely to next occur have focused either on...
As more and real time spatio-temporal datasets become available at increasing spatial temporal resolutions, the provision of high quality, predictive information about processes becomes an increasingly feasible goal. However, many sensor networks that collect are prone to failure, resulting in missing data. To complicate matters, data is often not random, characterised by long periods where no observed. The performance traditional univariate forecasting methods such as ARIMA models decreases...
Abstract Short‐term traffic flow prediction on a large‐scale road network is challenging due to the complex spatial–temporal dependencies, directed topology, and high computational cost. To address challenges, this article develops graph deep learning framework predict with accuracy efficiency. Specifically, we model dynamics of as an irreducible aperiodic Markov chain graph. Based representation, novel inception residual (STGI‐ResNet) developed for network‐based prediction. This integrates...
The coronavirus (COVID-19) pandemic has caused significant global mortality and impacted lives around the world. Virus Watch aims to provide evidence on which public health approaches are most likely be effective in reducing transmission impact of virus, will investigate community incidence, symptom profiles COVID-19 relation population movement behaviours.Virus is a household cohort study acute respiratory infections England Wales run from June 2020 August 2021. recruit 50 000 people,...
ObjectivesSeroprevalence studies can provide a measure of SARS-CoV-2 cumulative incidence, but better understanding spike and nucleocapsid (anti-N) antibody dynamics following infection is needed to assess the longevity detectability.MethodsAdults aged ≥18 years, from households enrolled in Virus Watch prospective community cohort study England Wales, provided monthly capillary blood samples, which were tested for anti-N. Participants self-reported vaccination dates past medical history....
In recent decades, we have witnessed great advances on the Internet of Things, mobile devices, sensor-based systems, and resulting big data infrastructures, which gradually, yet fundamentally influenced way people interact with in digital physical world. Many human activities now not only operate geographical (physical) space but also cyberspace. Such changes triggered a paradigm shift geographic information science (GIScience), as cyberspace brings new perspectives for roles played by...
Abstract Background Workers across different occupations vary in their risk of SARS-CoV-2 infection, but the direct contribution occupation to this relationship is unclear. This study aimed investigate how infection differed occupational groups England and Wales up April 2022, after adjustment for potential confounding stratification by pandemic phase. Methods Data from 15,190 employed/self-employed participants Virus Watch prospective cohort were used generate ratios virologically- or...