Related papers: A gridded establishment dataset as a proxy for eco…
We present a new approach to estimating the interdependence of industries in an economy by applying data science solutions. By exploiting interfirm buyer--seller network data, we show that the problem of estimating the interdependence of…
This study develops a new method to quantify neighborhood activity levels at high spatial and temporal resolutions and test whether, and to what extent, behavioral responses to social distancing policies vary with socioeconomic and…
Scientific knowledge flows enable cumulative progress by connecting researchers across disciplines, institutions, and countries. Yet it remains unclear how geography and national structures continue to shape these exchanges in an…
Business Knowledge Graphs (KGs) are important to many enterprises today, providing factual knowledge and structured data that steer many products and make them more intelligent. Despite their promising benefits, building business KG…
This study employs the annual unbalanced panel data of 42 listed banks in China from 2006 to 2021, adopts the non-radial and non-oriented super-efficiency Data envelopment analysis (Super-SBM-UND-VRS based DEA) model considering NPL as…
Foucaud, Krishna and Lekshmi recently introduced the concept of monitoring edge-geodetic sets in graphs, and a related graph invariant. These are sets of vertices such that the removal of any edge changes the distance between some pair of…
This study investigates the economic complexity of Indian states by constructing a state-industry bipartite network using firm-level data on registered companies and their paid-up capital. We compute the Economic Complexity Index and apply…
This paper takes the graph neural network as the technical framework, integrates the intrinsic connections between enterprise financial indicators, and proposes a model for enterprise credit risk assessment. The main research work includes:…
Road transport sector is found to be one of the major emitters, and responsible for serious air pollution and huge pubic health losses. One important parameter for determining the consequences of transport demand shocks for the…
Extreme public health interventions play a critical role in mitigating the local and global prevalence and pandemic potential of COVID-19. Here, we use population size for pathogen transmission to measure the intensity of public health…
Graphlets are subgraphs rooted at a fixed vertex. The number of occurrences of graphlets aligned to a particular vertex, called graphlet degree sequence (gds), gives a topological description of the surrounding of the analyzed vertex.…
In the 1990s, China started a process of structural reforms and of trade liberalization, which was followed by the accession to the World Trade Organization (WTO) in 2001. In this paper, we analyze trade patterns of Chinese firms for the…
The growth of business firms is an example of a system of complex interacting units that resembles complex interacting systems in nature such as earthquakes. Remarkably, work in econophysics has provided evidence that the statistical…
Renewable energy such as solar power is critical to fight the ever more serious climate change. China is the world leading installer of solar panel and numerous solar power plants were built. In this paper, we proposed a deep learning…
The distribution of facilities is closely related to our social economic activities. Recent studies have reported a scaling relation between population and facility density with the exponent depending on the type of facility. In this paper,…
Nestedness has traditionally been used to detect assembly patterns in meta-communities and networks of interacting species. Attempts have also been made to uncover nested structures in international trade, typically represented as bipartite…
We analyze nearly 20 million geocoded PubMed articles with author affiliations. Using K-means clustering for the lower 48 US states and mainland China, we find that the average published paper is within a relatively short distance of a few…
Characterizing urban environments with broad coverages and high precision is more important than ever for achieving the UN's Sustainable Development Goals (SDGs) as half of the world's populations are living in cities. Urban building height…
This research seeks to measure the impact of people with technological knowledge on regional digital economic activity and the implications of prosperous cities' contagion effect on neighbouring ones. The focus of this study is…
Robust grasping in cluttered environments remains an open challenge in robotics. While benchmark datasets have significantly advanced deep learning methods, they mainly focus on simplistic scenes with light occlusion and insufficient…