Categorizing Flight Paths using Data Visualization and Clustering Methodologies

This work leverages the U.S. Federal Aviation Administration's Traffic Flow Management System dataset and DV8, a recently developed tool for highly interactive visualization of air traffic data, to develop clustering algorithms for categorizing air traffic by their varying flight paths. Two clustering methodologies, a spatial-based geographic distance model, and a vector-based cosine similarity model, are demonstrated and compared for their clustering effectiveness. Examples of their applications reveal successful, realistic clustering based on automated clustering result determination and human-in-the-loop processes, with geographic distance algorithms performing better for enroute portions of flight paths and cosine similarity algorithms performing better for near-terminal operations, such as arrival paths. A point extraction technique is applied to improve computation efficiency.Comment: Published in the 9th International Conference on Research in Air Transportation (ICRAT'20): https://www.icrat.org/previous-conferences/9th-international-conference/papers

Learning Weakly Supervised Audio-Visual Violence Detection in Hyperbolic Space

In recent years, the task of weakly supervised audio-visual violence detection has gained considerable attention. The goal of this task is to identify violent segments within multimodal data based on video-level labels. Despite advances in this field, traditional Euclidean neural networks, which have been used in prior research, encounter difficulties in capturing highly discriminative representations due to limitations of the feature space. To overcome this, we propose HyperVD, a novel framework that learns snippet embeddings in hyperbolic space to improve model discrimination. Our framework comprises a detour fusion module for multimodal fusion, effectively alleviating modality inconsistency between audio and visual signals. Additionally, we contribute two branches of fully hyperbolic graph convolutional networks that excavate feature similarities and temporal relationships among snippets in hyperbolic space. By learning snippet representations in this space, the framework effectively learns semantic discrepancies between violent and normal events. Extensive experiments on the XD-Violence benchmark demonstrate that our method outperforms state-of-the-art methods by a sizable margin.Comment: 8 pages, 5 figure

Multi-tissue integrative analysis of personal epigenomes

Evaluating the impact of genetic variants on transcriptional regulation is a central goal in biological science that has been constrained by reliance on a single reference genome. To address this, we constructed phased, diploid genomes for four cadaveric donors (using long-read sequencing) and systematically charted noncoding regulatory elements and transcriptional activity across more than 25 tissues from these donors. Integrative analysis revealed over a million variants with allele-specific activity, coordinated, locus-scale allelic imbalances, and structural variants impacting proximal chromatin structure. We relate the personal genome analysis to the ENCODE encyclopedia, annotating allele- and tissue-specific elements that are strongly enriched for variants impacting expression and disease phenotypes. These experimental and statistical approaches, and the corresponding EN-TEx resource, provide a framework for personalized functional genomics

Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data

Under the development pattern of the “double cycle”, optimizing urban economic resilience is tremendously meaningful to improving a city’s affordability and the adaptability of the economy and to promoting the Chinese economy to develop with high quality. Based on Baidu migration big data perspective, exploratory spatial data analysis (ESDA) and multi-scale geographical weighted regression (MGWR) model were used to analyze the spatial characteristics and driving factors of economic resilience in 287 Chinese cities in 2019. The results show that (1) the number of low-level economically resilient cities is the largest and distributed continuously, while the number of high-level economically resilient cities is the lowest and distributed in clusters and blocks; (2) compared with the Pearl River Delta and Yangtze River Delta, the population accumulation characteristic of the Beijing- Tianjin-Hebei region is relatively slow; (3) Both net inflow of population after spring festival and daily flow scale are significantly correlated with urban economic resilience, and the former will affect urban economic resilience; and (4) the spatial heterogeneity of each factor driving is significant, and they have different impact scales. The impact intensity is as follows: net population inflow > innovation ability > public financial expenditure > financial efficiency > urban size. First published online 07 February 202

What Drives Health-Care Spending in China? A Nationwide Decomposition Analysis

10.1080/00036846.2022.2095346Applied Economics5591028-104

Perceived economic prospects during the early stage of COVID-19 breakout

How does a new epidemic affect individuals' expectations on economic prospects in the early stage of the breakout? We implemented an incentivized longitudinal online survey soon after the outbreak of the coronavirus disease 2019 (COVID-19) epidemic in China to answer this question. Results show that fewer new confirmed COVID-19 cases significantly increase individuals' expectations on gross domestic product and consumer price index growth rates. Our finding provides evidence that at the early stage of an unfamiliar epidemic, containing the spread of the disease may help to maintain positive economic expectations among individuals.Ministry of Education (MOE)Nanyang Technological UniversityWu thanks National Natural Science Foundation of China (No. 71373006 and 91546113) for financial support. Yan thanks Nanyang Technological University (NTU), Start Up Grant for financial support. Yan also thanks the Ministry of Education of Singapore (MOE) Tier 1 Grant (RG84/47) and CoHASS Research Support Grant for financial support

Table_1_Coupled and decoupled legumes and cereals in prehistoric northern and southern China.xlsx

Legumes and cereals, which provide different nutrients, are cultivated as coupled crops in most centers of plant domestication worldwide. However, as the only legume domesticated in China, the spatio-temporal distribution of soybeans and its status in the millet- and rice-based agricultural system of the Neolithic and Bronze Ages remains elusive. Here, archaeobotanical evidence of soybeans (n=254), millet (n=462), rice (n=482), and zooarchaeological evidence of fish (n=138) were synthesized to elucidate the phenomenon of coupled or decoupled cereals and legumes in prehistoric China. During the Neolithic and Bronze Ages, soybeans was mostly confined to northern China and rarely found in southern China, serving as a companion to millet. In contrast, fish remains have been widely found in southern China, indicating a continuous reliance on fish as a staple food besides rice. Thus, an antipodal pattern of millet-soybeans and rice-fish agricultural systems may have been established in northern and southern China since the late Yangshao period (6000–5000 cal BP) respectively. These two agricultural systems were not only complementary in terms of diet, but they also exhibited positive interactions and feedback in the coculture system. Consequently, these two systems enabled the sustainable intensification of agriculture and served as the basis for the emergence of complex societies and early states in the Yellow and Yangtze Rivers.</p

Eco-Corona vs Protein Corona: Effects of Humic Substances on Corona Formation and Nanoplastic Particle Toxicity in Daphnia magna

Despite many studies on the toxicity of nanoplastic particles (NPPs) to aquatic invertebrates, the effects of ecological constituents such as humic substances (HSs) are often neglected. In our study, Daphnia magna was used to evaluate the effects of three HSs, natural organic matter (NOM), fulvic acid (FA), and humic acid (HA), on NPP toxicity and corona formation. Acute toxicities of NPPs were reduced by all HSs at environmentally relevant concentrations. NPPs elicited the upregulation of all genes related to detoxification, oxidative stress, and endocrine activity after 7 days of exposure. The presence of NOM or HA resulted in the mitigation of gene expression, whereas significantly higher upregulation of all of the genes was observed with FA. The presence of FA led to increased protein adsorption on NPPs in D. magna culture medium (eco-corona, EC) and homogenates (protein corona, PC), while there was less adsorption in the presence of HA. The highly abundant proteins identified in EC are involved in immune defense, cell maintenance, and antipredator response, while those in PC are responsible for lipid transport, antioxidant effects, and estrogen mediation. Our findings revealed the key influence of HSs on the toxicity of NPPs and provide an analytical and conceptual foundation for future study

Dispersion Management in 10-PW Laser Front End

To improve pulse contrast in chirped pulse amplification petawatt laser systems, the regenerative amplifier is substituted with a multipass amplifier at the Shanghai Superintense Ultrafast Laser Facility (SULF). To reduce the consequent angular dispersion of the broadband spectrum, a double-grating stretcher is established in the SULF front end. A grating compressor is set up for the 10-PW front end to obtain 20-TW output. An accurate adjustment method of grating attitude (angular position) is presented, which references the direction of gravity, improving dispersion management and focusing ability of the beam. After a pulse passes the front end compressor, its duration and phase in the frequency domain are measured, and the duration can be continuously compressed to &lt;24 fs