Macroscopic Fundamental Diagram Estimation Considering Traffic Flow Condition of Road Network

A macroscopic fundamental diagram (MFD) is an important basis for road network research. It describes the functional relationship between the average flow and average density of the road network. We proposed an MFD estimation method based on the traffic flow condition. Firstly, according to statistical theories, the road network data are divided into three traffic flow conditions (free flow, chaotic and congested) bounded by a 95% confidence interval of the maximum traffic capacity of each intersection in the road network. Then, in each condition, we combined principal component analysis and the Jolliffe B4 method to reduce dimension for extracting critical intersections. Finally, the full-scale dataset of the road network was reconstructed to estimate the road network MFD. Through numerical simulation and empirical research, it is found that the root mean square error and absolute percentage error between estimated MFD and true MFD considering the traffic flow condition are smaller than those without considering the traffic flow condition. The MFD estimation and the division of the traffic states of the road network were completed at the same time. The proposed method effectively saves the time cost of road network research and is highly accurate

Fundamental Diagram Estimation Based on Random Probe Pairs on Sub-Segments

A new statistical algorithm is proposed in this paper with the aim of estimating fundamental diagram (FD) in actual traffic and dividing the traffic state. Traditional methods mainly focus on sensor data, but this paper takes random probe pairs as research objects. First, a mathematical method is proposed by using probe pairs data and the jam density to determine the FD on a stationary segment. Second, we applied it to the near-stationary probe traffic state set through linear regression and expectation maximisation iterative algorithm, estimating the free flow speed and the backward wave speed and dividing the traffic state based on the 95% confidence interval of the estimated FD. Finally, simulation and empirical analyses are used to verify the new algorithm. The simulation analysis results show that the estimation error corresponding to the free flow speed and the backward wave speed are 1.0668 km/h and 0.0002 km/h respectively. The empirical analysis calculates the maximum capacity of the road and divides the traffic into three states (free flow state, breakdown state, and congested state), which demonstrates the accuracy and practicability of the research in this paper, and provides a reference for urban traffic monitoring and government decision-making

Spectral Analysis of Satellite Altimeters and Tide Gauges Data around the Northern Australian Coast

The north of Australia is known for its complex tidal system, where the highest astronomical tides (HATs) reach 12 m. This paper investigates the tidal behaviour in this region by developing spectral climatology for tide gauge and altimetry data. Power spectral density analysis is applied to detect the magnitude of ocean tides in 20 years of sea-level data from multimission satellite altimeters and tide gauges. The spectra of altimetry sea level anomaly (SLA) time series have their strongest peaks centred at approximately 2.11, 5.88, and 7.99 cycles per year (cpy), corresponding to the diurnal and semidiurnal tidal constituents K1, M2, and O1, respectively. Closer to the coastline, the spectra peak at high-frequency overtide and shallow-water constituents such as M4, MK4, and MK3. There have been many large, high-frequency spectral peaks near the coastline, indicating the difficulty of predicting tidal signals by coastal altimetry. Similar to altimetry observations, there are dominant semidiurnal and diurnal tidal peaks in tide gauge SLA time series accompanying a number of overtides. The semidiurnal and diurnal peaks are mostly higher on the northwest coast of Australia compared with the north and northeast coast. The results from both altimetry and tide gauges indicate that tidal range increases with increasing continental shelf

Combined effects of colonial size and concentration of Microcystis aeruginosa on the life history traits of Daphnia similoides

Microcystis colonial size and concentration have detrimental effects on life history traits of Daphnia, but their detailed interactions have remained unclear so far. Our experiments show that the interaction between Microcystis colonial size and concentration on maturation time, life expectancy, net reproductive rate and innate capacity of increase in Daphnia similoides was significant. In all groups, the survival rate of D. similoides was 100% within 8 days. This value then declined quickly in the large-colony groups and in the SH group of Microcystis. Colonial M. aeruginosa significantly reduced the maturation time and body length at maturity of D. similoides. The number of offspring at first reproduction per female in the SH group of Microcystis was significantly higher than those in other groups. Net reproductive rate of D. similoides in the SL group of Microcystis was significantly higher than those in other groups of Microcystis. The innate capacity of increase of D. similoides in small-colony Microcystis groups was significantly higher than that in the large-colony groups. The results suggested that the effect of smallcolony Microcystis on the reproduction of Daphnia was positive under lower concentration, while their toxicity was intensitied under higher concentration when small-colony Microcystis were by Daphnia as food

Enhance the Discovery and Interoperability of Culturally Rich Information: the Chinese Women Poets WikiProject

Traditionally, special collections such as culture and heritage collections and their name authority data were cataloged using local cataloging standards with limited data interoperability. The library community has questioned for a number of years how to increase the accessibility and visibility of cultural heritage information stored in centralized databases. Wikidata, a global and open knowledge repository of structured data serving as a hub for linking resources, has emerged as one of possible solutions to library data silo issues. A group of Chinese American librarians from several institutions formed a WikiProject team: Chinese Culture and Heritage group in 2020 to study Wikidata. The group hoped to explore the potential of Wikidata, contribute to the diversity of data in Wikidata which has been increasingly utilized in libraries’ discovery systems, and seek collaboration opportunities. Its primary focus is to create and enhance Wikidata items that showcase Chinese culture and heritage information. This poster will present an overview of the Chinese Women Poets Wikiproject, the first project the group has embarked on, that uses OpenRefine and PyWikibot to enhance over 4,000 Chinese women poets’ names in Wikidata. In addition, the presenters will discuss the challenges and the benefits of the project as well as their future work

Stimulate economic growth by improving transport infrastructure – a lesson from China

This paper uses Feder model to test impacts of transport infrastructure on economic growth. With China provincial data from 1990-2010 the empirical models, including Basic model, Time-Lag model and Spatial model, demonstrate that transport infrastructure does have a positive Spillover Effect on economic growth. However, Direct Effect on economic growth is negative possibly due to Crowding-Out Effect and productivity difference between sectors. The research also proves the Spillover Effects are becoming weaker as time passed. Finally, Spatial Spillover Effect or Network Effects are confirmed

Adrenomedullin expression in epithelial ovarian cancers and promotes HO8910 cell migration associated with upregulating integrin α5β1 and phosphorylating FAK and paxillin

<p>Abstract</p> <p>Background</p> <p>Epithelial ovarian cancer (EOC) is one of the leading causes of cancer deaths in women worldwide. Adrenomedullin (AM) is a multifunctional peptide which presents in various kinds of tumors.</p> <p>Methods</p> <p>In this study, we characterized the expression and function of AM in epithelial ovarian cancer using immunohistochemistry staining. Exogenous AM and small interfering RNA (siRNA) specific for AM receptor CRLR were treated to EOC cell line HO8910. Wound healing assay and flow cytometry were used to measure the migration ability and expression of integrin α5 of HO8910 cells after above treatments. Western blot was used to examine the phosphorylation of FAK and paxillin.</p> <p>Results</p> <p>We found that patients with high AM expression showed a higher incidence of metastasis, larger residual size of tumors after cytoreduction and shorter disease-free and overall survival time. Exogenous AM induced ovarian cancer cell migration in time- and dose- dependent manners. AM upregulated the expression of integrin α5 and phosphorylation of FAK, paxillin as well.</p> <p>Conclusions</p> <p>Our results suggested that AM contributed to the progression of EOC and had additional roles in EOC cell migration by activating the integrin α5β1 signaling pathway. Therefore, we presumed that AM could be a potential molecular therapeutic target for ovarian carcinoma.</p

Seismic Data Interpolation based on Denoising Diffusion Implicit Models with Resampling

The incompleteness of the seismic data caused by missing traces along the spatial extension is a common issue in seismic acquisition due to the existence of obstacles and economic constraints, which severely impairs the imaging quality of subsurface geological structures. Recently, deep learning-based seismic interpolation methods have attained promising progress, while achieving stable training of generative adversarial networks is not easy, and performance degradation is usually notable if the missing patterns in the testing and training do not match. In this paper, we propose a novel seismic denoising diffusion implicit model with resampling. The model training is established on the denoising diffusion probabilistic model, where U-Net is equipped with the multi-head self-attention to match the noise in each step. The cosine noise schedule, serving as the global noise configuration, promotes the high utilization of known trace information by accelerating the passage of the excessive noise stages. The model inference utilizes the denoising diffusion implicit model, conditioning on the known traces, to enable high-quality interpolation with fewer diffusion steps. To enhance the coherency between the known traces and the missing traces within each reverse step, the inference process integrates a resampling strategy to achieve an information recap on the former interpolated traces. Extensive experiments conducted on synthetic and field seismic data validate the superiority of our model and its robustness on various missing patterns. In addition, uncertainty quantification and ablation studies are also investigated.Comment: 14 pages, 13 figure

Five-Minute Cognitive Test as A New Quick Screening of Cognitive Impairment in The Elderly

This study aims to develop a new evaluation method for quickly and conveniently screening cognitive impairment in the elderly. The five-minute cognitive test (FCT) was designed to capture deficits in five domains of cognitive abilities, including episodic memory, language fluency, time orientation, visuospatial function, and executive function. Subsequently, FCT efficiencies in differentiating normally cognitive ability from cognitive impairment were explored and compared with that of the Mini-Mental Status Evaluation (MMSE). Equipercentile equating method was utilized to create a crosswalk between scores of the FCT and MMSE. Further, the association of scores of the FCT and MMSE with hippocampal volumes was investigated. There were 241 subjects aged 60 years or above enrolled in this study, including 107 adults with cognitive abilities in normal range, 107 patients with mild cognitive impairment (MCI), and 27 patients with mild Alzheimer disease (AD). The AUC of FCT for detection of cognitive impairment (MCI and mild AD) was 0.885 (95% CI 0.838 to 0.922). The sensitivity and specificity of FCT for the diagnosis of cognitive impairment were 80.6% and 84.11 %, respectively. FCT’s diagnostic performance was superior to that of MMSE in the same cohort. Mean completion time of FCT was 339.9 ± 67.7 seconds (5-6 min). In addition, a conversion table between scores on the FCT and MMSE was created. Further, the FCT scores were positively correlated with hippocampal volumes. The FCT is a novel, reliable, and valid cognitive screening test for the detection of dementia at early stages