Exploring human mobility for multi-pattern passenger prediction : a graph learning framework

Traffic flow prediction is an integral part of an intelligent transportation system and thus fundamental for various traffic-related applications. Buses are an indispensable way of moving for urban residents with fixed routes and schedules, which leads to latent travel regularity. However, human mobility patterns, specifically the complex relationships between bus passengers, are deeply hidden in this fixed mobility mode. Although many models exist to predict traffic flow, human mobility patterns have not been well explored in this regard. To address this research gap and learn human mobility knowledge from this fixed travel behaviors, we propose a multi-pattern passenger flow prediction framework, MPGCN, based on Graph Convolutional Network (GCN). Firstly, we construct a novel sharing-stop network to model relationships between passengers based on bus record data. Then, we employ GCN to extract features from the graph by learning useful topology information and introduce a deep clustering method to recognize mobility patterns hidden in bus passengers. Furthermore, to fully utilize spatio-temporal information, we propose GCN2Flow to predict passenger flow based on various mobility patterns. To the best of our knowledge, this paper is the first work to adopt a multi-pattern approach to predict the bus passenger flow by taking advantage of graph learning. We design a case study for optimizing routes. Extensive experiments upon a real-world bus dataset demonstrate that MPGCN has potential efficacy in passenger flow prediction and route optimization. © 2000-2011 IEEE

Risk factors predicting a higher grade of subarachnoid haemorrhage in small ruptured intracranial aneurysm (< 5 mm)

Aim. To identify the risk factors for clinical and radiographic grades of subarachnoid haemorrhage (SAH) in small (&lt; 5 mm) intracranial aneurysms (SIAs). Material and methods. We retrospectively analysed patients with SIAs treated in our centre between February 2009 and June 2018. The clinical status was graded using the Hunt and Hess (H&amp;H) score and the radiological severity of SAH was graded by Fisher grades (FG). The risk factors were determined using multivariate logistic regression analysis. Results. A total of 160 patients with ruptured SIAs (&lt; 5 mm) were included. In univariate analysis, smoking (P = 0.007), alcohol use (P = 0.048), aspirin use (P = 0.001), and higher size ratio (SR) (P = 0.001) were significantly associated with a higher H&amp;H grade (3–5) in SIAs; and smoking (P = 0.019), aspirin use (P = 0.031), inflow angle &lt; 90 degrees (P = 0.011), and aneurysm size (P = 0.039) were significantly associated with a higher FG score (3–4). In the adjusted multivariate analysis, previous SAH (OR, 12.245, 95% CI, 2.261–66.334, P = 0.004), aspirin use (OR, 4.677, 95% CI, 1.392–15.718, P = 0.013), alcohol use (OR, 3.392, 95% CI, 1.146–10.045, P = 0.027), inflow angle &lt; 90 (OR, 3.881, 95% CI, 1.273–11.831, P = 0.017), and higher SR (OR, 6.611, 95% CI, 2.235–19.560, P = 0.001) were independent risk factors for a higher H&amp;H grade in ruptured SIAs; smoking (OR, 2.157, 95% CI, 1.061–4.384, P = 0.034), and inflow angle &lt; 90 degrees (OR, 2.603, 95% CI, 1.324–5.115, P = 0.006) were independent risk factors for a higher FG (3–4). Conclusions. This study revealed that inflow angle &lt; 90 degrees and size ratio, but not absolute size, may highly predict poorer grade of SAH in SRA. Aspirin use, previous SAH, and alcohol use were significantly associated with a higher H&amp;H grade in ruptured SIAs, and smoking was a significant predictor of poorer FG

The 2-Aminoethoxydiphenyl Borate Analog Dpb161 Blocks Storeoperated Ca 2+ Entry In Acutely Dissociated Rat Submandibular Cells

Cellular Ca 2+ signals play a critical role in cell physiology and pathology. In most non-excitable cells, store-operated Ca 2+ entry (SOCE) is an important mechanism by which intracellular Ca 2+ signaling is regulated. However, few drugs can selectively modulate SOCE. 2-Aminoethoxydiphenyl borate (2APB) and its analogs (DPB162 and DPB163) have been reported to inhibit SOCE. Here, we examined the effects of another 2-APB analog, DPB161 on SOCE in acutely-isolated rat submandibular cells. Both patch-clamp recordings and Ca 2+ imaging showed that upon removal of extracellular Ca 2+ ([Ca 2+ ] o =0), rat submandibular cells were unable to maintain ACh-induced Ca 2+ oscillations, but restoration of [Ca 2+ ] o to refill Ca 2+ stores enable recovery of these Ca 2+ oscillations. However, addition of 50 μM DPB161 with [Ca 2+ ] o to extracellular solution prevented the refilling of Ca 2+ store. Fura-2 Ca 2+ imaging showed that DPB161 inhibited SOCE in a concentration-dependent manner. After depleting Ca 2+ stores by thapsigargin treatment, bath perfusion of 1 mM Ca 2+ induced [Ca 2+ ] i elevation in a manner that was prevented by DPB161. Collectively, these results show that the 2-APB analog DPB161 blocks SOCE in rat submandibular cells, suggesting that this compound can be developed as a pharmacological tool for the study of SOCE function and as a new therapeutic agent for treating SOCE-associated disorders

A Statistical Design for Testing Transgenerational Genomic Imprinting in Natural Human Populations

Genomic imprinting is a phenomenon in which the same allele is expressed differently, depending on its parental origin. Such a phenomenon, also called the parent-of-origin effect, has been recognized to play a pivotal role in embryological development and pathogenesis in many species. Here we propose a statistical design for detecting imprinted loci that control quantitative traits based on a random set of three-generation families from a natural population in humans. This design provides a pathway for characterizing the effects of imprinted genes on a complex trait or disease at different generations and testing transgenerational changes of imprinted effects. The design is integrated with population and cytogenetic principles of gene segregation and transmission from a previous generation to next. The implementation of the EM algorithm within the design framework leads to the estimation of genetic parameters that define imprinted effects. A simulation study is used to investigate the statistical properties of the model and validate its utilization. This new design, coupled with increasingly used genome-wide association studies, should have an immediate implication for studying the genetic architecture of complex traits in humans

High-Throughput Functional MicroRNAs Profiling by Recombinant AAV-Based MicroRNA Sensor Arrays

BACKGROUND: microRNAs (miRNAs) are small and non-coding RNAs which play critical roles in physiological and pathological processes. A number of methods have been established to detect and quantify miRNA expression. However, method for high-throughput miRNA function detection is still lacking. PRINCIPAL FINDINGS: We describe an adeno-associated virus (AAV) vector-based microRNA (miRNA) sensor (Asensor) array for high-throughput functional miRNA profiling. Each Asensor contains a Gaussia luciferase (Gluc) and a firefly luciferase (Fluc) expression cassette to sense functional miRNA and to serve as an internal control respectively. Using this array, we acquired functional profiles of 115 miRNAs for 12 cell lines and found "functional miRNA signatures" for several specific cell lines. The activities of specific miRNAs including the let-7 family, miR-17-92 cluster, miR-221, and miR-222 in HEK 293 cells were compared with their expression levels determined by quantitative reverse transcriptase polymerase chain reaction (QRT-PCR). We also demonstrate two other practical applications of the array, including a comparison of the miRNA activity between HEK293 and HEK293T cells and the ability to monitor miRNA activity changes in K562 cells treated with 12-O-tetradecanoylphorbol-13-acetate (TPA). CONCLUSIONS/SIGNIFICANCE: Our approach has potential applications in the identification of cell types, the characterization of biological and pathological processes, and the evaluation of responses to interventions

Formation of Nanolaminated Structure with Enhanced Thermal Stability in Copper

Nanolaminated structure with an average boundary spacing of 67 nm has been fabricated in copper by high-rate shear deformation at ambient temperature. The nanolaminated structure with an increased fraction of low angle grain boundaries exhibits a high microhardness of 2.1 GPa. The structure coarsening temperature is 180 K higher than that of its equiaxial nanograined counterpart. Formation of nanolaminated structure provides an alternative way to relax grain boundaries and to stabilize nanostructured metals with medium to low stacking faults energies besides activation of partial dislocations

Reduction-Responsive Amphiphilic Star Copolymers with Long-chain Hyperbranched Poly(ε-caprolactone) Core and Disulfide Bonds for Trigger Release of Anticancer Drugs

In this contribution, the reduction-responsive star copolymers with long-chain hyperbranched poly(ε-caprolactone) (PCL) (HyperMacs) core and disulfide bonds were synthesized via Cu(I)-catalyzed azide-alkyne cycloaddition (CuAAC) reaction. The HyperMacs core was constructed from disulfide-containing AB2-type PCL macromonomers, which possesses length-adjustable chain segments between branching points, large cavities, low degree of crystallinity, and reduction-responsivity. After grafted with poly(ethylene glycol), the reduction-responsive star copolymers can self-assemble into micelles in aqueous solution. The obtained micelles exhibited much lower critical micelle concentration (CMC) than their linear analogues. The reduction-responsivity from disulfide bonds makes them a promising carrier candidate for trigger release of anticancer drugs. The in vitro release results confirmed that their doxorubicin (DOX)-loaded micelles exhibited desirable reduction-triggered release performance. The cellular proliferation inhibition against HepG2 cells demonstrated that the DOX-loaded micelles showed a comparable anticancer activity with free DOX. Therefore, it can be expected that the reduction-sensitive micelles may serve as smart vehicles for intracellular delivery of anti-cancer drugs in tumour therapy

Nucleation Process of the 2017 Nuugaatsiaq, Greenland Landslide

Seismic precursors prior to the failure of rocks are essential for probing the nucleation process and mitigating hazards. However, such precursory events before large landslides are rarely reported possibly due to the lack of near-source observations. The 2017 Nuugaatsiaq, Greenland landslide that was preceded by an abundance of small earthquakes and captured by a local seismic station is a notable exception and offers us a valuable opportunity to investigate how a large landslide initiated. Prior work suggests that accelerated creeping plays an important role during the landslide nucleation process. However, by analyzing the temporal evolution of the waveform similarities, waveform amplitudes, and inter-event times of the seismic precursors, we find that the Nuugaatsiaq landslide was very likely triggered by a series of accelerated and migratory small earthquakes approaching the nucleation area of the upcoming landslide, thus providing important insights into the failure initiation of massive landslides

Mapping the research on scientific collaboration

The aim of this paper was to identify the trends and hot topics in the study of scientific collaboration via scientometric analysis. Information visualization and knowledge domain visualization techniques were adopted to determine how the study of scientific collaboration has evolved. A total of 1,455 articles on scientific cooperation published between 1993 and 2007 were retrieved from the SCI, SSCI and A&amp;HCI databases with a topic search of scientific collaboration or scientific cooperation for the analysis. By using CiteSpace, the knowledge bases, research foci, and research fronts in the field of scientific collaboration were studied. The results indicated that research fronts and research foci are highly consistent in terms of the concept, origin, measurement, and theory of scientific collaboration. It also revealed that research fronts included scientific collaboration networks, international scientific collaboration, social network analysis and techniques, and applications of bibliometrical indicators, webmetrics, and health care related areas.</p

Evaluation and Analysis of Design Elements for Sustainable Renewal of Urban Vulnerable Spaces

The sustainable renewal design of urban vulnerable spaces is critical for urban space quality improvement. Taking Zhengzhou and surrounding cities as examples, a cognitive framework of urban vulnerable spaces is constructed. The three types of urban vulnerable spaces are vulnerable population, vulnerable cultural, and vulnerable forgotten spaces. Their sustainable renewal design elements comprise multidimensional factors, such as functional requirement, space organization, activity facility, urban context continuation, and material texture. The design elements for the sustainable update of urban vulnerable spaces are evaluated by grey relation analysis (GRA), and update strategies are proposed. The result shows that (1) vulnerable population spaces were shown to have the highest sensitivity to functional requirements and activity facility design elements, while vulnerable cultural spaces have high relevance to urban context continuation and functional requirement design elements. Furthermore, space organization, activity facility, and urban context continuation design elements all show high relevance and importance in vulnerable forgotten spaces. (2) The update of vulnerable population spaces should be designed to achieve functional communion; vulnerable cultural spaces can be reshaped through urban context implantation, and vulnerable forgotten spaces can use space creation to enhance ecological space continuity, achieving sustainable renewal. The study provides a reference for decision-making for improving urban vulnerable habitats and the sustainable renewal design of atypical urban space types