A Novel Neural Network Approach for Predicting the Arrival Time of Buses for Smart On-Demand Public Transit

Among the major public transportation systems in cities, bus transit has its problems, including more accuracy and reliability when estimating the bus arrival time for riders. This can lead to delays and decreased ridership, especially in cities where public transportation is heavily relied upon. A common issue is that the arrival times of buses do not match the schedules, resulting in latency for fixed schedules. According to the study in this paper on New York City bus data, there is an average delay of around eight minutes or 491 seconds mismatch between the bus arrivals and the actual scheduled time. This research paper presents a novel AI-based data-driven approach for estimating the arrival times of buses at each transit point (station). Our approach is based on a fully connected neural network and can predict the arrival time collectively across all bus lines in large metropolitan areas. Our neural-net data-driven approach provides a new way to estimate the arrival time of the buses, which can lead to a more efficient and smarter way to bring the bus transit to the general public. Our evaluation of the network bus system with more than 200 bus lines, and 2 million data points, demonstrates less than 40 seconds of estimated error for arrival times. The inference time per each validation set data point is less than 0.006 ms

Towards Understanding the Benefits and Challenges of Demand Responsive Public Transit- A Case Study in the City of Charlotte, NC

Access to adequate public transportation plays a critical role in inequity and socio-economic mobility, particularly in low-income communities. Low-income workers who rely heavily on public transportation face a spatial disparity between home and work, which leads to higher unemployment, longer job searches, and longer commute times. The overarching goal of this study is to get initial data that would result in creating a connected, coordinated, demand-responsive, and efficient public bus system that minimizes transit gaps for low-income, transit-dependent communities. To create equitable metropolitan public transportation, this paper evaluates existing CATS mobile applications that assist passengers in finding bus routes and arrival times. Our community survey methodology includes filling out questionnaires on Charlotte's current bus system on specific bus lines and determining user acceptance for a future novel smart technology. We have also collected data on the demand and transit gap for a real-world pilot study, Sprinter bus line, Bus line 7, Bus line 9, and Bus lines 97-99. These lines connect all of Charlotte City's main areas and are the most important bus lines in the system. On the studied routes, the primary survey results indicate that the current bus system has many flaws, the major one being the lack of proper timing to meet the needs of passengers. The most common problems are long commutes and long waiting times at stations. Moreover, the existing application provides inaccurate information, and on average, 80 percent of travelers and respondents are inclined to use new technology.Comment: 22 pages, 54 figure

RNA-seq analysis and reconstruction of gene networks involved in response to salinity stress in quinoa (cv. Titicaca)

Abstract To better understand the mechanisms involved in salinity stress, the adaptability of quinoa cv. Titicaca—a halophytic plant—was investigated at the transcriptome level under saline and non-saline conditions. RNA-sequencing analysis of leaf tissue at the four-leaf stage by Illumina paired—end method was used to compare salt stress treatment (four days after stress at 13.8 dsm−1) and control. Among the obtained 30,846,354 transcripts sequenced, 30,303 differentially expressed genes from the control and stress treatment samples were identified, with 3363 genes expressed ≥ 2 and false discovery rate (FDR) of < 0.001. Six differential expression genes were then selected and qRT-PCR was used to confirm the RNA-seq results. Some of the genes (Include; CML39, CBSX5, TRX1, GRXC9, SnRKγ1 and BAG6) and signaling pathways discussed in this paper not been previously studied in quinoa. Genes with ≥ 2 were used to design the gene interaction network using Cytoscape software, and AgriGO software and STRING database were used for gene ontology. The results led to the identification of 14 key genes involved in salt stress. The most effective hub genes involved in salt tolerance were the heat shock protein gene family. The transcription factors that showed a significant increase in expression under stress conditions mainly belonged to the WRKY, bZIP and MYB families. Ontology analysis of salt stress-responsive genes and hub genes revealed that metabolic pathways, binding, cellular processes and cellular anatomical entity are among the most effective processes involved in salt stress

Myocardial and Vascular Involvement in Patients with Takayasu Arteritis: A Cardiovascular MRI Study

We aimed to explore the cardiovascular magnetic resonance (CMR) of Takayasu arteritis (TA) and its cardiovascular complications. CMR was conducted on 37 TA patients and 28 healthy individuals. We evaluated the CMR findings and adverse cardiovascular complications at the time of the CMR (ACCCMR). After 8 to 26 months, the major adverse cardiac and cerebrovascular events (MACCEs) were evaluated. The TA included 25 women (67.6%), aged 36 ± 16 years old, and 28 age- and sex-matched healthy controls. Left ventricular (LV) ejection fraction was significantly lower in the TA group than in the control group (51 ± 9% vs. 58 ± 1.7%; p p CMR was seen in 13 TA patients (35.1%), with the most common cardiac complication being myocarditis (16.2%). During a median follow-up of 18 months (8–26 months), nine patients developed MACCEs, of which the most common was cerebrovascular accident in five (13.5%). The LVGLS of the CMR had the strongest association with complications. Myocardial strain values, especially LVGLS, can reveal concurrent and future cardiovascular complications in TA patients