Experimental Study for Optimizing Pedestrian Flows at Bottlenecks of Subway Stations

In subway stations, bottlenecks are the narrowed areas that reduce pedestrian flows in channels. Because pedestrians at bottlenecks are forced to dense together, bottlenecks decrease flow efficiency and pedestrians’ transfer comfort and may trigger serious crowd disasters such as trampling. This study used pedestrian experiments to investigate the methods of optimizing pedestrian traffic at bottlenecks of subway stations. Three optimization measures were proposed and evaluated by analyzing the characteristics of pedestrian flows, including efficiency, smoothness, and security. In this paper, setting the rear sides of the bottleneck entrance as straight and surface funnel shapes is called straight funnel shape and surface funnel shape, respectively. Setting a column at a bottleneck is called the column obstacle. The results showed that when efficiency or security come first, a column on the left is recommended; when comfort comes first, a concave funnel is recommended; when comprehensiveness is prioritized, a column on the left is recommended. Moreover, the larger the volume, the optimization is more obvious. Although many  bottlenecks cannot be prevented when subway stations are constructed, the proposed optimization measures may help ease their adverse effects by improving facility efficiency, smoothness, and security, and by providing recommendations for designing and managing subway stations.</p

Patent Keyword Extraction Algorithm Based on Distributed Representation for Patent Classification

Many text mining tasks such as text retrieval, text summarization, and text comparisons depend on the extraction of representative keywords from the main text. Most existing keyword extraction algorithms are based on discrete bag-of-words type of word representation of the text. In this paper, we propose a patent keyword extraction algorithm (PKEA) based on the distributed Skip-gram model for patent classification. We also develop a set of quantitative performance measures for keyword extraction evaluation based on information gain and cross-validation, based on Support Vector Machine (SVM) classification, which are valuable when human-annotated keywords are not available. We used a standard benchmark dataset and a homemade patent dataset to evaluate the performance of PKEA. Our patent dataset includes 2500 patents from five distinct technological fields related to autonomous cars (GPS systems, lidar systems, object recognition systems, radar systems, and vehicle control systems). We compared our method with Frequency, Term Frequency-Inverse Document Frequency (TF-IDF), TextRank and Rapid Automatic Keyword Extraction (RAKE). The experimental results show that our proposed algorithm provides a promising way to extract keywords from patent texts for patent classification

Pedestrian Walking Behavior Revealed through a Random Walk Model

This paper applies method of continuous-time random walks for pedestrian flow simulation. In the model, pedestrians can walk forward or backward and turn left or right if there is no block. Velocities of pedestrian flow moving forward or diffusing are dominated by coefficients. The waiting time preceding each jump is assumed to follow an exponential distribution. To solve the model, a second-order two-dimensional partial differential equation, a high-order compact scheme with the alternating direction implicit method, is employed. In the numerical experiments, the walking domain of the first one is two-dimensional with two entrances and one exit, and that of the second one is two-dimensional with one entrance and one exit. The flows in both scenarios are one way. Numerical results show that the model can be used for pedestrian flow simulation

Adaptability Analysis of Service Facilities in Transfer Subway Stations

Service capability and matching degree of transfer facilities are directly related to the operational efficiency and safety of a subway station. Owing to differences in planning and construction, the transfer subway stations in developing countries have some defects in facility size and serviceability, which cause a decline in service performance, operation efficiency, and security level. In order to solve the problems, traffic investigations were conducted on the form, size, and operation status of several typical transfer subway facilities. The service facilities were classified within a subway station in this research by considering service objects, service forms, service functions, and several other features. In addition, pedestrian behavior and pedestrian flow characteristics in different service facilities were analyzed in detail. The research results are deemed meaningful for the optimization of service facilities in subway stations and for the development of urban pedestrian transportation systems

Pilot testing of enhanced sorbents for calcium looping with cement production

One of the main challenges for commercialising calcium looping (CaL) as a CO2 capture technology is maintaining a high level of sorbent reactivity during long-term cycling. In order to mitigate the decay in carrying capacity, research has moved towards producing enhanced sorbents. However, this creates potential problems related to ease of scaling up production techniques and production costs, and raises the question as to whether such approaches can be used at large scale. On the other hand, a key advantage of CaL over other carbon capture technologies is synergy with the cement industry, i.e., use of spent sorbent as a feedstock for clinker production. In this work two enhanced materials: (i) limestone doped with HBr through a particle surface impregnation technique; and (ii) pellets prepared from limestone and calcium aluminate cement, were tested in a 25 kWth dual fluidised bed pilot-scale reactor in order to investigate their capture performance and mechanical stability under realistic CaL conditions. Moreover, the spent sorbent was then used as a raw material to make cement, which was characterised for phase and chemical composition as well as compressive strength. The HBr-doped limestone showed better performance in terms of both mechanical strength and stability of the CO2 uptake when compared to that of pellets. Furthermore, it was shown that the cement produced has similar characteristics and performance as those of commercial CEM 1 cement. This indicates the advantages of using the spent sorbent as feedstock for cement manufacture and shows the benefits of synthetic sorbents in CaL and suitability of end-use of spent sorbents for the cement industry, validating their synergy at pilot scale. Finally, this study demonstrates the possibility of using several practical techniques to improve the performance of CaL at the pilot scale, and more importantly demonstrates that commercial-grade cement can be made from the lime product from this technology

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Morphological diversity of single neurons in molecularly defined cell types.

Dendritic and axonal morphology reflects the input and output of neurons and is a defining feature of neuronal types1,2, yet our knowledge of its diversity remains limited. Here, to systematically examine complete single-neuron morphologies on a brain-wide scale, we established a pipeline encompassing sparse labelling, whole-brain imaging, reconstruction, registration and analysis. We fully reconstructed 1,741 neurons from cortex, claustrum, thalamus, striatum and other brain regions in mice. We identified 11 major projection neuron types with distinct morphological features and corresponding transcriptomic identities. Extensive projectional diversity was found within each of these major types, on the basis of which some types were clustered into more refined subtypes. This diversity follows a set of generalizable principles that govern long-range axonal projections at different levels, including molecular correspondence, divergent or convergent projection, axon termination pattern, regional specificity, topography, and individual cell variability. Although clear concordance with transcriptomic profiles is evident at the level of major projection type, fine-grained morphological diversity often does not readily correlate with transcriptomic subtypes derived from unsupervised clustering, highlighting the need for single-cell cross-modality studies. Overall, our study demonstrates the crucial need for quantitative description of complete single-cell anatomy in cell-type classification, as single-cell morphological diversity reveals a plethora of ways in which different cell types and their individual members may contribute to the configuration and function of their respective circuits

Cellular anatomy of the mouse primary motor cortex.

An essential step toward understanding brain function is to establish a structural framework with cellular resolution on which multi-scale datasets spanning molecules, cells, circuits and systems can be integrated and interpreted1. Here, as part of the collaborative Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based anatomical description of one exemplar brain structure, the mouse primary motor cortex, upper limb area (MOp-ul). Using genetic and viral labelling, barcoded anatomy resolved by sequencing, single-neuron reconstruction, whole-brain imaging and cloud-based neuroinformatics tools, we delineated the MOp-ul in 3D and refined its sublaminar organization. We defined around two dozen projection neuron types in the MOp-ul and derived an input-output wiring diagram, which will facilitate future analyses of motor control circuitry across molecular, cellular and system levels. This work provides a roadmap towards a comprehensive cellular-resolution description of mammalian brain architecture