Development and Application of Fire Video Image Detection Technology in China’s Road Tunnels

A large number of highway tunnels, urban road tunnels and underwater tunnels have been constructed throughout China over the last two decades. With the rapid increase in vehicle traffic, the number of fire incidents in road tunnels have also substantially increased. This paper aims to review the development and application of fire video image detection (VID) technology and their impact on fire safety in China’s road tunnels. The challenges of fire safety in China’s road tunnels are analyzed. The capabilities and limitations of fire detection technologies currently used in China’s road tunnels are discussed. The research and development of fire VID technology in road tunnels, including various detection algorithms, evolution of VID systems and evaluation of their performances in various tunnel tests are reviewed. Some cases involving VID applications in China’s road tunnels are reported. The studies show that the fire VID systems have unique features in providing fire protection and their detection capability and reliability have been enhanced over the decades with the advance in detection algorithms, hardware and integration with other tunnel systems. They have become an important safety system in China’s road tunnels

Electroacupuncture could influence the expression of IL-1 β and NLRP3 inflammasome in hippocampus of Alzheimer's disease animal model

Background. Effective therapies for Alzheimer's disease (AD) are still being explored. Electroacupuncture with traditional Chinese medicine theory may improve spatial learning and memory abilities and glucose metabolism rates in an animal model of AD. However, the mechanism of electroacupuncture in intervention of AD is still unclear. According to recent studies of AD mechanisms, the NLRP3 inflammasome regulated the expression of IL-1β in the brain which may mediate AD related processes. Therefore, in our study, we intend to explore the possible relation between electroacupuncture and the expression of NLRP 3 inflammasome in the hippocampus of an AD animal model. Method. In this study, 7.5-month-old male senescence-accelerated mouse prone 8 (SAMP8) mice were used as an AD animal model, which were randomly divided into two groups: Alzheimer's disease model group (AD group) and electroacupuncture group (EA group). In the control paradigm, 7.5-month-old male SAMR1 mice were used as the normal control group (N group). DU20, DU26, and EX-HN3 were selected as the acupuncture points, and after a 15-day treatment of electroacupuncture, we used immunohistochemistry and Western blotting to examine the expression of IL-1β and NLRP3, ASC, and Caspase-1 in the hippocampus of the AD animal model. Results. Compared with N group, IL-1β, NLRP3, ASC, and Caspase-1 positive cells in AD group were increased, and the relative expression of all above proteins significantly increased (P < 0.01). Compared with AD group, the expression of IL-1β, NLRP3, ASC, and Caspase-1 in EA group was significantly decreased (P < 0.01). Conclusion. Electroacupuncture treatment could inhibit the inflammation reaction in the hippocampus of SAMP8 mice. What is more, the possible mechanism of electroacupuncture reduced the expression of IL-1β and NLRP3 inflammasome relative protein

A big data based cost prediction method for remanufacturing end-of-life products

Remanufacturing is considered as an important industrial process to restore the performance and function of End-of-Life (EOL) products to a like-new state. In order to help enterprises effectively and precisely predict the cost of remanufacturing processes, a remanufacturing cost prediction model based on big data is developed. In this paper, a cost analysis framework is established by applying big data technologies to interpret the obtained data, identify the intricate relationship of obtained sensor data and its corresponding remanufacturing processes and associated costs. Then big data mining and particle swarm optimization Back Propagation (BP) neural network algorithm are utilized to implement the cost prediction. The application of presented model is verified by a case study, and the results demonstrates that the developed model can predict the cost of the remanufacturing accurately allowing early decision making for remanufacturability of the EOL products

A Personalized Rolling Optimal Charging Schedule for Plug-In Hybrid Electric Vehicle Based on Statistical Energy Demand Analysis and Heuristic Algorithm

To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs) have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost. Although the next-day electricity prices can be obtained in a day-ahead power market, a driving plan is not easily made in advance. Although PHEV owners can input a next-day plan into a charging system, e.g., aggregators, day-ahead, it is a very trivial task to do everyday. Moreover, the driving plan may not be very accurate. To address this problem, in this paper, we analyze energy demands according to a PHEV owner’s historical driving records and build a personalized statistic driving model. Based on the model and the electricity spot prices, a rolling optimization strategy is proposed to help make a charging decision in the current time slot. On one hand, by employing a heuristic algorithm, the schedule is made according to the situations in the following time slots. On the other hand, however, after the current time slot, the schedule will be remade according to the next tens of time slots. Hence, the schedule is made by a dynamic rolling optimization, but it only decides the charging decision in the current time slot. In this way, the fluctuation of electricity prices and driving routine are both involved in the scheduling. Moreover, it is not necessary for PHEV owners to input a day-ahead driving plan. By the optimization simulation, the results demonstrate that the proposed method is feasible to help owners save charging costs and also meet requirements for driving

A Demand-Supply Cooperative Responding Strategy in Power System with High Renewable Energy Penetration

Industrial demand response (IDR) plays an important role in promoting the utilization of renewable energy (RE) in power systems. However, it will lead to power adjustments on the supply side, which is also a non-negligible factor in affecting RE utilization. To comprehensively analyze this impact while enhancing RE utilization, this paper proposes a power demand-supply cooperative response (PDSCR) strategy based on both day-ahead and intraday time scales. The day-ahead PDSCR determines a long-term scheme for responding to the predictable trends in RE supply. However, this long-term scheme may not be suitable when uncertain RE fluctuations occur on an intraday basis. Regarding intraday PDSCR, we formulate a profit-driven cooperation approach to address the issue of RE fluctuations. In this context, unreasonable profit distributions on the demand-supply side would lead to the conflict of interests and diminish the effectiveness of cooperative responses. To mitigate this issue, we derive multi-individual profit distribution marginal solutions (MIPDMSs) based on satisfactory profit distributions, which can also maximize cooperative profits. Case studies are conducted on an modified IEEE 24-bus system and an actual power system in China. The results verify the effectiveness of the proposed strategy for enhancing RE utilization, via optimizing the coordination of IDR flexibility with generation resources.Comment: Accepted by IEEE Transactions on Control Systems Technolog

The Analysis and Calculation Method of Urban Rail Transit Carrying Capacity Based on Express-Slow Mode

Urban railway transport that connects suburbs and city areas is characterized by uneven temporal and spatial distribution in terms of passenger flow and underutilized carrying capacity. This paper aims to develop methodologies to measure the carrying capacity of the urban railway by introducing a concept of the express-slow mode. We first explore factors influencing the carrying capacity under the express-slow mode and the interactive relationships among these factors. Then we establish seven different scenarios to measure the carrying capacity by considering the ratio of the number of the express trains and the slow trains, the station where overtaking takes place, and the number of overtaking maneuvers. Taking Shanghai Metro Line 16 as an empirical study, the proposed methods to measure the carrying capacity under different express-slow mode are proved to be valid. This paper contributes to the literature by remodifying the traditional methods to measure the carrying capacity when different express-slow modes are applied to improve the carrying capacity of the suburban railway

Unusual cross-shelf transport driven by the changes of wind pattern in a marginal sea

Author Posting. © American Geophysical Union, 2021. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 126(11), (2021): e2021JC017526, https://doi.org/10.1029/2021JC017526.The traditional understanding of the regional circulation in the Northwest Pacific marginal seas is that the Korean Coastal Current flows southward, following the isobaths of 20–50 m. However, an unusual tongue-shaped structure of cold water is observed in satellite SST data in January 2017, indicating a possible offshore spread of cold coastal water into the middle Southern Yellow Sea (SYS). Additional observations, including in situ hydrographic data as well as direct current measurement, also suggest this cross-shelf transport of the Korean Coastal Water in January 2017. Our analysis shows that this flow breaks through the isobaths at ∼37°N, moves southward between 50–75 m, and eventually veers anti-cyclonically at ∼35°N to join the western slope of the SYS. This circulation pattern is further supported by heat budget analysis. Diagnosis of potential vorticity (PV) reveals that the elevated negative PV anomaly imposed by surface wind stress favors this unusual cross-shelf transport. The change of wind pattern, although under a deceasing wind speed condition, plays an important role. This work provides an alternative view of the wintertime circulation pattern and motivates future studies of the variability of the coastal currents over interannual and longer time scales in the SYS.his study was supported by the Shandong Provincial Key Research and Development Program (2019JZZY020713, 2019GHY112057), the National Key Research and Development Program (2016YFC1401406, 2016YFA0600900), the National Natural Science Foundation of China (42076010, 42130403), National Fund Committee-Shandong joint fund (U1706215), the Fundamental Research Funds for the Central Universities (2020042010), and Ocean University of China-Woods Hole Oceanographic Institution Cooperative Research Initiative (24887).2022-05-0