Integrating Space Syntax and Location-Allocation Model for Fire Station Location Planning in a China Mega City

The appropriate planning of infrastructure protects people’s lives and property. Fire stations are an essential part of a city’s infrastructure and they must be precisely located to shorten emergency response times and reduce casualties. Recently, the focus of the city emergency service has shifted from fire suppression to technical rescues. We compared the spatial distribution of fire suppression and technical rescues at a city scale to show the variation in their influences. An integrated road-network accessibility and location-allocation model (RNALA) for the location planning of a fire station was proposed. Specific sites for fire stations were identified using the L-A model. Then, the spatial design network analysis was performed to quantify areas around the selected site with high road network accessibility. The RNALA model was used to extend the selection from a point to a region by introducing road network accessibility to accomplish coverage and efficiency requirements. A quantitative and universal approach that focuses on fire station location planning based on emergency services is proposed. This methodology provides a practical solution for implementation, as a specific identified location might not be available for implementation. These results can serve as a reference for identifying fire station locations in cities

Path Planning System for Smart Cars Used in Education

In this paper, we developed a path planning system for smart cars for teaching electronic engineering or computer science, which consists of the interactive platform for smart cars development and path planning. Designed by Visual C++, the interactive platform can call Matlab engine, allows users to choose path optimization algorithms such as genetic or A-star(A*) algorithm for different tasks and control smart cars through serial ports. The simulation and practice demonstrate that our interactive platform can help learners to plan paths and control intelligent vehicles without specially designing a user interface.Peer reviewe

Intelligent real-time scheduling of water supply network based on deep learning

Inappropriate scheduling plans can result in additional economic losses and the safety of water distribution network (WDN). Optimizing manual experience based scheduling plans can help water utilities rationally allocate water plants and pump stations, ensuring the safety, stability, and economy of the water supply system. However, there is a lack of real-time, rational, and optimized scheduling methods. To address this, we proposed a novel intelligent scheduling framework based on deep learning. In this framework, two neural network models, multi-heads convolutional gated recurrent unit network (MH-CGRU) and multi-head gated recurrent unit network (MH-GRU), can effectively extract key features from the WDNs. Operating data were used as decision variables to predict and generate scheduling orders for water plants and pump stations, respectively. The rationality of the orders is verified by combining a high precision online hydraulic model and the evaluation of the operational status of the WDNs. This system has been deployed in a real WDN and put into practical application. From June to November of 2022, the total adoption rate of all orders reached 96.29%, with the average deviation between predicted and actual control targets being less than 5%, and energy consumption decreased by 3.05% compared to the previous year. HIGHLIGHTS Proposed an optimized, real-time, and secure intelligent control method for water supply networks based on deep learning algorithms.; Presented a data evaluation approach for selecting high-quality samples from monitoring data in the water supply system.; Developed an intelligent verification mechanism that combines a high-precision hydraulic model with scheduling orders for improved control reliability.

Constructing Hierarchically Porous Nestlike Al2O3-MnO2@Diatomite Composite with High Specific Surface Area for Efficient Phosphate Removal

In this work, Al2O3-MnO2@diatomite composite (AM-Dt) was prepared by a simple hydrothermal method. This composite was formed by using diatomite as a porous substrate to support Al2O3 and MnO, nanoparticles. It exhibited hierarchically porous structures and a high specific surface area (352 m(2)/g). The maximum phosphate adsorption capacity of AM-Dt was 63.7 mg of P/g of (Al2O3-MnO2), which is 6 times greater than those of Al2O3 coated diatomite, Al2O3, and Al2O3-MnO2. The composite also showed superior adsorption efficiency, high structural stability, and selectivity for phosphate in the presence of interfering anions (Cl-, NO3-, and CO32-). With the help of X-ray photoelectron spectroscopy and P K-edge X-ray absorption nearedge structure analysis, it can be concluded that electrostatic attraction and formation of surface complexes via phosphate bonding with Al2O3 and MnO2 were the main adsorption mechanisms. The facile preparation method, excellent adsorption performance, and cost effectiveness suggested that this composite possesses a promising potential for phosphate removal from contaminated water

Monitoring seasonal distribution of an endangered anadromous sturgeon in a large river using environmental DNA

Monitoring dynamic distribution is crucial to conservation management of anadromous sturgeons, but traditional survey methods are less efficient for low-density populations in a large river. Natural propagation of Chinese sturgeon has been monitored annually mainly at the spawning ground using netting for eggs and hydroacoustics for broodstock. However, absence of spawning was observed sporadically in recent years, indicating further crises for the declining population. We analyzed eDNA of water samples collected from 24 sites across 1360 km of the migratory route of anadromous Chinese sturgeon in the middle and lower reaches of the Yangtze River. Chinese sturgeon was detected at 9 sites during the spawning season and 14 sites after the spawning season. We found that positive eDNA detection rates remained constant in the middle reaches but dramatically changed in the lower reaches, reflecting seasonal migration pattern of Chinese sturgeon. Invasive sturgeons were detected in the river, indicating their possible escape from aquaculture facilities. This study established a protocol for the use of eDNA to monitor distribution of Chinese sturgeon and could be valuable in making better policies for the conservation of this endangered species

Health-status outcomes with invasive or conservative care in coronary disease

BACKGROUND In the ISCHEMIA trial, an invasive strategy with angiographic assessment and revascularization did not reduce clinical events among patients with stable ischemic heart disease and moderate or severe ischemia. A secondary objective of the trial was to assess angina-related health status among these patients. METHODS We assessed angina-related symptoms, function, and quality of life with the Seattle Angina Questionnaire (SAQ) at randomization, at months 1.5, 3, and 6, and every 6 months thereafter in participants who had been randomly assigned to an invasive treatment strategy (2295 participants) or a conservative strategy (2322). Mixed-effects cumulative probability models within a Bayesian framework were used to estimate differences between the treatment groups. The primary outcome of this health-status analysis was the SAQ summary score (scores range from 0 to 100, with higher scores indicating better health status). All analyses were performed in the overall population and according to baseline angina frequency. RESULTS At baseline, 35% of patients reported having no angina in the previous month. SAQ summary scores increased in both treatment groups, with increases at 3, 12, and 36 months that were 4.1 points (95% credible interval, 3.2 to 5.0), 4.2 points (95% credible interval, 3.3 to 5.1), and 2.9 points (95% credible interval, 2.2 to 3.7) higher with the invasive strategy than with the conservative strategy. Differences were larger among participants who had more frequent angina at baseline (8.5 vs. 0.1 points at 3 months and 5.3 vs. 1.2 points at 36 months among participants with daily or weekly angina as compared with no angina). CONCLUSIONS In the overall trial population with moderate or severe ischemia, which included 35% of participants without angina at baseline, patients randomly assigned to the invasive strategy had greater improvement in angina-related health status than those assigned to the conservative strategy. The modest mean differences favoring the invasive strategy in the overall group reflected minimal differences among asymptomatic patients and larger differences among patients who had had angina at baseline