Exploration of Detailed Planning Practice of Chemical Industrial Parks under the Background of Territorial Space Planning

With the gradual completion of the overall planning of city and county land space,the detailed planning will be prepared according to the requirements of transmitting and refining the upper planning.Industrial parks are one of the“main forces”of local economic development,and the preparation of their detailed planning will escort their development.The key points of the Control Indicators of Construction Land in Industrial Projectsissued in 2008 and 2023 were compared,and the new requirements for detailed planning under the background of territorial space and the contradictions between the detailed planning of industrial parks and the overall planning of the upper territorial space were sorted out based on the summary of the existing problems in the development of chemical parks.It provides some ideas for the practice of detailed planning of chemical industrial parks under the background of territorial space.

Research on Key Points of Design of Standard Plants in Modern Industrial Parks Under the Background of Promoting the Development of New Quality Productive Forces

With the progress of science and technology and the acceleration of industrialization,the modern industrial park is an important carrier of industrial development.The importance of its standard plant design has become increasingly prominent.With the development of new quality productive forces as the background,this research deeply discusses the key points of standard plant design in modern industrial parks.This paper uses literature review and case analysis to systematically analyze the important role of standard plant design in developing new quality productive forces in modern industrial parks and puts forward suggestions for optimizing design.It is found that the rationality,intelligence,and environmental protection of plant design are the key factors affecting the development of new quality productive forces.The paper summarizes the core points of modern industrial park standard plant design to provide a reference for the future development of related industries.

Analysis and Suggestions on Management Strategies in Eco-industrial Parks in China

In the research, management strategies and problems of eco-industrial parks were mainly analyzed and some suggestions were proposed based on eco-industrial park, circular economy and ecologization of industrial park in China, providing references for ecologicalization policy design of industrial parks in China.

The situation and development trend of health industrial park construction in China

[目的] 描述我国健康产业园区基本现状,总结园区发展模式,为园区未来发展提供理论基础. [方法]利用百度搜索、CNKI和万方数据库全面搜索国内健康产业园区的相关信息和文献资料,基于文献内容 分析法和案例分析法对园区信息进行归纳与分析.[结果]共检索到健康产业园区3 5 个,涉及 1 8个省市,最 早的园区于1994年创办,园区平均面积为16.82 km2,平均投资金额为140.9亿元.从管理运营、投融资、产 业类型、研发方面归纳了园区的不同发展模式,发现园区建设中的问题并提出未来发展趋势.[结 论 ]我国健 康产业园区正在蓬勃发展,但是仍然存在重复建设缺乏特色,监管机制尚不完善等问题,还需政府进-步完善 审批、优惠等政策,引导园区健康发展.

Path Planning and Tracking Control for Parking via Soft Actor-Critic Under Non-Ideal Scenarios

Parking in a small parking lot within limited space poses a difficult task. It often leads to deviations between the final parking posture and the target posture. These deviations can lead to partial occupancy of adjacent parking lots, which poses a safety threat to vehicles parked in these parking lots. However, previous studies have not addressed this issue. In this paper, we aim to evaluate the impact of parking deviation of existing vehicles next to the target parking lot(PDEVNTPL) on the automatic ego vehicle(AEV) parking, in terms of safety, comfort, accuracy, and efficiency of parking. A segmented parking training framework(SPTF) based on soft actor-critic(SAC) is proposed to improve parking performance. In the proposed method, the SAC algorithm incorporates strategy entropy into the objective function, to enable the AEV to learn parking strategies based on a more comprehensive understanding of the environment. Additionally, the SPTF simplifies complex parking tasks to maintain the high performance of deep reinforcement learning(DRL). The experimental results reveal that the PDEVNTPL has a detrimental influence on the AEV parking in terms of safety, accuracy, and comfort, leading to reductions of more than 27%, 54%, and 26%respectively. However, the SAC-based SPTF effectively mitigates this impact, resulting in a considerable increase in the parking success rate from 71% to 93%. Furthermore, the heading angle deviation is significantly reduced from 2.25 degrees to 0.43degrees.

Dysfunction of synaptic endocytic trafficking in Parkinson's disease

Parkinson's disease is characterized by the selective degeneration of dopamine neurons in the nigrostriatal pathway and dopamine deficiency in the striatum.The precise reasons behind the specific degeneration of these dopamine neurons remain largely elusive.Genetic investigations have identified over 20 causative PARK genes and 90 genomic risk loci associated with both familial and sporadic Parkinson's disease.Notably,several of these genes are linked to the synaptic vesicle recycling process,particularly the clathrinmediated endocytosis pathway.This suggests that impaired synaptic vesicle recycling might represent an early feature of Parkinson's disease,followed by axonal degeneration and the eventual loss of dopamine cell bodies in the midbrain via a"dying back"mechanism.Recently,several new animal and cellular models with Parkinson's disease-linked mutations affecting the endocytic pathway have been created and extensively characterized.These models faithfully recapitulate certain Parkinson's disease-like features at the animal,circuit,and cellular levels,and exhibit defects in synaptic membrane trafficking,further supporting the findings from human genetics and clinical studies.In this review,we will first summarize the cellular and molecular findings from the models of two Parkinson's disease-linked clathrin uncoating proteins:auxilin(DNAJC6/PARK19)and synaptojanin 1(SYNJ1/PARK20).The mouse models carrying these two PARK gene mutations phenocopy each other with specific dopamine terminal pathology and display a potent synergistic effect.Subsequently,we will delve into the involvement of several clathrin-mediated endocytosis-related proteins(GAK,endophilin A1,SAC2/INPP5 F,synaptotagmin-11),identified as Parkinson's disease risk factors through genome-wide association studies,in Parkinson's disease pathogenesis.We will also explore the direct or indirect roles of some common Parkinson's disease-linked proteins(alpha-synuclein(PARK1/4),Parkin(PARK2),and LRRK2(PARK8))in synaptic endocytic trafficking.Additionally,we will discuss the emerging novel functions of these endocytic proteins in downstream membrane traffic pathways,particularly autophagy.Given that synaptic dysfunction is considered as an early event in Parkinson's disease,a deeper understanding of the cellular mechanisms underlying synaptic vesicle endocytic trafficking may unveil novel to rgets for early diagnosis and the development of interventional therapies for Parkinson's disease.Future research should aim to elucidate why generalized synaptic endocytic dysfunction leads to the selective degeneration of nigrostriatal dopamine neurons in Parkinson's disease.

Study on the Landscape Flavor of Suzhou Industrial Park

The creation of new urban landscape environment is one of the core problems to inherit the urban history and culture and to form its character.By analyzing the landscape nodes around the Jinji Lake in Suzhou Industrial Park,this research sums up its natural landscape flavor created by water resource,the art landscape flavor created by buildings' layout,and the vivid culture flavor of urban landscape.The combination of the park's landscape creation and its nature,art and culture completely describes the feature of Jinji Lake Industrial Park-the fusion of history and fashion,classical garden and western garden,natural landscape and man-made landscape.

Smart Parking Management System “MOTAH”

With a surge in the university’s student and staff population, parking problems and congestion have rapidly intensified. The recent inclusion of women drivers, particularly during official working hours, has exacerbated these challenges. This pressing issue underscores the critical necessity for a structured approach to managing university entries and overseeing parking at the gates. The proposed smart parking management system aims to address these concerns by introducing a design concept that restricts unauthorized access and provides exclusive parking privileges to authorized users. Through image processing, the system identifies available parking spaces, relaying real-time information to users via a mobile application. This comprehensive solution also generates detailed reports (daily, weekly, and monthly), aiding university safety authorities in future gate management decisions.

基于障碍物和车位检测的单阶段多任务YOLO-Parking算法研究

文章提出一种基于YOLOv4的端到端多任务网络模型用于自动泊车系统中的感知任务,以环视图像(around view monitor, AVM)作为网络输入,基于卷积网络提取图像特征信息,通过YOLO和DMPR-PS(directional marking-point regression-parking slot)检测头实现停车位与障碍物并行检测。在PS 2.0公开数据集上进行验证的结果表明,所提出的多任务检测方法能够同时检测停车位和障碍物,障碍物识别平均精度均值达到89.72%,车位识别查准率达到93.53%,网络检测速率为34.0帧/s,在满足自动泊车感知任务需求的同时提升了系统的检测效率。该文研究成果对自动泊车感知技术的发展具有一定的意义。

FACTORS AFFECTING FORMATION AND DEVELOPMENT OF THE URBAN INDUSTRIAL DISTRICT IN CHINA──A Case Study on Caohejing Hi-Tech Park in Shanghai

In China,the urban industrial district is usually an organic concentrated district including many factories that are in big,middle or small size,and are coordinated in the process of production,or use infrastructure in common.The formation and development of the urban industrial district in China are affected by not only general factors such as natural factor,transportation factor,labour factor,ecologic factor,but also special factors such as agglomeration factor,technologic factor and social factor.To the district’s formation, both the social factors and natural factors are important,especially the attitude the government have towards the district and the regional natural condition.But the agglomeration, market and transportation costs here are not as important as those in the traditional Industrial Location Theory.Now we must pay great attention to these three factors owing to the new economic conditions in China.In the development of the district,the main factors are technology and agglomeration.This indicates that the technologic factor is gradually the essential condition in the development of the district.Besides,we must also know the affection of the eclologic factor in the development of the district.According to the reality of Caohejing district,this paper gives every factor mark in the Analytic Hierarchy Process(AHP).With the result of the AHP,some suggestions have been put forward to Caohejing Hi-Tech Park and other urban industrial districts as well.

Terrain or climate factor dominates vegetation resilience?Evidence from three national parks across different climatic zones in China

Vegetation resilience(VR),providing an objective measure of ecosystem health,has received considerable attention,however,there is still limited understanding of whether the dominant factors differ across different climate zones.We took the three national parks(Hainan Tropical Rainforest National Park,HTR;Wuyishan National Park,WYS;and Northeast Tiger and Leopard National Park,NTL)of China with less human interference as cases,which are distributed in different climatic zones,including tropical,subtropical and temperate monsoon climates,respectively.Then,we employed the probabilistic decay method to explore the spatio-temporal changes in the VR and their natural driving patterns using Geographically Weighted Regression(GWR)model as well.The results revealed that:(1)from 2000 to 2020,the Normalized Difference Vegetation Index(NDVI)of the three national parks fluctuated between 0.800 and 0.960,exhibiting an overall upward trend,with the mean NDVI of NTL(0.923)>HTR(0.899)>WYS(0.823);(2)the positive trend decay time of vegetation exceeded that of negative trend,indicating vegetation gradual recovery of the three national parks since 2012;(3)the VR of HTR was primarily influenced by elevation,aspect,average annual temperature change(AATC),and average annual precipitation change(AAPC);the WYS'VR was mainly affected by elevation,average annual precipitation(AAP),and AAPC;while the terrain factors(elevation and slope)were the main driving factors of VR in NTL;(4)among the main factors influencing the VR changes,the AAPC had the highest proportion in HTR(66.7%),and the AAP occupied the largest area proportion in WYS(80.4%).While in NTL,elevation served as the main driving factor for the VR,encompassing 64.2%of its area.Consequently,our findings indicated that precipitation factors were the main driving force for the VR changes in HTR and WYS national parks,while elevation was the main factors that drove the VR in NTL.Our research has promoted a deeper understanding of the driving mechanism behind the VR.

Optimal scheduling of zero-carbon park considering variational characteristics of hydrogen energy storage systems

Zero-carbon parks have broad prospects in carbon neutralization.As an energy hub,hydrogen energy storage plays an important role in zero-carbon parks.However,the nonlinear characteristics of hydrogen energy storage systems(HESSs)have a significant impact on the system economy.Therefore,considering the variable working condition characteristics of HESSs,a hybrid operation method is proposed for HESS,to support the efficient and economic operation of zero-carbon parks,By analyzing the operating principle of a zero-carbon park with HESS,the system structure framework and variable condition linearization model of the equipment in HESS are established.Moreover,considering the energy output characteristics of hydrogen energy storage equipment under variable working conditions,a multimodule hybrid operation strategy is proposed for electrolytic and fuel cells,effectively meeting the thermoelectric load demand of zero-carbon parks in different scenarios.Finally,the economy of the proposed hybrid operation strategy was verified in typical scenarios,using a zero-carbon park embedded with a HESS.

Low-Density Microplastics in Recreational Parks of Al Ain, United Arab Emirates: Abundance, Composition, and Potential Effects on Soil Health

Microplastics (MPs) have been an emerging concern due to their harmful effects on the ecosystem and are ubiquitous in various habitats, from marine to terrestrial environments. However, studies on the presence of MPs in recreational areas are limited. One of the previous works has reported that urban recreational parks are considered “sinks” for plastic debris, including MPs. In this study, low-density MPs (LD-MPs) in soil samples collected from recreational parks of Al Ain, United Arab Emirates (UAE) were isolated by density flotation method. Results showed that these parks have varying levels of LD-MPs caused by various anthropogenic activities, such as sludge use and application of reclaimed water from wastewater treatment facilities in those areas. These plastic particles were isolated in 87% of the soil samples, with an average concentration of 1550 ± 340 MPs/kg. Predominantly, these comprised large LD-MPs (300 - 5000 μm), with red and blue being the most common colors. Fourier transform infrared (FTIR) spectroscopy identified possible synthetic polymers, including polyethylene and polypropylene. Additionally, a negative correlation was observed between LD-MP concentration and soil pH and moisture content, indicating potential adverse effects on soil health. These findings highlight the need for monitoring and managing microplastic pollution in urban recreational areas to mitigate its ecological impacts.

Influence of Human Activity Intensity on Habitat Quality in Hainan Tropical Rainforest National Park,China

Due to long-term human activity interference,the Hainan Tropical Rainforest National Park(HTRNP)of China has experienced ecological problems such as habitat fragmentation and biodiversity loss,and with the expanding scope and intensity of human activity impact,the regional ecological security is facing serious challenges.A scientific assessment of the interrelationship between human activity intensity and habitat quality in the HTRNP is a prerequisite for achieving effective management of ecological disturbances caused by human activities and can also provide scientific strategies for the sustainable development of the region.Based on the land use change data in 2000,2010,and 2020,the spatial and temporal variations and the relationship between habitat quality(HQ)and human activity intensity(HAI)in the HTRNP were explored using the integrated valuation of ecosystem services and trade-offs(InVEST)model.System dynamics and land use simulation models were also combined to conduct multi-scenario simulations of their relationships.The results showed that during 2000–2020,the habitat quality of the HTRNP improved,the intensity of human activities decreased each year,and there was a negative correlation between the two.Second,the system dynamic model could be well coupled with the land use simulation model by combining socio-economic and natural factors.The simulation scenarios of the coupling model showed that the harmonious development(HD)scenario is effective in curbing the increasing trend of human activity intensity and decreasing trend of habitat quality,with a weaker trade-off between the two compared with the baseline development(BD)and investment priority oriented(IPO)scenarios.To maintain the authenticity and integrity of the HTRNP,effective measures such as ecological corridor construction,ecological restoration,and the implementation of ecological compensation policies need to be strengthened.

Application of Connected Truck Data to Evaluate Spatiotemporal Impact of Rest Area Closures on Ramp Parking

Ensuring adequate access to truck parking is critical to the safe and efficient movement of freight traffic. There are strict federal guidelines for commercial truck driver rest periods. Rest areas and private truck stops are the only places for the trucks to stop legally and safely. In locations without sufficient parking areas, trucks often park on interstate ramps, which create safety risks for other interstate motorists. Historically, agencies have employed costly and time intensive manual counting methods, camera surveillance, and driver surveys to assess truck parking. Connected truck data, available in near real-time, offers an efficient alternative to practitioners to assess truck parking patterns and identify areas where there may be insufficient safe parking spaces. This paper presents a case study of interstate I-70 in east central Indiana and documents the observed spatiotemporal impacts of a rest area closure on truck parking on nearby interstate ramps. Results showed that there was a 28% increase in parking on ramps during the rest area closure. Analysis also found that ramps closest to the rest area were most impacted by the closure, seeing a rise in truck parking sessions as high as 2.7 times. Parking duration on the ramps during rest area closure also increased drastically. Although it was expected that this would result in increased parking by trucks on adjacent ramps, this before, during, after scenario provided an ideal scenario to evaluate the robustness of these techniques to assess changing parking characteristics of long-haul commercial trucks. The data analytics and visualization tools presented in this study are scalable nationwide and will aid stakeholders in informed data-driven decision making when allocating resources towards improving the nations commercial vehicle parking infrastructure.

Exploring impacts of COVID-19 on spatial and temporal patterns of visitors to Canadian Rocky Mountain National Parks from social media big data

COVID-19 posed challenges for global tourism management.Changes in visitor temporal and spatial patterns and their associated determinants pre-and peri-pandemic in Canadian Rocky Mountain National Parks are analyzed.Data was collected through social media programming and analyzed using spatiotemporal analysis and a geographically weighted regression(GWR)model.Results highlight that COVID-19 significantly changed park visitation patterns.Visitors tended to explore more remote areas peri-pandemic.The GWR model also indicated distance to nearby trails was a significant influence on visitor density.Our results indicate that the pandemic influenced tourism temporal and spatial imbalance.This research presents a novel approach using combined social media big data which can be extended to the field of tourism management,and has important implications to manage visitor patterns and to allocate resources efficiently to satisfy multiple objectives of park management.

Path Tracking Controller Design of Automated Parking Systems via NMPC with an Instructible Solution

Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future.

Spatial-temporal Patterns of Urban Parks’Effects on the Sentiments and Their Associated Factors Based on Social Media Data——a Case Study in Beijing

As the pivotal green space,urban parks play an important role in urban residents’daily activities.Thy can not only bring people physical health,but also can be more likely to elicit positive sentiment to those who visit them.Recently,social media big data has provided new data sources for sentiment analysis.However,there was limited researches that explored the connection between urban parks and individual’s sentiments.Therefore,this study firstly employed a pre-trained language model(BERT,Bidirectional Encoder Representations from Transformers)to calculate sentiment scores based on social media data.Secondly,this study analysed the relationship between urban parks and individual’s sentiment from both spatial and temporal perspectives.Finally,by utilizing structural equation model(SEM),we identified 13 factors and analyzed its degree of the influence.The research findings are listed as below:①It confirmed that individuals generally experienced positive sentiment with high sentiment scores in the majority of urban parks;②The urban park type showed an influence on sentiment scores.In this study,higher sentiment scores observed in Eco-parks,comprehensive parks,and historical parks;③The urban parks level showed low impact on sentiment scores.With distinctions observed mainly at level-3 and level-4;④Compared to internal factors in parks,the external infrastructure surround them exerted more significant impact on sentiment scores.For instance,number of bus and subway stations around urban parks led to higher sentiment scores,while scenic spots and restaurants had inverse result.This study provided a novel method to quantify the services of various urban parks,which can be served as inspiration for similar studies in other cities and countries,enhancing their park planning and management strategies.

Determinants of COVID-19 Face Mask Litter in Coastal Urban Parking Lots: Implications for Source Modelling of Potential Microplastic Pollution

Despite cities being recognized as being potential sources of microplastic pollution to the wider environment, most surveys of COVID-19 plastic-based litter have been undertaken through linear transects of marine beaches. For the far fewer number of studies conducted on inland and urban locations, the site-specific focus has primarily been surveys along the length of streets. The present study is the first to specifically assess the standing stock (i.e., moment-in-time) of littered face masks for the entire surface area of urban parking lots. The density of face masks in 50 parking lots in a Canadian coastal town (0.00054 m2 ± 0.00051 m2) was found to be significantly greater than the background level of littering of town streets. Face mask density was significantly related to visitation “usage” of parking lots as gauged by the areal size of the lots and of their onsite buildings, as well as the number of vehicles present. Neither parking lot typology nor estimates of inferred export (various measures of wind exposure) and entrapment (various metrics of obstruction) of face masks had a significant influence on the extent of whole-lot littering. In consequence, modelling of the potential input of mask-derived microplastics to the marine environment from coastal communities can use the areal density of face masks found here in association with the total surface area of lots for individual municipalities as determined through GIS analysis.

Collision-free parking recommendation based on multi-agent reinforcement learning in vehicular crowdsensing

The recent proliferation of Fifth-Generation(5G)networks and Sixth-Generation(6G)networks has given rise to Vehicular Crowd Sensing(VCS)systems which solve parking collisions by effectively incentivizing vehicle participation.However,instead of being an isolated module,the incentive mechanism usually interacts with other modules.Based on this,we capture this synergy and propose a Collision-free Parking Recommendation(CPR),a novel VCS system framework that integrates an incentive mechanism,a non-cooperative VCS game,and a multi-agent reinforcement learning algorithm,to derive an optimal parking strategy in real time.Specifically,we utilize an LSTM method to predict parking areas roughly for recommendations accurately.Its incentive mechanism is designed to motivate vehicle participation by considering dynamically priced parking tasks and social network effects.In order to cope with stochastic parking collisions,its non-cooperative VCS game further analyzes the uncertain interactions between vehicles in parking decision-making.Then its multi-agent reinforcement learning algorithm models the VCS campaign as a multi-agent Markov decision process that not only derives the optimal collision-free parking strategy for each vehicle independently,but also proves that the optimal parking strategy for each vehicle is Pareto-optimal.Finally,numerical results demonstrate that CPR can accomplish parking tasks at a 99.7%accuracy compared with other baselines,efficiently recommending parking spaces.