Investigation and Analysis of Main Diseases of Landscape Plants in the Main Urban Area of Lu'an City

To figure out the disease occurrence of landscape plants in the main urban area of Lu'an City,the author investigated the disease occurrence of landscape plants in park green space,residential green space,unit attached green space and main road in the area under administration.The survey results showed that there were 29 species of urban landscape plant diseases,mainly powdery mildew and spot diseases.According to the characteristics of the diseases,the causes and problems of the diseases were analyzed,and the corresponding prevention and control measures were put forward.

文旅融合:“Citywalk”热潮下的冷思考

“Citywalk”(城市漫步)强调慢节奏和沉浸式体验,是深受年轻人追捧的文旅消费新范式。“Citywalk”火爆出圈的背后,也存在着产品辨识度不高、利润低、专业性不强、产品更迭慢等问题。“文旅融合”的有效健康发展,需要在资源供给、产品创新、服务品质等方面开展全方位、多领域的合作联动,成果共享才能形成互利共赢新格局。

物质循环视角下的“可持续漂浮城市”解析——以BIG事务所“Oceanix City”方案为例

随着时代发展,现代城市正面临着土地短缺、住房紧张、能源枯竭以及海平面上升等一系列问题。因而探索陆地之外的生存空间,进而缓解多种城市问题是人们长久以来的愿景。近年来,联合国人居署提出可持续发展的漂浮城市概念,并由BIG事务所设计了世界上第一个弹性化和可持续的漂浮城市原型——Oceanix City。该城市通过引入城市农业,配置能量、水分、养分等循环系统实现最大限度自给自足,满足居民日常生活需求,达到可持续发展的目标。文章运用文献研究法梳理了从漂浮建筑、漂浮社区到漂浮城市的发展历程,并以“Oceanix City”方案为案例分析对象,从物质循环视角入手解析方案的规划设计与建造、循环系统的运作等方面,总结得出拓展海上空间、引入城市农业并构建物质循环系统是应对上述城市问题的有效方式,以期为未来城市的可持续发展提供启示。

Between the City and Images:An Analysis of Mainstream Media’s Paths of Constructing the Cultural Memory of a City:Taking Chengdu Radio and Television’s“Hi Chengdu”as an Example

Mainstream media play a crucial role in constructing the cultural memory of a city.This study used 319 short videos released by“Hi Chengdu,”a new media product of Chengdu Radio and Television,as samples.Based on the grounded theory,a research framework encompassing“content,technology,and discourse”was established to explore the paths through which mainstream media construct the cultural memory.Regarding content,this paper emphasized temporal and spatial contexts and urban spaces,delving deep into the themes of the cultural memory and vehicles for it.In terms of technology,this paper discussed the practice of leveraging audio/visual-mode discourse to stitch together the impressions of a city and evoke emotional resonance to create a“flow”of memory.As for discourse,this paper looked at the performance of a communication ritual to frame concepts and shape urban identity.It is essential to break free from conventional thinking and leverage local culture as the primary driving force to further boost a city’s productivity,in order to excel in cultural communication.

Development of a Lightweight Model for Handwritten Dataset Recognition: Bangladeshi City Names in Bangla Script

The context of recognizing handwritten city names,this research addresses the challenges posed by the manual inscription of Bangladeshi city names in the Bangla script.In today’s technology-driven era,where precise tools for reading handwritten text are essential,this study focuses on leveraging deep learning to understand the intricacies of Bangla handwriting.The existing dearth of dedicated datasets has impeded the progress of Bangla handwritten city name recognition systems,particularly in critical areas such as postal automation and document processing.Notably,no prior research has specifically targeted the unique needs of Bangla handwritten city name recognition.To bridge this gap,the study collects real-world images from diverse sources to construct a comprehensive dataset for Bangla Hand Written City name recognition.The emphasis on practical data for system training enhances accuracy.The research further conducts a comparative analysis,pitting state-of-the-art(SOTA)deep learning models,including EfficientNetB0,VGG16,ResNet50,DenseNet201,InceptionV3,and Xception,against a custom Convolutional Neural Networks(CNN)model named“Our CNN.”The results showcase the superior performance of“Our CNN,”with a test accuracy of 99.97% and an outstanding F1 score of 99.95%.These metrics underscore its potential for automating city name recognition,particularly in postal services.The study concludes by highlighting the significance of meticulous dataset curation and the promising outlook for custom CNN architectures.It encourages future research avenues,including dataset expansion,algorithm refinement,exploration of recurrent neural networks and attention mechanisms,real-world deployment of models,and extension to other regional languages and scripts.These recommendations offer exciting possibilities for advancing the field of handwritten recognition technology and hold practical implications for enhancing global postal services.

Grid System Analysis of Urban Flora of Bukhara City (Uzbekistan)

This article presents information on the study of the flora of Uzbekistan based on grid system mapping. The urban flora of the city of Bukhara was researched in it. As a result of research, the territory of Bukhara city was divided into 85 indexes based on 1 × 1 km2 grid mapping system. The diversity and density of species in the indexes are determined. The influence of anthropogenic factors on the diversity of species in the indexes is determined.

Geospatial Technology Integration in Smart City Frameworks for Achieving Climate Neutrality by 2050: A Case Study of Limassol Municipality, Cyprus

This study investigated the integration of geospatial technologies within smart city frameworks to achieve the European Union’s climate neutrality goals by 2050. Focusing on rapid urbanization and escalating climate challenges, the research analyzed how smart city frameworks, aligned with climate neutrality objectives, leverage geospatial technologies for urban planning and climate action. The study included case studies from three leading European cities, extracting lessons and best practices in implementing Climate City Contracts across sectors like energy, transport, and waste management. These insights highlighted the essential role of EU and national authorities in providing technical, regulatory, and financial support. Additionally, the paper presented the application of a WEBGIS platform in Limassol Municipality, Cyprus, demonstrating citizen engagement and acceptance of the proposed geospatial framework. Concluding with recommendations for future research, the study contributed significant insights into the advancement of urban sustainability and the effectiveness of geospatial technologies in smart city initiatives for combating climate change.

An Enhanced Multiview Transformer for Population Density Estimation Using Cellular Mobility Data in Smart City

This paper addresses the problem of predicting population density leveraging cellular station data.As wireless communication devices are commonly used,cellular station data has become integral for estimating population figures and studying their movement,thereby implying significant contributions to urban planning.However,existing research grapples with issues pertinent to preprocessing base station data and the modeling of population prediction.To address this,we propose methodologies for preprocessing cellular station data to eliminate any irregular or redundant data.The preprocessing reveals a distinct cyclical characteristic and high-frequency variation in population shift.Further,we devise a multi-view enhancement model grounded on the Transformer(MVformer),targeting the improvement of the accuracy of extended time-series population predictions.Comparative experiments,conducted on the above-mentioned population dataset using four alternate Transformer-based models,indicate that our proposedMVformer model enhances prediction accuracy by approximately 30%for both univariate and multivariate time-series prediction assignments.The performance of this model in tasks pertaining to population prediction exhibits commendable results.

An Analysis of the Lifestyle and Mental Health Status of Adult People Living in Dhaka City: A Cross-Sectional Study in Post COVID-19 Era

Introduction: The Novel Coronavirus or COVID-19 affected all the megacities of the world and made the mental health and lifestyle of people paralyzed. According to different studies, such difficulties were different in scale in different cities depending on the demographic attributes of the people. This phenomenon has created the essence of the current study to examine the health conditions in terms of their mental health, lifestyle, and demographic attributes during and immediate past of the COVID-19 era. Method: It was a cross-sectional study covering the people of Dhaka City Corporation. For this purpose, a multistage sampling method was applied, under which the respondents were selected randomly and a self-administered structured questionnaire was used to collect data. The questionnaire was developed based on the DASS 21, as it was suitable to measure the components of mental health in the form of depression, anxiety, and stress. Descriptive analysis and cross-tabulation were applied to find out the association between dependent and independent variables, whereas, a chi-square test was performed to examine the hypothesis. Finally, multivariate analysis was done to find out the risk factors. Three logistic regression models were developed for three dependent variables. Result: The findings of the analysis revealed that the lifestyle of people had severely influenced the components of their mental health conditions during and immediate past of COVID-19 in the Dhaka City Corporation, which varies to some extent depending on the demographic attributes of those. Conclusion: The above findings are statistically significant enough to conclude about the essence of taking preventive measures regarding mental health issues in the future. However, the limitations of this study-keeping it within the urban areas and the educated people, have also created the venue for future researchers to move with their research endeavors in the rural areas nationwide and thus generalize the results.

Assessment of Breast Cancer Prevention Practices among Women Attending Primary Health Care in Abha City, Aseer Region, Saudi Arabia

Cancer is a leading cause of death worldwide, with breast cancer being the most common (2.26 million new cases and 685,000 deaths). In Saudi Arabia, breast cancer ranked the first among females in 2014, accounting for 15.9% of all cancers reported among Saudi nationals and 28.7% of all cancers reported among females of all ages. Early detection of breast cancer could decrease the risks, have a better prognosis, and have better outcomes/more successful treatments. Prevalence of breast cancer reached more than 25% of all diagnosed cancer in the kingdom among women. Aim: This study aims to assess the knowledge and performance of women attending primary care centers about breast self-examination and mammogram screening for prevention and early detection of breast cancer in Abha city primary healthcare centers, Kingdom of Saudi Arabia. Research Method: cross sectional design was conducted by using questionnaire, which was distributed to primary care center nurses. The collected data was statistically analyzed using the Statistical Package for Social Sciences, version 25. Results: The study found that participants had poor awareness and knowledge about breast self-examination, risk factors for breast cancer, and trends and practices in early diagnosis of breast cancer. Conclusion and Recommendations: It recommends increasing awareness campaigns and providing educational programs to improve knowledge and practices.

The Contribution of AI-Powered Mobile Apps to Smart City Ecosystems

In the groundbreaking study “The Contribution of AI-powered Mobile Apps to Smart City Ecosystems,” authored by Zaki Ali Bayashot, the transformative role of artificial intelligence (AI) in urban development is meticulously examined. This comprehensive research delineates the multifaceted ways in which AI-powered mobile applications can significantly enhance the efficiency, sustainability, and livability of urban environments, marking a pivotal step towards the realization of smart cities globally. Bayashot meticulously outlines the critical areas where AI-powered apps offer unprecedented advantages, including urban mobility, public safety, energy management, and environmental monitoring. By leveraging AI’s capabilities, these applications not only streamline city operations but also foster a more sustainable interaction between city dwellers and their environment. The paper emphasizes the importance of data-driven decision-making in urban planning, showcasing how AI analytics can predict and mitigate traffic congestion, optimize energy consumption, and enhance emergency response strategies. The author also explores the social implications of AI in urban settings, highlighting the potential for these technologies to bridge the gap between government entities and citizens. Through engaging case studies, Bayashot demonstrates how participatory governance models, enabled by AI apps, can promote transparency, accountability, and citizen engagement in urban management. A significant contribution of this research is its focus on the challenges and opportunities presented by the integration of AI into smart city ecosystems. Bayashot discusses the technical, ethical, and privacy concerns associated with AI applications, advocating for a balanced approach that ensures technological advancements do not come at the expense of civil liberties. The study calls for robust regulatory frameworks to govern the use of AI in public spaces, emphasizing the need for ethical AI practices that respect privacy and promote inclusivity. Furthermore, Bayashot’s research underscores the necessity of cross-disciplinary collaboration in the development and implementation of AI technologies in urban contexts. By bringing together experts from information technology, urban planning, environmental science, and social sciences, the author argues for a holistic approach to smart city development. This interdisciplinary strategy ensures that AI applications are not only technologically sound but also socially and environmentally responsible. The paper concludes with a visionary outlook on the future of smart cities, posited on the seamless integration of AI technologies. Bayashot envisions a world where AI-powered mobile apps not only facilitate smoother urban operations but also empower citizens to actively participate in the shaping of their urban environments. This research serves as a critical call to action for policymakers, technologists, and urban planners to embrace AI as a tool for creating more sustainable, efficient, and inclusive cities. By presenting a detailed analysis of the current state of AI in urban development, coupled with practical insights and forward-looking recommendations, “The Contribution of AI-powered Mobile Apps to Smart City Ecosystems” stands as a seminal work that is poised to inspire and guide the evolution of urban landscapes worldwide. Its comprehensive exploration of the subject matter, combined with its impactful conclusions, make it a must-read for anyone involved in the field of smart city development, AI technology, or urban policy-making.

Megacity pathways in China under the dual carbon goal:The case of Shanghai

The pathways to achieving carbon neutrality at the city level are diverse due to varying energy supply and demand conditions.Shanghai faces obstacles such as limited land resources,high costs of renewable energy technologies,and instability of renewable energy.These challenges hinder the city’s efforts to achieve carbon peak and carbon neutrality(dual carbon).Therefore,Shanghai must identify and optimize its development path for renewable energy under the dual carbon goal.We employed the Low Emissions Analysis Platform Shanghai(LEAP-SH)model to simulate the impact of policies,such as industrial upgrading,energy efficiency improvement,energy structure optimization,increased technical innovation on energy,and ecological restoration,on the carbon emission pathways from 2022 to 2060 using five different scenarios.Our results indicate that Shanghai has the potential to achieve carbon neutrality in 2059 by promoting carbon reduction,pollution control,and green expansion.Moreover,we determined that the manufacturing industry;power generation industry;and transportation,storage,and mail services are the three major sectors for emission reduction under the dual carbon goal.Furthermore,the capacity and output of coal-fired power plants will be gradually replaced by offshore wind power in the dual carbon pathway.Finally,this study proposes countermeasures and suggestions for Shanghai to attain the dual carbon goal and high-quality development.

Resilience assessment and optimization method of city road network in the post-earthquake emergency period

The post-earthquake emergency period,which is a sensitive time segment just after an event,mainly focuses on saving life and restoring social order.To improve the seismic resilience of city road networks,a resilience evaluation method used in the post-earthquake emergency period is proposed.The road seismic damage index of a city road network can consider the influence of roads,bridges and buildings along the roads,etc.on road capacity after an earthquake.A function index for a city road network is developed,which reflects the connectivity,redundancy,traffic demand and traffic function of the network.An optimization model for improving the road repair order in the post-earthquake emergency period is also developed according to the resilience evaluation,to enable decision support for city emergency management and achieve the best seismic resilience of the city road network.The optimization model is applied to a city road network and the results illustrate the feasibility of the resilience evaluation and optimization method for a city road network in the post-earthquake emergency period.

Constructing a standard system of city sustainable development assessment technology based on the SDGs

Given the rapid development of China’s new urbanization,cities with different locations and varying functional positioning,resource endowments,and development stages have insufficient scientific and applicable technical tools for implementing the United Nations Sustainable Development Goals(SDGs).City managers and policymakers must urgently establish SDG benchmarks to diagnose city development.Moreover,successful experiences from similar cities regarding sustainable development and self-improvement must be learned from to promote diversified,sustainable development across the country.Furthermore,emerging technologies such as artificial intelligence,the Internet of Things,big data and 5G are widely used in smart cities.Therefore,there is a growing need for“knowledge-based,personalized and intelligent”technologies to support monitoring,evaluation,and decision-making processes facilitating sustainable development in cities.This paper uses standardization as the theoretical support and technical basis.This approach can help clarify the sustainable development processes in China and clarify the evaluation results of and provide data on horizontal city comparisons,which can be used to develop evaluation technology for sustainable development in cities and construct a standardized system.The results provide a standard framework for intelligent assessment and decision-making regarding cities’sustainable development capabilities in China.Evaluating major international standardization institutions reveals that the practices of Chinese national standards should be fully absorbed and integrated to guide the evaluation of smart,resilient,and low-carbon cities.To this end,an indicator library of city sustainable development is proposed to provide standard evaluation technology methods.Finally,analyzing the response relationship of the indicator library to SDGs reveals the need for a standardized knowledge map of sustainable development assessment techniques and methods from the perspective of integrated management for sustainable development in cities.

Some of the Chemical and Physical Characteristics of the Graff River in Kut City, Iraq

Some of the chemical and physical water qualities of the Graff River in the city of Kut were studied, and for two sites of the river, One was at the Crimea site, the other in the Jihad district, and for the period from October/2018 to March/2019, Seven variables of river water have been analyzed: temperature PH, electrical conductivity, TDS, turbidity, alkaline, and chloride. The results showed that most of the chemical and physical water properties of the river were in normal proportions and did not rise, except for the turbidity, which was at a very high level, and that the pH values were close to the basal side. The results of the statistical analysis revealed positive significant relationships between the pH and (chloride and TDS). On the other hand, between electrical conductivity and both previous variables as well. And a negative significant connection between temperature and alkaline.

Subsurface multi-physical characterization of mountain excavation and city construction in loess plateau with a fiber-optic sensing system

Mountain excavation and city construction(MECC)projects being launched in the Loess Plateau in China involve the creation of large-scale artificial land.Understanding the subsurface evolution characteristics of the artificial land is essential,yet challenging.Here,we use an improved fiber-optic monitoring system for its subsurface multi-physical characterization.The system enables us to gather spatiotemporal distribution of various parameters,including strata deformation,temperature,and moisture.Yan’an New District was selected as a case study to conduct refined in-situ monitoring through a 77 m-deep borehole and a 30 m-long trench.Findings reveal that the ground settlement involves both the deformation of the filling loess and the underlying intact loess.Notably,the filling loess exhibits a stronger creep capability compared to underlying intact loess.The deformation along the profile is unevenly distributed,with a positive correlation with soil moisture.Water accumulation has been observed at the interface between the filling loess and the underlying intact loess,leading to a significant deformation.Moreover,the temperature and moisture in the filling loess have reached a new equilibrium state,with their depths influenced by atmospheric conditions measuring at 31 m and 26 m,respectively.The refined investigation allows us to identify critical layers that matter the sustainable development of newly created urban areas,and provide improved insights into the evolution mechanisms of land creation.

Planning and construction of Xiong’an New Area(city of over 5 million people):Contributions of China’s geologists and urban geology

China established Xiong’an New Area in Hebei Province in 2017,which is planned to accommodate about 5 million people,aiming to relieve Beijing City of the functions non-essential to its role as China’s capital and to expedite the coordinated development of the Beijing-Tianjin-Hebei region.From 2017 to 2021,the China Geological Survey(CGS)took the lead in multi-factor urban geological surveys involving space,resources,environments,and disasters according to the general requirements of“global vision,international standards,distinctive Chinese features,and future-oriented goals”in Xiong’an New Area,identifying the engineering geologic conditions and geologic environmental challenges of this area.The achievements also include a 3D engineering geological structure model for the whole area,along with“one city proper and five clusters”,insights into the ecology and the background endowment of natural resources like land,geothermal resources,groundwater,and wetland of the area before engineering construction,a comprehensive monitoring network of resources and environments in the area,and the“Transparent Xiong’an”geological information platform that is open,shared,dynamically updated,and three-dimensionally visualized.China’s geologists and urban geology have played a significant role in the urban planning and construction of Xiong’an New Area,providing whole-process geological solutions for urban planning,construction,operation and management.The future urban construction of Xiong’an New Area will necessitate the theoretical and technical support of earth system science(ESS)from various aspects,and the purpose is to enhance the resilience of the new type of city and to provide support for the green,low-carbon,and sustainable development of this area.

Microplastics Detection and Identification in the Waters along Coastal Areas of Borongan City

This study detects the presence of microplastics in the coastal areas of Borongan City, Eastern Samar, this specifically implies the microplastics present in the waters along coastal areas of Borongan City. Two (2) sampling areas were identified and selected for the presence of these microcontaminants using density separation, filtration and microscopic identification. Results reveal a total of 35 microplastics observed from the water samples collected, with this the microplastics from Baybay boulevard with an average of 0.79 microplastics per Liter, while the average microplastic contamination in Hilangagan beach resort was calculated at 0.43 microplastics per Liter. This sums up to an average of 0.49 microplastics per Liter for both sampling sites in Borongan City.

Bivariate Analysis of Pollutants Monthly Maxima in Mexico City Using Extreme Value Distributions and Copula

In the present work, we are interested in studying the joint distributions of pairs of the monthly maxima of the pollutants used by the environmental authorities in Mexico City to classify the air quality in the metropolitan area. In order to obtain the joint distributions a copula will be considered. Since we are analyzing the monthly maxima, the extreme value distributions of Weibull and Fréchet are taken into account. Using these two distributions as marginal distributions in the copula a Bayesian inference was made in order to estimate the parameters of both distributions and also the association parameters appearing in the copula model. The pollutants taken into account are ozone, nitrogen dioxide, sulphur dioxide, carbon monoxide, and particulate matter with diameters smaller than 10 and 2.5 microns obtained from the Mexico City monitoring network. The estimation was performed by taking samples of the parameters generated through a Markov chain Monte Carlo algorithm implemented using the software OpenBugs. Once the algorithm is implemented it is applied to the pairs of pollutants where one of the coordinates of the pair is ozone and the other varies on the set of the remaining pollutants. Depending on the pollutant and the region where they were collected, different results were obtained. Hence, in some cases we have that the best model is that where we have a Fréchet distribution as the marginal distribution for the measurements of both pollutants and in others the most suitable model is the one assuming a Fréchet for ozone and a Weibull for the other pollutant. Results show that, in the present case, the estimated association parameter is a good representation to the correlation parameters between the pair of pollutants analyzed. Additionally, it is a straightforward task to obtain these correlation parameters from the corresponding association parameters.

Shear wave velocity model using HVSR inversion beneath Bandar Lampung City

The horizontal-to-vertical spectral ratio(HVSR)method has been used to characterize site-effect parameters that are indispensable in seismic hazard and risk-reduction studies in urban areas and rapid land-use planning.This method is widely used because it is the cheapest and simplest geophysical method for the acquisition and processing stages.In subsequent developments,the HVSR method has been widely used to determine elastic rock parameters,particularly shear wave velocity(v_(S)),through the HVSR curve inversion process.Furthermore,the v_(S)structural model can be used to delineate the presence of complex geological structures,particularly faults and sedimentary basins.Bandar Lampung is a city in Lampung Province with many fault structures and groundwater basins to the south.There are 83 HVSR measurement points around Bandar Lampung for delineating the presence of fault structures and groundwater basins.We produced the HVSR curve from the measurement results and then performed an inversion process using the particle swarm optimization algorithm to obtain v_(S)for the depth profile.Subsequently,from this profile,we produced a two-dimensional(2D)lateral and vertical model.The mean v_(S)value was calculated from all the measurement points,and we found stiff soil layers reaching depths of approximately 5 m,with a value of v_(S)<330 m/s.A bedrock layer with a velocity exceeding 1250 m/s was visible at a depth of 100 m.Based on the 2D model,the v_(S)structure shows that the city of Bandar Lampung is divided into two zones,with a NW-SE boundary.The north-middle-eastern part of the city consists of harder rocks.This harder rock is characterized by extremely high v_(S)values,starting from a depth of 50 m.In contrast,the south-middle-west exhibits a low-moderate v_(S)anomaly associated with groundwater basins SW of the city.From the 2D v_(S)structural model,fault structures can be found along the city,characterized by a contrast of v_(S)values from low to medium and from medium to high.