Mapping and measuring urban-rural inequalities in accessibility to social infrastructures

Equal access to social infrastructures is a fundamental prerequisite for sustainable development,but has long been a great challenge worldwide.Previous studies have primarily focused on the accessibility to social infras-tructures in urban areas across various scales,with less attention to rural areas,where inequality can be more severe.Particularly,few have investigated the disparities of accessibility to social infrastructures between urban and rural areas.Here,using the Changsha-Zhuzhou-Xiangtan urban agglomeration,China,as an example,we investigated the inequality of accessibility in both urban and rural areas,and further compared the urban-rural difference.Accessibility was measured by travel time of residents to infrastructures.We selected four types of social infrastructures including supermarkets,bus stops,primary schools,and health care,which were funda-mentally important to both urban and rural residents.We found large disparities in accessibility between urban and rural areas,ranging from 20 min to 2 h.Rural residents had to spend one to two more hours to bus stops than urban residents,and 20 min more to the other three types of infrastructures.Furthermore,accessibility to multiple infrastructures showed greater urban-rural differences.Rural residents in more than half of the towns had no access to any infrastructure within 15 min,while more than 60%of the urban residents could access to all infrastructures within 15 min.Our results revealed quantitative accessibility gap between urban and rural areas and underscored the necessity of social infrastructures planning to address such disparities.

The Influence of Climate Factors on the Stability of Infrastructures: Case of Forest Ecosystem in Southern Cameroon

The southern forest ecosystem of Cameroon extends from latitude 2° to 6°N and from 10° to 16°E. In order to investigate about the influence of climate factors on the infrastructures, the main parameters of local climate of that ecosystem have been evaluated. The results show that, the factors are stable and have a common trend. But, the abundance of precipitations;the important hydrographic network and the presence of dense forest appear as the majors climatic constraints that may be taken in account to ensure the stability of the infrastructures in forest ecosystem.

An Appraisal of Water Availability, Infrastructures for Faecal Disposal and the Potential of Spread of Infectious Diseases in the Traveling Agencies and Motor Parks in the City of Yaounde (Cameroon)

The number of interurban and urban-rural travelers in the city of Yaounde has recently exceeded one hundred thousand per year, yet surprisingly few studies have assessed travelers’ behavior, illness, and risk factors in a sanitary risks setting. Particularly scarce are surveys of data spanning travel, return, and follow-up of the same cohort in traveling agencies and parks. This study examines behavior and illness among travelers moving from Yaounde to other urban and rural areas of Cameroon and beyond. Patterns of behavior connected to a type of travel and illness are characterized in this study so as to identify risks factors and provide background data for pre-travel advice in our traveling agencies. Assessing the susceptibility that imported cases could pose to the national response to infectious diseases depends both on public health, health services and infrastructures. The six agencies assessed: Nvan, Mokolo, Tongolo, Biyem Assi, Mimbowman and Etoudi reveal that the sanitary infrastructures for faecal and urinary disposal are not sufficient and more so, some agencies do not keep enough cleanliness, let alone provide adequate hand washing material as prescribed by national and international concerns to combat the global health challenges. This could be an impediment to travellers going out or inside of the city, and could be a preponderant mechanism for the spread of infectious disease as presented by the infectious diseases isolated and identified in the health districts around the travelling agencies.

Reliability analysis of geotechnical infrastructures: Introduction

In the design of geotechnical infrastructure,engineers have to deal with naturally occurring soils and rocks which are subjected to spatial variability as well as other uncertainties such as errors in measurement and in modeling methods.Reliability assessment which provides a systematic approach for quantifying the risk of failure has been shown to be a promising tool for solving these challenging geotechnical engineering problems.The method provides a more consistent measure of the level of safety or“structural reliability”through the evaluation of a reliability index and the associated“failure”probability,and is a method that satisfies the need to clearly convey safety issues to the public and regulatory authorities.Various methods for calculating the reliability of geotechnical infrastructures with regard to the assessment of the ultimate and serviceability limit states have been proposed by many researchers and these approaches include:the direct Monte Carlo Simulation,Bayesian and other sampling techniques,the first-order reliability method and the second-order reliability method,the random field method,the response surface method and other surrogate models with the related probabilistic procedures.In this special issue of Geoscience Frontiers,we assemble eleven invited papers which provide insights on the latest developments and challenges in applying probabilistic and reliability methods to geotechnical infrastructure design.

A Blockchain-Based Architecture for Enabling Cybersecurity in the Internet-of-Critical Infrastructures

Due to the drastic increase in the number of critical infrastructures like nuclear plants,industrial control systems(ICS),transportation,it becomes highly vulnerable to several attacks.They become the major targets of cyberattacks due to the increase in number of interconnections with other networks.Several research works have focused on the design of intrusion detection systems(IDS)using machine learning(ML)and deep learning(DL)models.At the same time,Blockchain(BC)technology can be applied to improve the security level.In order to resolve the security issues that exist in the critical infrastructures and ICS,this study designs a novel BC with deep learning empowered cyber-attack detection(BDLE-CAD)in critical infrastructures and ICS.The proposed BDLE-CAD technique aims to identify the existence of intrusions in the network.In addition,the presented enhanced chimp optimization based feature selection(ECOA-FS)technique is applied for the selection of optimal subset of features.Moreover,the optimal deep neural network(DNN)with search and rescue(SAR)optimizer is applied for the detection and classification of intrusions.Furthermore,a BC enabled integrity checking scheme(BEICS)has been presented to defend against the misrouting attacks.The experimental result analysis of the BDLE-CAD technique takes place and the results are inspected under varying aspects.The simulation analysis pointed out the supremacy of the BDLE-CAD technique over the recent state of art techniques with the accuy of 92.63%.

An Automated Process of Creating 3D City Model for Monitoring Urban Infrastructures

This paper describes the process of designing models and tools for an automated way of creating 3D city model based on a raw point cloud.Also,making and forming 3D models of buildings.Models and tools for creating tools made in the model builder application within the ArcGIS Pro software.An unclassified point cloud obtained by the LiDAR system was used for the model input data.The point cloud,collected by the airborne laser scanning system(ALS),is classified into several classes:ground,high and low noise,and buildings.Based on the created DEMs,points classified as buildings and formed prints of buildings,realistic 3D city models were created.Created 3D models of cities can be used as a basis for monitoring the infrastructure of settlements and other analyzes that are important for further development and architecture of cities.

A Diachronic Perspective on the Use of French Spatial Data Infrastructures

Despite the recent development of many worldwide initiatives, there is still a need for the development of observation frameworks that will provide a comprehensive view of SDI’s use. Amongst the many challenges left, a thorough analysis of the information flows between existing SDIs as well as their respective uses and the way that those evolve over time is an important issue to explore. The research presented in this paper introduces a methodological framework oriented to the study of the SDIs use from a diachronic perspective. The approach is based on a Social Network Analysis (SNA) and questionnaires collected by online surveys. We develop a structural and diachronic analysis based on a series of graph-based measures identifying the main patterns that appear over time. The methodological framework is applied to a series of French SDIs and users involved in environmental management. The study identifies a series of structural differences in the data flows that emerge between the users and SDIs. Last, the diachronic network analysis provides an overall understanding on how data flows evolve over time at different institutional levels.

Research e-infrastructures for open science: The national example of CSTCloud in China

This paper focuses on research e-infrastructures in the open science era.We analyze some of the challenges and opportunities of cloud-based science and introduce an example of a national solution in the China Science and Technology Cloud(CSTCloud).We selected three CSTCloud use cases in deploying open science modules,including scalable engineering in astronomical data management,integrated Earth-science resources for SDG-13 decision making,and the coupling of citizen science and artificial intelligence(AI)techniques in biodiversity.We conclude with a forecast on the future development of research e-infrastructures and introduce the idea of the Global Open Science Cloud(GOSC).We hope this analysis can provide some insights into the future development of research e-infrastructures in support of open science.

Numerical evaluation of enhanced green infrastructures for mitigating urban heat in a desert urban setting

The cities of desert climates are anticipated to recognize a synergy of urban heat island(UHI)and severe heat waves during summertime.To improve the urban thermal environment,the present study aims quantitatively explore a strategically designed network of vegetation patches called green infrastructure(GI)in subtropical desert cities such as Dubai.To achieve a more comfortable temperature environment,we built and simulated four GI situations with higher GI fractions,GI25,GI50,GI75,and GI100.Using a mesoscale urban model,the mosaic approach is utilized to test potential thermal improvement and urban climate impact,and a portion of each urban grid cell in the model domain is altered with various species of urban vegetation patches by 25%,50%,75%,and 100%.The daily peak reduction in ambient temperature at 17:00LT is similar to 0.0168℃ per unit of GI increase when compared to the untreated scenario;however,the maximum anticipated daytime summer temperature decline for GI25,GI50,GI75,and GI100 is 0.6℃,1.1℃,1.4℃,and 1.7℃,respectively.The associated reduction in nighttime ambient temperature per unit increase in the GI is 0.0432℃,with a maximum temperature drop of around 2.4℃ for the GI100 scenario.Increased GI reduces the height of the planetary boundary layer(PBL)by up to 468 m,which might lead to greater pollution concentrations.While GI-based cooling has a significant influence on delayed sea breeze and humidity,it may raise the risk of heat discomfort in the indoor building environment.This study adds to our understanding of the potential for GI mitigation as well as the seasonal impact of developing GIs on the desert urban boundary layer.

Global and International Security Under Spatial Grasp Paradigm

Global and international security cannot be provided from a single point or a set of separate points whatever powerful these might be(even with quantum supercomputers!).It should rather be deeply embedded and integrated with bodies of real systems wherever in physical,virtual,or combined spaces they may exist.So global security capabilities should not only be distributed,but rather be really spatial,self-organized,and dynamic,also exhibiting overall integrity,awareness,and consciousness features.The paper describes applicability of the patented and revealed in 10 books Spatial Grasp Model and Technology(SGT)and its basic Spatial Grasp Language(SGL)which conceptually and functionally match security problems of large distributed and heterogeneous systems.It investigates very practical security solutions for finding and tracing distribution of forbidden items,world roaming criminals,recovery from natural and human-made disasters,tracing and elimination of moving dangerous objects in terrestrial and celestial spaces,as well as analysis and restoration of damaged transport networks.It advises how different security infrastructures can be organized and managed,and how to cooperate and integrate within global security systems with higher awareness and consciousness levels over them.The provided security-oriented version of SGL can be quickly implemented and integrated with existing distributed management and security systems.

Research on Logistics Network Infrastructures Based on DEA-PCA Approach:Evidence from the Yangtze River Delta Region in China

Compared with the extensive research on logistics network infrastructures(LNIs)in the developed world,empirical research is still scarce in China.In this paper the theory of LNIs is firstly overviewed.Then a new evaluation index system for LNIs is set up which contains factors that reflect the economic development level,transportation accessibility and turnover volume of freight traffc.An empirical study is carried out by using data envelopment analysis(DEA)and principal component analysis(PCA)approach to classify LNIs into 4 clusters for 25 cities in the Yangtze River Delta Region of China.According to the characteristics of the 4 clusters,suggestions are proposed for improving their LNIs.Finally,after comparing different LNIs of 25 cities in the Yangtze River Delta Region of China,this paper proposes that different LNIs including hub,central distribution center or cross docking center,regional distribution center or distribution center should be built reasonably in order to meet the customer's requirement in the four different cluster cities.

Pervasive geo-security - a lightweight triple-A approach to securing distributed geo-service infrastructures

Security has recently become a major concern in distributed geo-infrastructures for spatial data provision.Thus,a lightweight approach for securing distributed low-power environments such as geo-sensor networks is needed.The first part of this article presents a survey of current security mechanisms for authentication and authorisation.Based on this survey,a lightweight and scalable token-based security infrastructure was developed,which is tailored for use in distributed geo-web service infrastructures.The developed security framework comprises dedicated components for authentication,rule-based authorisation and optimised storage and administration of access rules.For validation purposes,a prototypical implementation of the approach has been created.

Echo from the underground: the heritage customization of subway infrastructures in Shanghai’s listed areas

The design of metro stations constitutes a clear example of the new core role of culture in a city such as Shanghai that remains to be assessed from a critical heritage perspective.As an unexplored dimension of a massive heritage institutional apparatus,metro stations act as‘white canvases’where commercial,political and cultural messages are displayed.These messages contribute to city branding while simultaneously influencing the perception and interpretation of the historic urban landscape above ground.This research offers insights into the subway stations located in the listed heritage areas of Shanghai and the architectural,artistic and exhibitive resources that‘give character’to these stations.The research applies visual methods and discursive analysis based on direct observation of these‘characteristic’elements in metro stations.The paper establishes the argument that the amount and distribution of these characteristic elements in the metro network offers unequal representation of the importance of the heritage areas above.When represented,we argue that such features convey renewed narratives of urban identity according to an authorised heritage discourse in Shanghai.These narratives cater to an image of ideal,harmonious continuity between the past and the future that aims to characterise Shanghai as a Chinese global metropolis.

New roles of research data infrastructure in research paradigm evolution

Research data infrastructures form the cornerstone in both cyber and physical spaces,driving the progression of the data-intensive scientific research paradigm.This opinion paper presents an overview of global research data infrastructure,drawing insights from national roadmaps and strategic documents related to research data infrastructure.It emphasizes the pivotal role of research data infrastructures by delineating four new missions aimed at positioning them at the core of the current scientific research and communication ecosystem.The four new missions of research data infrastructures are:(1)as a pioneer,to transcend the disciplinary border and address complex,cutting-edge scientific and social challenges with problem-and data-oriented insights;(2)as an architect,to establish a digital,intelligent,flexible research and knowledge services environment;(3)as a platform,to foster the high-end academic communication;(4)as a coordinator,to balance scientific openness with ethics needs.

Impacts of road on plant invasions in the Middle Mountain region of central Nepal

Biological invasion is triggered by human development activities such as the construction and expansion of road networks.Road verges serve as important habitats and corridors for the distribution of invasive alien plant species(IAPS)between geographically distant habitats.However,the trajectory of plant invasion and the data regarding the impact of roads on IAPS distribution are relatively poor in Nepal.Here,we surveyed two road types(main roads and feeder road)in the Middle Mountain region of central Nepal in order to investigate how different road types are driving the dispersal of IAPS along road verges and the adjacent natural habitats.Systematic sampling was conducted at ca 2.5 km intervals along the roads.At each sampling site,paired plots(25 m×4 m)were sampled:one adjacent to and along the road,and another 20 m away and parallel to it in the interior habitat.Our results revealed that the main road verges had a higher cover(33%)and a larger number of IAPS(14 species)than the feeder road(25%;10 species).The IAPS cover and richness were significantly higher along verges than in the adjacent interior habitats for both road types,indicating that roads are contributing as corridors for the dispersal of IAPS in the Middle Mountain areas of central Nepal.Further,elevation,tree canopy,and disturbances(grazing/mowing/trampling)were found to be the key factors that determine spatial distribution of IAPS along road verges.We emphasize that regular monitoring of vegetation along the road verges can help with the early detection and control of potential IAPS in the region before they become problematic.

Enhancing the Trustworthiness of 6G Based on Trusted Multi-Cloud Infrastructure:A Practice of Cryptography Approach

Due to the need for massive device connectivity,low communication latency,and various customizations in 6G architecture,a distributed cloud deployment approach will be more relevant to the space-air-ground-sea integrated network scenario.However,the openness and heterogeneity of the 6G network cause the problems of network security.To improve the trustworthiness of 6G networks,we propose a trusted computing-based approach for establishing trust relationships inmulti-cloud scenarios.The proposed method shows the relationship of trust based on dual-level verification.It separates the trustworthy states of multiple complex cloud units in 6G architecture into the state within and between cloud units.Firstly,SM3 algorithm establishes the chain of trust for the system’s trusted boot phase.Then,the remote attestation server(RAS)of distributed cloud units verifies the physical servers.Meanwhile,the physical servers use a ring approach to verify the cloud servers.Eventually,the centralized RAS takes one-time authentication to the critical evidence information of distributed cloud unit servers.Simultaneously,the centralized RAS also verifies the evidence of distributed RAS.We establish our proposed approach in a natural OpenStack-based cloud environment.The simulation results show that the proposed method achieves higher security with less than a 1%system performance loss.

Thornthwaite moisture index and depth of suction change under current and future climate‒An Australian study

Climate change is one of the major global challenges and it can have a significant influence on the behaviour and resilience of geotechnical structures.The changes in moisture content in soil lead to effective stress changes and can be accompanied by significant volume changes in reactive/expansive soils.The volume change leads to ground movement and can exert additional stresses on structures founded on or within a shallow depth of such soils.Climate change is likely to amplify the ground movement potential and the associated problems are likely to worsen.The effect of atmospheric boundary interaction on soil behaviour has often been correlated to Thornthwaite moisture index(TMI).In this study,the long-term weather data and anticipated future projections for various emission scenarios were used to generate a series of TMI maps for Australia.The changes in TMI were then correlated to the depth of suction change(H s),an important input in ground movement calculation.Under all climate scenarios considered,reductions in TMI and increases in H s values were observed.A hypothetical design scenario of a footing on expansive soil under current and future climate is discussed.It is observed that a design that might be considered adequate under the current climate scenario,may fail under future scenarios and accommodations should be made in the design for such events.

Extensive identification of landslide boundaries using remote sensing images and deep learning method

The frequent occurrence of extreme weather events has rendered numerous landslides to a global natural disaster issue.It is crucial to rapidly and accurately determine the boundaries of landslides for geohazards evaluation and emergency response.Therefore,the Skip Connection DeepLab neural network(SCDnn),a deep learning model based on 770 optical remote sensing images of landslide,is proposed to improve the accuracy of landslide boundary detection.The SCDnn model is optimized for the over-segmentation issue which occurs in conventional deep learning models when there is a significant degree of similarity between topographical geomorphic features.SCDnn exhibits notable improvements in landslide feature extraction and semantic segmentation by combining an enhanced Atrous Spatial Pyramid Convolutional Block(ASPC)with a coding structure that reduces model complexity.The experimental results demonstrate that SCDnn can identify landslide boundaries in 119 images with MIoU values between 0.8and 0.9;while 52 images with MIoU values exceeding 0.9,which exceeds the identification accuracy of existing techniques.This work can offer a novel technique for the automatic extensive identification of landslide boundaries in remote sensing images in addition to establishing the groundwork for future inve stigations and applications in related domains.

Hybrid Prairie Dog and Beluga Whale Optimization Algorithm for Multi-Objective Load Balanced-Task Scheduling in Cloud Computing Environments

The cloud computing technology is utilized for achieving resource utilization of remotebased virtual computer to facilitate the consumers with rapid and accurate massive data services.It utilizes on-demand resource provisioning,but the necessitated constraints of rapid turnaround time,minimal execution cost,high rate of resource utilization and limited makespan transforms the Load Balancing(LB)process-based Task Scheduling(TS)problem into an NP-hard optimization issue.In this paper,Hybrid Prairie Dog and Beluga Whale Optimization Algorithm(HPDBWOA)is propounded for precise mapping of tasks to virtual machines with the due objective of addressing the dynamic nature of cloud environment.This capability of HPDBWOA helps in decreasing the SLA violations and Makespan with optimal resource management.It is modelled as a scheduling strategy which utilizes the merits of PDOA and BWOA for attaining reactive decisions making with respect to the process of assigning the tasks to virtual resources by considering their priorities into account.It addresses the problem of pre-convergence with wellbalanced exploration and exploitation to attain necessitated Quality of Service(QoS)for minimizing the waiting time incurred during TS process.It further balanced exploration and exploitation rates for reducing the makespan during the task allocation with complete awareness of VM state.The results of the proposed HPDBWOA confirmed minimized energy utilization of 32.18% and reduced cost of 28.94% better than approaches used for investigation.The statistical investigation of the proposed HPDBWOA conducted using ANOVA confirmed its efficacy over the benchmarked systems in terms of throughput,system,and response time.

Characterization of Wastewater in School Environments for an Ecological Treatment Solution: A Case Study of Ndiebene Gandiol 1 School

The study conducted at Ndiebene Gandiol 1 school in Senegal has unveiled serious environmental and public health challenges. The wastewater analysis revealed high levels of Biochemical Oxygen Demand (BOD5), Chemical Oxygen Demand (COD), and fecal coliforms, signaling potential risks to the well-being of students and staff. This situation mirrors a wider issue in rural educational settings, where inadequate sanitation persists. Intensive wastewater treatment options are known for their effectiveness against high pollutant loads but are resource-intensive in both energy and cost. Conversely, extensive treatment systems, while requiring more land, provide a sustainable alternative by harnessing natural processes for pollutant removal. The research suggests a hybrid treatment approach could serve the school’s needs, balancing the robust capabilities of intensive methods with the ecological benefits of extensive systems. Such a solution would need to be tailored to the specific environmental, financial, and logistical context of the school, based on comprehensive feasibility studies and stakeholder engagement. This study’s findings underscore the urgency of addressing sanitation in schools, as it is intrinsically linked to the health and academic success of students. Quick, effective, and long-term strategies are vital to secure a healthier and more prosperous future for the youth. With proper implementation, the school can transform its sanitation facilities, setting a precedent for rural educational institutions in Senegal and similar contexts globally.