Inaccessible Areas Research Articles

Detection of Brain-Derived Cell-Free DNA in Plasma

Background: Neuronal loss is a major pathological feature of neurodegenerative diseases. The analysis of plasma cell-free DNA (cfDNA) is an emerging approach to track cell death events in a minimally invasive way and from inaccessible areas of the body, such as the brain. Previous studies showed that DNA methylation (DNAm) profiles can be used to map the tissue of origin of cfDNA and to identify molecules released from the brain upon cell death. The aim of the present study is to contribute to this research field, presenting the development and validation of an assay for the detection of brain-derived cfDNA (bcfDNA). Methods: To identify CpG sites with brain-specific DNAm, we compared brain and non-brain tissues for their chromatin state profiles and genome-wide DNAm data, available in public datasets. The selected target genomic regions were experimentally validated by bisulfite sequencing on DNA extracted from 44 different autoptic tissues, including multiple brain regions. Sequencing data were analysed to identify brain-specific epihaplotypes. The developed assay was tested in plasma cfDNA from patients with immune effector cell-associated neurotoxicity syndrome (ICANS) following chimeric antigen receptor T (CAR-T) therapy. Results: We validated five genomic regions with brain-specific DNAm (four hypomethylated and one hypermethylated in the brain). DNAm analysis of the selected genomic regions in plasma samples from CAR-T patients revealed higher levels of bcfDNA in participants with ongoing neurotoxicity syndrome. Conclusions: We developed an assay for the analysis of bcfDNA in plasma. The assay is a promising tool for the early detection of neuronal loss in neurodegenerative diseases.

Empirical Evaluation and Simulation of the Impact of Global Navigation Satellite System Solutions on Uncrewed Aircraft System–Structure from Motion for Shoreline Mapping and Charting

Uncrewed aircraft systems (UASs) and structure-from-motion/multi-view stereo (SfM/MVS) photogrammetry are efficient methods for mapping terrain at local geographic scales. Traditionally, indirect georeferencing using ground control points (GCPs) is used to georeference the UAS image locations before further processing in SfM software. However, this is a tedious practice and unsuitable for surveying remote or inaccessible areas. Direct georeferencing is a plausible alternative that requires no GCPs. It relies on global navigation satellite system (GNSS) technology to georeference the UAS image locations. This research combined field experiments and simulation to investigate GNSS-based post-processed kinematic (PPK) as a means to eliminate or reduce reliance on GCPs for shoreline mapping and charting. The study also conducted a brief comparison of real-time network (RTN) and precise point positioning (PPP) performances for the same purpose. Ancillary experiments evaluated the effects of PPK base station distance and GNSS sample rate on the accuracy of derived 3D point clouds and digital elevation models (DEMs). Vertical root mean square errors (RMSEz), scaled to the 95% confidence interval using an assumption of normally-distributed errors, were desired to be within 0.5 m to satisfy National Oceanic and Atmospheric Administration (NOAA) requirements for nautical charting. Simulations used a Monte Carlo approach and empirical tests to examine the influence of GNSS performance on the quality of derived 3D point clouds. RTN and PPK results consistently yielded RMSEz values within 10 cm, thus satisfying NOAA requirements for nautical charting. PPP did not meet the accuracy requirements but showed promising results that prompt further investigation. PPK experiments using higher GNSS sample rates did not always provide the best accuracies. GNSS performance and model accuracies were enhanced when using base stations located within 30 km of the survey site. Results without using GCPs observed a direct relationship between point cloud accuracy and GNSS performance, with R2 values reaching up to 0.97.

A means of destroying sites of perennial root shoot weeds with pests and diseases in them

BACKGROUND: The subject of the study is the technological process of protective spraying of agricultural crops using a combined method against perennial weeds in sites in the field using two pneumohydraulic devices with slot atomizers as part of an improved small-sized boom sprayer. AIM: Development of a technical mean for exterminating sites of perennial root shoot weeds with pests and diseases in them. METHODS: The developed pneumohydraulic devices were used for an improved mounted boom sprayer of plants to treat sites of perennial weeds in the field. Chemical spraying with combined use of the traditional method and the developed pneumohydraulic devices with axial fans and 12 V electric motors, ensuring the distribution of droplet liquid on the treatment surface with two sprayers over 4 meters, is able to reduce the amount of the applied chemicals compared to the conventional technology and to reduce the pesticide load on crop plants by local destruction of sites of weeds, pests and diseases. Based on the developed methods, the results of spraying the surface with a drop liquid with a known dispersion using slot sprayers and controlled liquid pressures with a dial gauge during experiments were obtained. SCIENTIFIC NOVELTY: For the first time, a combined method and technical mean of achieving the research aim have been proposed for the destruction of sites of perennial weeds in the field and the diseases and pests of agricultural crops spread in them. RESULTS: When using a mounted sprayer with two containers for working fluids of combined herbicide solutions or for an insecticide solution in one of the containers and installation of the improved pneumohydraulic devices on the edges of the boom with a conventional arrangement of slot atomizers, it is possible to meet agrotechnical requirements for the use of herbicides, insecticides and fungicides. The simultaneous impact of large drops of herbicides on weeds and the penetration of small drops into plants will destroy sites of rhizome and root weeds with pests and diseases to ensure favorable conditions for the production of agricultural crops. CONCLUSION: A combined method and the technical mean of chemical treatment of perennial weeds with pests and diseases to create favorable conditions for the production of cultivated plants has been experimentally substantiated. Compliance with the conditions is ensured by equipping the mounted sprayer with two containers, pumps for supplying liquid through hoses to slot atomizers, and installing pneumohydraulic liquid nozzles at the edges of the boom. Working liquid sprayers ensure spraying width of more than 4 m, taking into account the size of a site, as well as spraying inaccessible areas using conventional technical means. The efficiency of the developed combined protective spraying of agricultural crops against perennial weeds and pests by the technical mean of its implementation lies in the savings of expensive herbicides and insecticides up to 70% in the later stages of their growing season (as they grow over the field area) compared to the forced continuous application of the herbicide over the entire field area.

Aerial Systems for Releasing Natural Enemy Insects of Purple Loosestrife Using Drones

Lythrum salicaria (purple loosestrife) is an invasive species that displaces native wetland flora in the USA. The detection and manual release of biological control agents for L. salicaria is challenging because L. salicaria inhabits many inaccessible areas. This study was conducted to develop aerial systems for the detection of L. salicaria and the release of its natural enemy, Galerucella calmariensis (Coleoptera: Chrysomelidae). We determined the optimal sensors and flight height for the aerial detection of L. salicaria and designed an aerial deployment method for G. calmariensis. Drone-based aerial surveys were conducted at various flight heights utilizing RGB, multispectral, and thermal sensors. We also developed an insect container (i.e., bug ball) for the aerial deployment of G. calmariensis. Our findings indicated that L. salicaria flowers were detectable with an RGB sensor at flight heights ≤ 15 m above the canopy. The post-release mortality and feeding efficiency of G. calmariensis did not significantly differ from the control group (non-aerial release), indicating the feasibility of the targeted release of G. calmariensis. This innovative study establishes a critical foundation for the future development of sophisticated aerial systems designed for the automated detection of invasive plants and the precise release of biological control agents, significantly advancing ecological management and conservation efforts.

Study on surface waves for detection of fatigue cracks in railway joint bars

The current method of inspecting railway joint bars involves the use of high-resolution cameras to detect fatigue cracks that have undergone significant cracking exposed to the surface. The novelty of the work presented in this paper discusses the development and application of non-contact ultrasonic surface wave approach to detect and characterize near-surface fatigue cracks in the head of the railway joint bars which is not usually accessible for inspection. Simulated cracks were implanted in the head of the two different used joint bars to assess the capabilities of the ultrasonic nondestructive evaluation (NDE) surface wave approach. One of the joint bars was implanted with 3.175 mm and 6.35 mm cracks in length, while the other joint bar was implanted with 12.7 mm and 25.4 mm cracks in length. Despite the complex geometry of railway joint bars, the laboratory proof-of-concept testing conducted in an immersion water tank demonstrated that the developed non-contact surface wave approach successfully detected implanted cracks in both joint bars. The results obtained from the study indicate that a 0.5 MHz ultrasonic transducer provided the best sensitivity for detecting implanted cracks compared to 1 MHz and 2.25 MHz transducers. Similarly, test results obtained with a 0.5 MHz ultrasonic transducer, launching a surface wave from an accessible area to an inaccessible area of the joint bar (where the implanted cracks were located) yielded a significantly higher signal-to-noise ratio (SNR) than the 1 MHz and 2.25 MHz transducer.

Spectral Discrimination of Common Karoo Shrub and Grass Species Using Spectroscopic Data

Rangelands represent about 25% of the Earth’s land surface but are under severe pressure. Rangeland degradation is a gradually increasing global environmental problem, resulting in temporary or permanent loss of ecosystem functions. Ecological rangeland studies aim to determine the productivity of rangelands as well as the severity of their degradation. Rigorous in situ assessments comprising visual identification of plant species are required as such assessments are perceived to be the most accurate way of monitoring rangeland degradation. However, in situ assessments are expensive and time-consuming exercises, especially when carried out over large areas. In situ assessments are also limited to areas that are accessible. This study aimed to evaluate the effectiveness of multispectral (MS) and hyperspectral (HS) remotely sensed, unmanned aerial vehicle (UAV)-based data and machine learning (random forest) methods to differentiate between 15 dominant Nama Karoo plant species to aid ecological impact surveys. The results showed that MS imagery is unsuitable, as classification accuracies were generally low (37.5%). In contrast, much higher classification accuracies (>70%) were achieved when the HS imagery was used. The narrow bands between 398 and 430 nanometres (nm) were found to be vital for discriminating between shrub and grass species. Using in situ analytical spectral device (ASD) spectroscopic data, additional important wavebands between 350 and 400 nm were identified, which are not covered by either the MS or HS remotely sensed data. Using feature selection methods, 12 key wavelengths were identified for discriminating among the plant species with accuracies exceeding 90%. Reducing the dimensionality of the ASD data set to the 12 key bands increased classification accuracies from 84.8% (all bands) to 91.7% (12 bands). The methodology developed in this study can potentially be used to carry out UAV-based ecological assessments over large and inaccessible areas typical of Karoo rangelands.

Evaluation of aerial thermography for measuring the thermal transmittance (U-value) of a building façade

In efforts to mitigate greenhouse gas emissions in the construction sector, policies promoting energy efficiency improvements in existing buildings are being implemented. Accurately assessing the impact of energy retrofit strategies requires precise determination of thermal envelope performance through energy audits. Aerial thermography, employing unmanned aerial vehicles (UAVs) equipped with infrared thermal cameras (IRT), is an underused method overcoming limitations in energy audits of large buildings or complexes. This approach offers an elevated perspective, providing an overview of the building’s thermal patterns, aiding in the identification of thermal envelope defects. By measuring temperature distribution, even in inaccessible envelope areas, the severity of identified defects can be estimated. Beyond detecting thermal bridges, air leaks, and moisture, aerial thermography is valid for estimating thermal transmittance (U-value) of enclosures. The aim of this research is to evaluate this method to calculate the U-value of the façade of an university building located in a Subtropical Mediterranean climate, during a typical full day in different seasons of the year. Concurrently with aerial thermography, the thermometric method (THM) was applied to compare results and refine the operational conditions during U-value measurement using different statistical indices and uncertainty analysis. The results demonstrated the validation of airborne thermography as a method for U-value calculation under specific meteorological and operational conditions, overcoming the common physical limitations of traditional building audit methods.

Socio-monetary and Demographic Profile of Gujjar and Bakkarwals of Poonch District

The present study is an attempt to understand the educational backwardness of scheduled tribes of district Poonch of Jammu and Kashmir. The Scheduled Tribes (ST’s) are the socially and educationally deprived people in India. Scheduled Tribes have specific histories of social and monetary deprivation and the underlying reasons in their educational marginalization are also strikingly awesome. Schooling forms a crucial factor inside the average improvement of people, enabling them to get extra awareness, higher comprehension in their social, political and cultural surroundings and additionally facilitating inside the development of their socio-monetary conditions. The time period “tribe” was earlier used for a network which constituted a homogenous institution that lived in overall isolation having a particularly self-sustaining economic system independent political setup and which maintained wonderful customs, religions practices inherited from one common place ancestor. The scheduled tribes are the oldest settlers, if no longer the primary in India and India has the second one biggest concentration of the tribes inside internationally. Scheduled tribe population constitutes 8.6% of the entire population in India. Jammu and Kashmir has many tribal communities having their own traditions, cultures and customs. Scheduled Tribe groups have traditionally lived in remote and some difficult terrains in the direction of forests and natural assets. Most of the tribes live in inaccessible areas.

Drone‐towed electromagnetic and magnetic systems for subsurface characterization and archaeological prospecting

AbstractDrone‐based geophysical surveying is an emerging measuring platform. High time‐cost efficiency and flexibility to survey over inaccessible areas make drones attractive or sometimes the only feasible option to carry geophysical measurements. This study presents a new drone‐towed electromagnetic induction and magnetic gradient sensor system used for near‐surface characterization and areal mapping.The system uses various datasets to enhance processing and interpretation. The system includes; an electromagnetic induction instrument; magnetic sensors; GNSS‐IMU system; photogrammetry; Lidar model data; and geoid model data. Robust data processing and stochastic inversion subsurface characterization for archaeological prospecting with drone‐towed electromagnetic induction and magnetic gradient sensor systems. Robust statistical methods were used to process the data.We conducted the fieldwork at one of the ancient Viking settlements in Denmark. The surveyed area was approximately 100200 m. We then implemented and applied a one‐dimensional laterally constrained non‐linear stochastic inversion to image the subsurface electrical conductivity. The inversion results show a consistent conductive layer at 5–8 m depths, likely associated with the groundwater level. This conductive layer is disrupted under a prominent anomaly within a 2–4 m wide area. Our analysis showed that this conductivity disruption could be a flint mine extending 7 m deep. This anomaly also has a strong signature in magnetic gradient data.

Love thy neighbour: Feral buffalos show greater space use, resource overlap and encounters during the wet season in the Northern Territory.

Managing feral water buffalo in the Northern Territory is a formidable challenge. As an introduced species, buffalo are associated with a myriad of biosecurity, economic, cultural and environmental issues ranging from overgrazing, decreased water quality, disease vectors to the destruction of cultural assets. Nevertheless, the buffalo are also a harvestable resource that can support economic development of the region. To mitigate some of the biosecurity, economic, cultural and environmental risks they pose and manage buffalo effectively, we need a detailed understanding of their spatial and behavioural ecology. However, several factors make understanding how best to manage the dense populations of wild individuals challenging as buffalo inhabit remote areas with limited infrastructure and accessibility and their large size and often aggressive nature can make them difficult to observe in otherwise inaccessible areas. GPS tracking allows for high-frequency data collection and surveillance of individual buffalo. Here, we investigated how the different seasonal periods of a Northern Territory floodplain area shaped patterns of habitat use for 17 buffalo tracked over 16 months. We found in the dry season, buffalo space use is restricted, and the size of home ranges are significantly smaller than in the wet season. During the wet season, buffalo expand their home range area as well as their social encounter area with other buffalo. These differences in their space use and social patterns suggest that increased disease surveillance may be needed for the wet season when buffalo are more likely to share space and interact. During the dry season, however, buffalo movement is more predictable and restricted, suggesting greater optimisation opportunities for buffalo management. Results from these models can be used by land holders, Traditional Owners and wildlife managers to make evidence-based decisions to improve buffalo management with respect to disease risk, sustainable harvest and damage to environmental and cultural assets.

Optimization of Fuel Enrichment and Reactor Core Pitch Dimension in Hydride Microreactor using NSGA-II Method and OpenMC Calculation

Abstract This study focuses on the design optimization of a hydride microreactor, aimed at supporting the equitable development of electricity in remote regions of Indonesia. Its compact design, inherent safety properties, and independence from the conventional electric grid make this microreactor concept suitable for electrifying even the most inaccessible areas. Current research investigates various aspects of the hydride microreactor design, employing a standard reactor core pitch dimension of 2.4 cm and fuel enrichment of 12%. It is crucial to operate the reactor using specific concentrations of Gadolinia burnable poison to enable a shutdown in the event of a stuck rod. By optimizing only the pitch dimension and fuel enrichment, the reactor can be simulated relatively quickly without the need for burnup calculations. Ideal configuration aims for lower enrichment, an extended fuel cycle, and a relatively low power peaking factor (PPF). The optimization process utilizes the Non-dominated Sorting Genetic Algorithm – II, with the neutron multiplication factor (keff) and PPF as primary objectives. Fuel cycle and feedback reactivity are the sub-objectives that are used to identify the optimal solution from the Pareto front. The calculation process of keff, PPF, fuel cycle, and feedback reactivity coefficients for specific pitch dimensions and fuel enrichment are done by utilizing the OpenMC Monte Carlo code. The optimal configuration is obtained through four generations of NSGA-II, featuring a reactor core pitch of 2.1 cm and fuel enrichment of 10.4%. This configuration yields a keff value of 1.0712049 and a PPF value of 2,0728 at the Beginning of Life (BOL). Remarkably, this configuration enables safe operation without using burnable poison for a continuous period of 12 years, generating 1 MW of thermal power. Emphasizing the reduction of fissile material is also essential to enhance the inherent safety of the reactor.

Extending geodetic networks for geo-monitoring by supervised point cloud matching

Abstract In this paper we propose a monitoring method that allows the inclusion of point clouds into a geodetic monitoring network. Consequently, network adjustment and a rigorous deformation analysis can be performed allowing consistent error propagation and trustful significance calculation. We introduce a supervised pipeline based on ICP-matching of small-scale laser scan patches. It is specially designed for geo-monitoring applications and allows to improve the spatial resolution as well as the network geometry of monitoring networks in inaccessible hazardous areas in the mountains, where the installation of a sufficient number of targets is difficult. We apply our method to two datasets. The first is a monitoring setup in the laboratory, where we establish the parameters for the supervised patch selection and demonstrate how the network geometry is improved. Second is the real case study of Mt. Hochvogel, where the proposed method helps to clearly improve the spatial resolution of deformation vectors.

A Review of Multi-UAV Task Allocation Algorithms for a Search and Rescue Scenario

Unmanned aerial vehicles (UAVs) play a crucial role in enhancing search and rescue (SAR) operations by accessing inaccessible areas, accomplishing challenging tasks, and providing real-time monitoring and modeling in situations where human presence is unsafe. Multi-UAVs can collaborate more efficiently and cost-effectively than a single large UAV for performing SAR operations. In multi-UAV systems, task allocation (TA) is a critical and complex process involving cooperative decision making and control to minimize the time and energy consumption of UAVs for task completion. This paper offers an exhaustive review of both static and dynamic TA algorithms, confidently assessing their strengths, weaknesses, and limitations. It provides valuable insights into addressing research questions related to specific UAV operations in SAR. The paper rigorously discusses outstanding issues and challenges and confidently presents potential directions for the future development of task assignment algorithms. Finally, it confidently highlights the challenges of multi-UAV dynamic TA methods for SAR. This work is crucial for gaining a comprehensive understanding of multi-UAV dynamic TA algorithms and confidently emphasizes critical open issues and research gaps for future SAR research and development, ensuring that readers feel informed and knowledgeable.

Brain Metastases in Differentiated Thyroid Cancer: Clinical Presentation, Diagnosis, and Management.

Background: Brain metastases (BM) are the most common intracranial neoplasms in adults and are a significant cause of morbidity and mortality. The brain is an unusual site for distant metastases of thyroid cancer; indeed, the most common sites are lungs and bones. In this narrative review, we discuss about the clinical characteristics, diagnosis, and treatment options for patients with BM from differentiated thyroid cancer (DTC). Summary: BM can be discovered before initial therapy due to symptoms, but in most patients, BM is diagnosed during follow-up because of imaging performed before starting tyrosine kinase inhibitors (TKI) or due to the onset of neurological symptoms. Older male patients with follicular thyroid cancer (FTC), poorly differentiated thyroid cancer (PDTC), and distant metastases may have an increased risk of developing BM. The gold standard for detection of BM is magnetic resonance imaging with contrast agent administration, which is superior to contrast-enhanced computed tomography. The treatment strategies for patients with BM from DTC remain controversial. Patients with poor performance status are candidates for palliative and supportive care. Neurosurgery is usually reserved for cases where symptoms persist despite medical treatment, especially in patients with favorable prognostic factors and larger lesions. It should also be considered for patients with a single BM in a surgically accessible location, particularly if the primary disease is controlled without other systemic metastases. Additionally, stereotactic radiosurgery (SRS) may be the preferred option for treating small lesions, especially those in inaccessible areas of the brain or when surgery is not advisable. Whole brain radiotherapy is less frequently used in treating these patients due to its potential side effects and the debated effectiveness. Therefore, it is typically reserved for cases involving multiple BM that are too large for SRS. TKIs are effective in patients with progressive radioiodine-refractory thyroid cancer and multiple metastases. Conclusions: Although routine screening for BM is not recommended, older male patients with FTC or PDTC and distant metastases may be at higher risk and should be carefully evaluated for BM. According to current data, patients who are suitable for neurosurgery seem to have the highest survival benefit, while SRS may be appropriate for selected patient.

Exploring Cognitive Workload Changes in Teleoperators: Collaboration with On-Site Workers and Robots in Assembly Tasks

Teleoperation is commonly employed to perform industrial tasks in remote or inaccessible areas. However, there is a noticeable gap in evaluating cognitive workload of teleoperators in collaboration environments. This study compared the variation of cognitive workload for teleoperators guiding an on-site participant to complete a wire assembly task in two scenarios: one aided by a robot arm (tRH) and another without any robot assistance (HH). Additionally, the task demands for on-site participants were manipulated to measure its impact on teleoperator’s workload. NASA-TLX and EEG activity were utilized to assess workload. The results indicated that EEG theta activity was significantly higher for the HH group than tRH group, potentially showing lower workload for teleoperators in the scenario with robot assistance. Task difficulty did not affect any of the workload measures. The study highlights the importance of cognitive workload assessment in human-robot collaborations to optimize human cognitive demands in complex settings.

Microplastics and gut microbiomes impact on Yunnan snub-nosed monkeys in the Three Parallel Rivers region in China.

Microplastics (MPs) has been rapidly increasing and interacting with wildlife. As the highest altitudes inhabited non-human primate, Yunnan snub-nosed monkey (Rhinopithecus bieti) have been proven to be an umbrella and flagship species to indicate ecosystem changes and help develop environmental management strategies. In this study, we aimed to investigate the behavioral and ecological reasons for the types, content and differences of MPs in the feces of R. bieti, and explored the effects of MPs on gut microbiome of R. bieti. We used the Agilent 8700 LDIR to identify the abundance and size distribution of MPs in fecal samples, and then analyzed the causes of differences in MPs content by combining data from different populations (wild group, provisioned wild group) and dominance hierarchy. At the same times, the relationships were investigated between gut microbiome diversity and MPs content. We first demonstrate MPs ingestion by R. bieti, which highlights the potential impacts of MPs pollution in such high-altitude, inaccessible protected areas. A total of 36 types of MPs were detected, with an average of 75.263 ± 58.141MPs/g. Food provisioning and tourism significantly increased the content of MPs in the feces of R. bieti, but tourism alone did not significantly increase the content of MPs as food provisioning. At the same time, the study found that there was no significant difference in the content of MPs between different sex groups, however, the feces MPs content of adult R. bieti was significantly lower than that of juvenile, and the social dominance hierarchies among OMUs was positively correlated with the exposure of MPs. The current level of MPs pollution did not cause gut microbiome dysbiosis of R. bieti. Our study proved from behavioral and ecological perspectives that the R. bieti exposure to MPs was related to provisioned food, and was closely related to dominance hierarchy and age. From the perspective of intestinal microbiology, it was proved that the current intake of MPs did not cause gut microbiome dysbiosis of R. bieti. Our study provided scientific basis for formulating effective protection measures and promoting the effective protection of rare and endangered animals.

The Future of Microreactors: Technological Advantages, Economic Challenges, and Innovative Licensing Solutions with Blockchain

This study details the unique advantages and challenges associated with microreactors. Microreactors offer rapid installation and flexible application capabilities, meeting energy needs in remote and inaccessible areas. Unlike large nuclear power plants, they can be set up and start generating energy within a few days, resulting in significant time and cost savings. Their small size and modular design reduce capital and operational costs while enhancing economic competitiveness. However, some technical and regulatory challenges persist for the widespread adoption of microreactors. Licensing processes designed for large nuclear power plants may delay the widespread adoption of microreactors. Blockchain technology can play a crucial role in overcoming these challenges by providing transparency and reliability in the licensing processes. The operational settings of microreactors should be carefully considered, and regulatory authorities must be effectively designated. Collaboration and coordination are vital in this process. Consequently, the flexibility and innovative solutions offered by microreactors highlight the importance of future research to examine the optimal conditions for their use.

Fostering urban resilience and accessibility in cities: A dynamic knowledge graph approach

This paper explores the utilisation of knowledge graphs and an agent-based implementation to enhance urban resilience and accessibility in city planning. We expand The World Avatar (TWA) dynamic knowledge graph to support decision-making in disaster response and urban planning. By employing a set of connected agents and integrating diverse data sources — including flood data, geospatial building information, land plots, and open-source data — through sets of ontologies, we demonstrate disaster response in a coastal town in the UK and various aspects relevant to city planning for a mid-sized town in Germany using TWA. In King’s Lynn, our agent-based approach facilitates holistic disaster response by calculating optimal routes, avoiding flooded segments dynamically, assessing infrastructure accessibility before and during a flood using isochrones, identifying inaccessible population areas, guiding infrastructure restoration, and conducting critical path analysis. In Pirmasens, for city planning purposes, the knowledge graph-driven isochrone generation provides evidence-based insights into current amenity coverage and enables scenario planning for future amenities while adhering to land regulations. The implementation of agents and knowledge graphs achieves interoperability and enhances urban resilience and accessibility by enabling cross-domain correlation analysis that extends various areas including geospatial buildings, population demographics, accessibility coverage, and land use regulations.

Detection of Cliff Top Erosion Drivers through Machine Learning Algorithms between Portonovo and Trave Cliffs (Ancona, Italy)

Rocky coastlines are characterised by steep cliffs, which frequently experience a variety of natural processes that often exhibit intricate interdependencies, such as rainfall, ice and water run-off, and marine actions. The advent of high temporal and spatial resolution data, that can be acquired through remote sensing and geomatics techniques, has facilitated the safe exploration of otherwise inaccessible areas. The datasets that can be gathered from these techniques, typically combined with data from fieldwork, can subsequently undergo analyses employing/applying machine learning algorithms and/or numerical modeling, in order to identify/discern the predominant influencing factors affecting cliff top erosion. This study focuses on a specific case situated at the Conero promontory of the Adriatic Sea in the Marche region. The research methodology entails several steps. Initially, the morphological, geological and geomechanical characteristics of the areas were determined through unmanned aerial vehicle (UAV) and conventional geological/geomechanical surveys. Subsequently, cliff top retreat was determined within a GIS environment by comparing orthophotos taken in 1978 and 2022 using the DSAS tool (Digital Shoreline Analysis System), highlighting cliff top retreat up to 50 m in some sectors. Further analysis was conducted via the use of two Machine Learning (ML) algorithms, namely Random Forest (RF) and eXtreme Gradient Boosting (XGB). The Mean Decrease in Impurity (MDI) methodology was employed to assess the significance of each factor. Both algorithms yielded congruent results, emphasising that cliff top erosion rates are primarily influenced by slope height. Finally, a validation of the ML algorithm results was conducted using 2D Limit Equilibrium Method (LEM) codes. Ten sections extracted from the sector experiencing the most substantial cliff top retreat, as identified by DSAS, were utilised for 2D LEM analysis. Factor of Safety (FS) values were identified and compared with the cliff height of each section. The results from the 2D LEM analyses corroborated the outputs of the ML algorithms, showing a strong correlation between the slope instability and slope height (R2 of 0.84), with FS decreasing with slope height.

Anthropic influence on chelonian composition in a metropolitan region of Southern Brazil

Knowledge about chelonians in Brazil remains limited, especially concerning basic research on these organisms. Considered one of the most threatened vertebrate group, chelonians are negatively affected by different factors such as anthropic pressure. Therefore, this study had two main goals: to describe the freshwater turtle assemblage within the urban and periurban area of Maringá and Sarandi, Southern Brazil, as well as to compare turtle composition between areas accessed by people and inaccessible areas. Fieldwork was conducted in six sites in 2013, 2014, 2016, 2017 and 2021, employing four different methods to record turtles. A total of five species were registered, whith two native to the region (Hydromedusa tectifera, Phrynops geoffroanus) and three exotic taxa (Trachemys dorbigni, Trachemys scripta elegans, Platemys platycephala platycephala). The most abundant species was T. dorbigni (n=162), followed by P. geoffroanus (n=140) and T. scripta elegans (n=95). To analyze the anthropic influence on the turtle composition, standardized samplings were conducted in two accessed and two inaccessible areas and Principal Coordinate Analysis (PCoA) was performed. The results revealed a strong relationship between the human presence in the areas and the occurrence of exotic turtles. The two alien taxa (T. dorbigni and T. scripta elegans) represented 74.5% of all chelonians analyzed, indicating a worrying scenario for the urban ecosystem.