Detailed Mapping Research Articles

Topographic and Geodetic Survey for Samarkand's Administrative Boundaries

General Background: Administrative and territorial boundary delineation is vital in the effective governance and economic planning of urban regions globally, with digital technologies increasingly integrated into these processes for accuracy and efficiency. Specific Background: In Uzbekistan, the city of Samarkand’s administrative boundaries are undergoing significant realignment as part of a broader initiative to incorporate strategic urban centers and enable digital land management across administrative zones. Knowledge Gap: Existing methods lack precise integration with digital geospatial frameworks, leaving a gap in high-resolution topographic data essential for clear administrative delineation. Aims: This study seeks to develop and apply an accurate, digitally supported methodology for determining the boundaries of Samarkand's administrative units using advanced geodetic and topographic techniques. Results: By utilizing the CREDO DAT program, this study achieved precise boundary coordinates through the automated processing of survey points, and further analysis was conducted using the Panorama program for detailed map orientation. Novelty: This research presents a unique approach by integrating CREDO DAT with geospatial tools in administrative boundary demarcation, enabling accurate and reproducible results that surpass traditional methods in efficiency and scalability. Implications: The findings support the strategic planning of Samarkand’s infrastructure and resource allocation while also laying the groundwork for applying similar methodologies in other urban regions, advancing Uzbekistan’s digital transformation efforts in land management.Highlights: Digital tools enhance accuracy in administrative boundary mapping. CREDO DAT and Panorama software streamline data processing for precise mapping. This method supports effective urban planning and resource management in Samarkand. Keywords: Administrative Zones, Border, Territory, District, City

Shifting Sands: Examining and Mapping the Population Structure of Greece Through the Last Three Censuses

This paper aims to facilitate a more nuanced understanding of regional disparities in the population age structure at a local scale by applying a recent method for visualizing these disparities. Utilizing data from the three most recent population censuses in Greece, this method applies advanced data visualization techniques to map age distributions, highlighting significant variations in aging patterns across municipalities, towns, and districts. Traditional demographic analysis often overlooks local heterogeneities, leading to broad policies that often fail to address the unique needs of specific regions. Detailed maps are created by integrating geographic data with census data (using R and GIS), enabling policymakers to pinpoint areas with specific demographic challenges and opportunities. This localized approach reveals critical insights, such as regions experiencing rapid population aging, areas with younger population profiles, and zones undergoing demographic transitions. The visualization tool significantly improves the formulation of targeted strategies, enhancing the effectiveness of policies related to healthcare, workforce planning, and social services distribution. Through case studies and comparative analysis, we demonstrate the practical applications and advantages of this method in shaping public policy and strategic planning. This paper contributes to the field of geodemography by introducing and demonstrating a visualization method that enhances the accuracy of demographic analysis, providing policy makers with useful information to better address local demographic challenges and tailor strategies to specific regional needs.

Late pleistocene glacial history of Mount Karadağ, SW Türkiye

Glacial landforms in the southwestern part of the Anatolian Peninsula are found at lower elevations than the rest, suggesting that glaciers were present during the Late Pleistocene. Karadağ, located west of the Western Taurus Mountains, provides evidence of the climatic conditions that facilitated this extensive glaciation. It is characterized by numerous peaks exceeding 2300 m above sea level (asl), with the highest peak reaching 2418 m, making it the region's largest glaciation area. This high mountain mass is composed mainly of limestone and dolomite. This study focuses on the glacial landforms in Karadağ to reconstruct the Late Pleistocene glacial chronology and palaeoclimate of the Western Taurus Mountains. We employed detailed UAV photogrammetry, extensive fieldwork and mapping, surface exposure dating with cosmogenic 36Cl, meteorological measurements, palaeoglacier reconstruction, and palaeo-equilibrium line altitude (pELA) calculations. Karadağ, a topographic barrier to humid air masses from the Mediterranean Sea, ranks as the second wettest area in the Western Taurus Mountains. At a meteorological station we installed in Karadağ, an annual precipitation of 1700 mm or more was recorded, highlighting its significant precipitation. In Karadağ, we have identified two glacial valleys with a maximum length of 4.5 km and six cirques. The glaciers reached their maximum extent around 22.4 ± 2.8 ka during the Last Glacial Maximum (LGM), facilitated by the lowering of the pELA to 2090 m. During the LGM, the glaciers covered an area of approximately 3.5 km2 and reached a maximum thickness of about 140 m. Sample TRKR 10 at 2015 m probably belongs to the LGM period. Although a single sample does not conclude definitive conclusions, the presence of the moraine at its highest position indicates the maximum thickness of the glacier. Following the LGM, two more significant glacier advances occurred during the Lateglacial (15.5 ± 2.7 ka) and the Younger Dryas (12.4 ± 1.1 ka). During the late Pleistocene glaciations, and especially during the LGM, Karadağ probably received more precipitation than today, leading to the formation of glaciers at relatively lower elevations than on the Anatolian Peninsula.

Spectral aging analysis of the 3C 219 double-double radio galaxy

Context. Double-double radio galaxies are characterized by intermittent jet-formation activity. The exact reasons for this behavior are not yet fully understood. Studying these objects and their environment allows us to find common characteristics and compare them with the general population of radio galaxies. 3C 219 is a well-known and thoroughly studied radio galaxy. Among the many explanations for its unusual “partial jet” structure, intermittent activity seems to be the leading one. However, this hypothesis has never been tested using aging analysis. Aims. The aim of this paper is to put constraints on the active galactic nucleus duty cycle and dynamics of radio lobe expansion in 3C 219, in both the inner and outer double. This will provide us with information on the behavior of the central engine and the interaction of the radio lobes with the ambient medium, allowing us to verify whether the structure of 3C 219 is the result of intermittent activity and to search for its possible causes. Methods. We performed a spectral aging analysis of the 3C 219 double-double radio galaxy using archival Karl G. Jansky Very Large Array and Low Frequency Array data. We present detailed spectral age maps and constructed a spectral age profile. We compared ratios of linear sizes and luminosities in individual phases of activity with lobe expansion velocities in the plane of the sky derived from the age profile to infer hot-spot advance velocities through the surrounding medium and the orientation of the jet axes. Results. The galaxy shows a general asymmetry in the distribution of plasma with respect to the inferred jet axis in the original phase of activity, suggesting an influence of the intracluster medium on the formation of the radio structure. The advance speed of hot spots in the outer double is typical of classical FRII sources expanding into an ambient thermal medium, while for the inner double, the lower limit is estimated to be ∼0.28 c. The radio galaxy has experienced a very short quiescent period of no more than 2 Myr, which is ≲7% of its total lifetime. Conclusions. The most plausible explanation for the double-double radio structure in 3C 219 is a rapid jet reorientation along the line of sight, which may be the result of a minor merger. Further study of the 3C 219 inner double is needed. High-resolution maps are required to probe its structure in sufficient detail, while high-frequency observations are necessary to better constrain the durations of the quiescent and restarted phases.

Bamboo Forests: Unleashing the Potential for Carbon Abatement and Local Income Improvements

Bamboo forests exhibit a unique efficient growth pattern that makes them invaluable in reducing atmospheric CO2 levels. Additionally, bamboo forests offer a diverse range of products, thus holding the potential to bolster local income. Despite these benefits, the comprehensive assessment of bamboo forests’ potential in both carbon abatement and improving local income enhancement has been hindered by the absence of a detailed bamboo biomass map. In this study, we address this gap by amalgamating a bamboo aboveground biomass (AGB) map covering three prominent producing provinces in southern China, utilizing multi-source remote sensing datasets. The results not only demonstrate a satisfactory consistency with China’s Ninth National Forest Inventory but also provide a more detailed spatial distribution. Based on this AGB estimation, we project an approximately threefold potential increase in annual bamboo culm harvest from existing bamboo forests. This represents a significant opportunity for expanding carbon abatement efforts, elevating local income levels, and facilitating the production of bamboo-derived biofuels. Furthermore, the adoption of an optimized management strategy has the potential to further enhance bamboo production. This study generates the first high-resolution bamboo AGB map and underscores the substantial potential of China’s bamboo forests in contributing to carbon sequestration and improving local income. The favorable income generated for local residents can serve as a compelling incentive for the implementation of sustainable forest management practices, offering a promising pathway toward achieving carbon-related objectives within the forestry sector and providing necessary support for forestry designation projects.

Flood Vulnerability Assessment in Paradip Coastal Area Using Weighted Overlay Index

Paradip, a prominent coastal city on India's eastern seaboard, presents a unique combination of environmental challenges and urban pressures. It has the largest tidal range among major regional tidal gauge stations, including Vishakhapatnam and Chennai. The city experiences an annual sea level rise of 2.33 mm, with projections indicating an increase of 0.183 feet by 2047 and 0.76 feet over the next century. The city's unique environmental and urban issues are exacerbated by its placement within the Mahanadi River's deltaic deposits, floodplains, and coastal marine deposits along the Bay of Bengal. The shoreline of Paradip is topographically uniform, with ground elevations ranging from 3.6 to 5.7 meters. According to India's Wind and Cyclone Hazard Map, Paradip is in the "Very High Damage Risk Zone," indicating the presence of significant wind speeds along the coast. The paper digs into these vulnerabilities and their possible influence on the coastal community, emphasizing the city's need to strike a balance between urban growth and ecological preservation. One of the main problems is flooding. Rainwater enters government buildings and impoverished areas because of encroachments on natural drainage systems. Dryland capable of residential, agricultural, and other economic activities is submerged by overflowing water which causes loss of life, property, and infrastructure. This study evaluates flood vulnerabilities in Paradip, a coastal city, using GIS and a weighted overlay index. By integrating satellite imagery, digital elevation models (DEM), and historical data on rainfall and soil types, we developed a detailed flood vulnerability map that categorises areas into high, moderate, and low risk. ArcGIS Pro 2.7.3 software and a weighted overlay index were utilized for the collection, processing, and display of spatial and attribute data. spatial analysis was the process used to produce the flood vulnerability map. The results provide essential insights for urban planning and flood mitigation strategies, with direct implications for improving disaster preparedness and climate resilience. The flood vulnerability map was then compared to the masterplan of Paradip which was proposed for 2030, to know the actual vulnerable area and to defy some major which were proposed by Paradip development authority. The study illustrates how remote sensing and GIS techniques can be effectively utilized to generate flood vulnerability data essential for informed decision-making.

Deep learning-assisted morphological segmentation for effective particle area estimation and prediction of interfacial properties in polymer composites.

The link between the macroscopic properties of polymer nanocomposites and the underlying microstructural features necessitates an understanding of nanoparticle dispersion. The dispersion of nanoparticles introduces variability, potentially leading to clustering and localized accumulation of nanoparticles. This non-uniform dispersion impacts the accuracy of predictive models. In response to this challenge, this study developed an automated and precise technique for particle recognition and detailed mapping of particle positions in scanning electron microscopy (SEM) micrographs. This was achieved by integrating deep convolutional neural networks with advanced image processing techniques. Following particle detection, two dispersion factors were introduced, namely size uniformity and supercritical clustering, to quantify the impact of particle dispersion on properties. These factors, estimated using the computer vision technique, were subsequently used to calculate the effective load-bearing area influenced by the particles. An adapted micromechanical model was then employed to quantify the interfacial strength and thickness of the nanocomposites. This approach enabled the establishment of a correlation between dispersion characteristics and interfacial properties by integrating experimental data, relevant micromechanical models, and quantified dispersion factors. The proposed systematic procedure demonstrates considerable promise in utilizing deep learning to capture and quantify particle dispersion characteristics for structure-property analyses in polymer nanocomposites.

Chromatic covalent organic frameworks enabling in-vivo chemical tomography

Covalent organic frameworks designed as chromatic sensors offer opportunities to probe biological interfaces, particularly when combined with biocompatible matrices. Particularly compelling is the prospect of chemical tomography – or the 3D spatial mapping of chemical detail within the complex environment of living systems. Herein, we demonstrate a chromic Covalent Organic Framework (COF) integrated within silk fibroin (SF) microneedles that probe plant vasculature, sense the alkalization of vascular fluid as a biomarker for drought stress, and provide a 3D in-vivo mapping of chemical gradients using smartphone technology. A series of Schiff base COFs with tunable pKa ranging from 5.6 to 7.6 enable conical, optically transparent SF microneedles with COF coatings of 120 to 950 nm to probe vascular fluid and the surrounding tissues of tobacco and tomato plants. The conical design allows for 3D mapping of the chemical environment (such as pH) at standoff distances from the plant, enabling in-vivo chemical tomography. Chromatic COF sensors of this type will enable multidimensional chemical mapping of previously inaccessible and complex environments.

Integrative 3D genomics with multi-omics analysis and functional validation of genetic regulatory mechanisms of abdominal fat deposition in chickens

Chickens are the most abundant agricultural animals globally, with controlling abdominal fat deposition being a key objective in poultry breeding. While GWAS can identify genetic variants associated with abdominal fat deposition, the precise roles and mechanisms of these variants remain largely unclear. Here, we use male chickens from two lines divergently selected for abdominal fat deposition as experimental models. Through the integration of genomic, epigenomic, 3D genomic, and transcriptomic data, we build a comprehensive chromatin 3D regulatory network map to identify the genetic regulatory mechanisms that influence abdominal fat deposition in chickens. Notably, we find that the rs734209466 variant functions as an allele-specific enhancer, remotely enhancing the transcription of IGFBP2 and IGFBP5 by the binding transcription factor IRF4. This interaction influences the differentiation and proliferation of preadipocytes, which ultimately affects phenotype. This work presents a detailed genetic regulatory map for chicken abdominal fat deposition, offering molecular targets for selective breeding.

Vitamin D in cardiac fibroblasts: new evidence for a TRP-mediated non-genomic pathway

Abstract Background/Introduction Vitamin D’s (VD) role transcends phosphocalcic metabolism to affect different systems, notably the cardiovascular system in health and diseases. Beyond its genomic effect, VD act through non-genomic calcium (Ca2+) signaling pathways, hinting at a broader spectrum of physiological impacts. Despite the established interactions with cardiomyocytes via the Vitamin D Receptor (VDR), little is known about VD and cardiac fibroblast, a pivotal cell player in cardiac function and disease. Purpose This research aims to reveal Vitamin D's role in modulating cardiac fibroblast function through Transient Receptor Potential (TRP) channels. Methods Utilizing primary cardiac fibroblasts from human and rats, our investigation focused on intracellular calcium signaling. Through Ca2+ imaging techniques combined to synthetic fluorescent VD analogue, we explored Vitamin D's behavior within the cell. The study further employed biochemical assays to elucidate the interaction between VDR on the cell membrane and TRP channels signaling, providing a detailed map of the cellular choreography orchestrated by VD within cardiac fibroblasts. In addition, in vitro and ex vivo heart perfusion experiments were incorporated to assess cardiac cGMP production in response to VD. Results Our findings reveal a unique pathway wherein VD induces Ca2+ oscillations in human and rat cardiac fibroblasts specifically through the TRPC3 channel, sidelining other calcium sources. This process is regulated by the interaction between TRPC3 and the membrane-bound VDR, harmonizing with phospholipase C signaling to a crescendo of cGMP production in cardiac fibroblasts, and across the entire heart. This was associated with less pro-fibrotic potential of cardiac fibroblasts. Conclusion This study provides the first evidence of a TRP-mediated, VD non-genomic pathway within human and rat cardiac fibroblasts. Our findings herald a promising horizon for investigating vitamin D’s antifibrotic potential in heart disease.

The evolution of spatial and temporal distribution of rainfall erosivity in Henan Province, central China

With the advancement of urbanization, there has been a significant reduction in cultivated land, accompanied by soil erosion. Concurrently, the regularity of rainfall in recent years has been erratic, adversely impacting the grain economy and agricultural development in certain regions. Henan Province, spanning the basins of the Yangtze River, the Yellow River, the Huaihe River, and the Haihe River, possesses complex hydrological conditions and serves as a pivotal agricultural zone in China. Therefore, this paper utilizes daily rainfall data collected over 54 years (1969–2022) from 112 rain measuring stations in Henan Province to calculate the rainfall erosivity using the Zhang model and the erosivity model from the first national water survey. Meanwhile, spatial analysis was performed using the Kriging interpolation method in the ArcGIS Geostatistical Wizard, resulting in detailed spatial distribution maps of rainfall and rainfall erosivity. The study also employed Wavelet and Mann–Kendall tests to analyze the abrupt changes, trends and periodicity of rainfall and rainfall erosivity within the target region. The findings indicate that the average rainfall (1969–2022) in Henan province was 718.26 mm, while the average rainfall erosivity (R) was 3213.46 MJ mm/(hm2 h). R values are positively correlated with rainfall intensity and volume, displaying an annual upward trend. Spatially, R values increase gradually from northwest to southeast, closely aligning with topographical variations. Additionally, the analysis revealed a predominant periodic cycle of 54 years in the precipitation patterns. These results offer valuable insights for environmental and agricultural management in other regions of central China.

AN INTEGRATED APPROACH TO IDENTIFY SUITABLE AREAS FOR THE LOCATION OF PUBLIC FACILITIES USING MULTI-CRITERIA ANALYSIS BASED ON GIS AND AHP IN THE CITY OF EL KHROUB, ALGERIA

Random and spontaneous urban growth is the result of massive natural population growth, as it is in all developing countries. As for our study air, it also results from the unloading of the mother city of Constantine to the satellite city of El-Khroub, which gave urbanization the power to take over its vast environment, An uneven distribution of public facilities in the city’s major districts, as well as traffic jams. This work attempted to determine the suitability of urban land for the location of public facilities in the city. It should be noted that land suitability assessment is a major factor in urban planning and management. Our land adequacy assessment is subject to the AHP model, calculating the weighting of various criteria including physical, socio-economic, environmental and urban. The final adequacy analysis revealed the proportion of land most suitable, estimated at 3.52% of the total area, covering mainly fallow land. The results of this study provide a detailed mapping of urban development potential, integrating both existing data and future projections.

Real-time localization with probabilistic maps and unscented kalman filtering: a dynamic sensor fusion approach

This paper presents a robust position estimation technique for autonomous vehicles navigating urban and highway environments. It employs a probabilistic framework, integrating Monte Carlo simulation and Bayesian filtering via particle filters to represent position estimates beyond Gaussian distributions. To improve accuracy, Unscented Kalman Filtering (UKF) is used to fuse radar and lidar data, facilitating the detection of static, pole-like objects. These objects are matched with landmarks from a detailed reference map generated through 3D lidar scans. The proposed method addresses both lateral and longitudinal localisation challenges, ensuring precise vehicle positioning. Comprehensive simulation tests validate the system's effectiveness, demonstrating reliable performance across various driving conditions.

Magnetometric and seismic investigation of the Nova Colinas impact structure, Parnaíba Basin, Brazil

Nova Colinas (NC) is a complex-type impact structure located in the northeast region of Brazil. It was formed in the volcano-sedimentary strata of the Parnaíba Basin, in the northern part of Western Gondwana. With an apparent diameter of approximately 6.5–7 km, its rim exhibits a distinctive magnetic signal, likely associated to basic volcanic rocks from the Mosquito Formation. These rocks present shock deformation, bracketing the maximum age of the impact event to 197 Ma. We use the magnetometric and seismic methods to establish the geophysical signature of NC and it is the structural framework in subsurface, as well as for characterizing the occurrence and extent of the volcanics. The magnetometric maps present two distinct magnetic domains in the region of NC: (i) the northern area is characterized by short-wavelength magnetic anomalies related to the basaltic flows of the Mosquito Formation; and (ii) the southern region, where sedimentary rocks from the Sambaiba Formation occur, which lacks significant magnetic anomalies, a typical pattern of siliciclastic sedimentary strata. The magnetic sources at the structure's rim reach an estimated depth of ∼250 m, and the position of the rim itself has been effectively established by the total horizontal derivative of the tilt derivative (THDR_TDR) technique. The regional magnetic anomaly suggests a deeper source at the center of the structure, possibly caused by strata with high magnetic susceptibility uplifted in the modification stage of crater formation. Magnetometric modeling using the magnetization vector inversion (MVI) method allowed detailed mapping of the volcanic rocks that form NC's rim. Additionally, analysis of the seismic data allowed the identification of two well-marked horizons, interpreted as diabase sills, located at depths of 600 m and 1200 m, respectively. Impact-related deformation represented by structures such as fractures, a central uplift, and reflector discontinuities associated with faulting, fracturing, and brecciation, were also unveiled by the seismic data, as well as the establishment of the depth of the crystalline basement at ca. 2200 m.

Mapping Tropical Dry Forest Gradients in an Andean Region with High Environmental Variability

Tropical Dry Forest (TDF) is one of the most threatened terrestrial environments in the neotropics because of high rates of conversion to agriculture. Despite this high degree of threat, many regions lack detailed maps on the actual extent and boundaries of their TDFs, which is fundamental information for their conservation. We developed a methodological framework to map TDF at 10 m in regions where they grade into other forest types. The approach uses climate variables, altitude, soil properties, and remote sensing data (multispectral and SAR − Synthetic Aperture Radar-SAR imagery) to predict TDF in the Department of Caldas, Colombia. Accuracy of the resulting map was confirmed with field observations (Overall Accuracy = 0.88, Kappa = 0.73, Area Under the Receiver Operating Characteristics Curve = 0.87, and True Skill Statistic = 0.73). We estimated ∼ 54 km2 of TDF, which represents 9.2 % of its potential area of occurrence in the study area. TDF gradually transitions to Tropical Moist Forest (TMF) from two main low altitude river valleys to higher altitudes in the Andes Mountains. With modification, our methods could be applied for mapping TDF in other tropical regions.

The Cibarco anticline of the northernmost San Jacinto fold belt: Possible influence of mud diapirism on the Neogene to the recent evolution of the structure where the first oil and gas wells were drilled in Colombia

The Cibarco anticline, located in the northwestern South American convergent margin, is a long (approximately 40 km) and narrow (2.5 km wide), south-southwest–north-northeast-trending structure that separates two much wider depocenters, the Tubará-Juan de Acosta depocenter (approximately 20 km wide) to the west, and the Sabanalarga syncline (approximately 11 km wide) to the east. Detailed geologic surface mapping and subsurface seismic interpretation suggest that the formation and evolution of the Cibarco anticline have been strongly influenced by mud diapirism, which has been focused along a west-southwest–east-northeast-trending, inverted pre-Oligocene extensional fault. Seismic interpretation and outcrop analyses also confirmed that the source of mobile shales is the Upper Oligocene marlstones of the Lower Ciénaga de Oro Formation. We suggest that the main mechanism that caused the overpressures that triggered and controlled shale mobilization was disequilibrium compaction related to the sedimentary loading of impermeable seals and the shortening and inversion of pre-Oligocene extensional faults. Growth strata indicate that the Upper Oligocene mud started moving in Early Miocene times during the deposition of the thick Porquero mudstones, and it stopped migrating in Latest Miocene times. After an uplift and erosion event, mud diapirism remained inactive in the Early Miocene, and it was then reactivated in Late Pliocene times. Slight mud migration focused on the inverted fault continued throughout the Pleistocene and to the present. Today, the slight mud migration to the surface is observed in volcanoes located in the northern strand of the Cibarco anticline, although the rest of the anticline has become welded. Our new interpretations, carried out more than a century after the first hydrocarbon exploration activities began in Colombia, will hopefully allow us to increase our understanding of shale tectonics, petroleum systems, and plays in this portion of the convergent margin.

Quantifying interstellar extinction at high galactic latitudes

Abstract A detailed map of the distribution of dust at high Galactic latitudes is essential for future cosmic microwave background (CMB) polarization experiments because the dust, while diffuse, remains a significant foreground in these regions. We develop a Bayesian model to identify a region of the Hertzsprung-Russell (HR) diagram suited to constrain the single-star extinction accurately at high Galactic latitudes. Using photometry from Gaia, 2MASS and ALLWISE, and parallax from Gaia, we employ nested sampling to fit the model to the data and analyse the posterior over stellar parameters for both synthetic and real data. Charting low variations in extinction is complex due to systematic errors and degeneracies between extinction and other stellar parameters. The systematic errors can be minimised by restricting our data to a region of the HR diagram where the stellar models are most accurate. Moreover, the degeneracies can be reduced by including astrophysical priors and spectroscopic constraints. We show that accounting for the measurement error of the data and the assumed inaccuracies of the stellar models are critical in accurately recovering small variations in extinction. We compare the posterior distribution for individual stars with spectroscopic stellar parameter estimates from LAMOST and Gaia ESO and illustrate the importance of estimating extinction and effective temperature as a joint solution.

Characteristics, impacts and future research directions of Mongolian peatlands

Mongolia is an important peatland distribution area in the world. Over the past few decades, Mongolian peatlands have undergone significant degradation due to climate change and human activities, yet there remains substantial uncertainty about the impacts of Mongolian peatland changes on regional environment and human society. Here, compiling the data of peatland distribution, climate, human activity, as well as the permafrost, we systematically review the distribution, changes, and the ecosystem service values of the Mongolian peatlands in the face of climate warming and intensifying human activities. The current data show that the total area of peatland in the Mongolian is 15500~27000 km2, and most of the peatlands are distributed in permafrost regions, while the accuracies of these maps were not assessed. In addition to climate warming, overgrazing, mining activities, and transportation, we suggest permafrost degradation also poses significant threatens on the peatlands. Although the importance of Mongolian peatlands has been recognized, the ecosystem service values, including water provision, habitat quality, carbon fixation, soil conservation, and wind erosion prevention largely remain unknown. Currently, efforts have been made to protect the Mongolian grassland, but there are no specific measures to combat peatland degradation. To better understand the changes and roles of peatland ecosystems in regulating regional development, we propose three research directions for future studies: 1) produce a detailed map of peatland distribution based on field survey data, new remote sensing data, and new algorithms; 2) Unveil the mechanisms underlying the interaction of peat, vegetation, and permafrost; 3) Evaluate the ecosystem services of Mongolian peatlands. These knowledges are the scientific foundation to propose and implement measures to protect, maintain, and sustainably utilize peatlands in Mongolia.

A comprehensive review of deep learning for medical image segmentation

Medical image segmentation provides detailed mappings of regions of interest, facilitating precise identification of critical areas and greatly aiding in the diagnosis, treatment, and understanding of diverse medical conditions. However, conventional techniques frequently rely on hand-crafted feature-based approaches, posing challenges when dealing with complex medical images, leading to issues such as low accuracy and sensitivity to noise. Recent years have seen substantial research focused on the effectiveness of deep learning models for segmenting medical images. In this study, we present a comprehensive review of the various deep learning-based approaches for medical image segmentation and provide a detailed analysis of their contributions to the domain. These methods can be broadly categorized into five groups: CNN-based methods, Transformer-based methods, Mamba-based methods, semi-supervised learning methods, and weakly supervised learning methods. Convolutional Neural Networks (CNNs), with their efficient feature self-learning, have driven major advances in medical image segmentation. Subsequently, Transformers, leveraging self-attention mechanisms, have achieved performance on par with or surpassing Convolutional Neural Networks. Mamba-based methods, as a novel selective state-space model, are emerging as a promising direction. Furthermore, due to the limited availability of annotated medical images, research in weakly supervised and semi-supervised learning continues to evolve. This review covers common evaluation methods, datasets, and deep learning applications in diagnosing and treating skin lesions, hippocampus, tumors, and polyps. Finally, we identify key challenges such as limited data, diverse modalities, noise, and clinical applicability, and propose future research in zero-shot segmentation, transfer learning, and multi-modal techniques to advance the development of medical image segmentation technology.

A Generic Transformation Approach for Complex Laboratory Data Using the Fast Healthcare Interoperability Resources Mapping Language: Method Development and Implementation.

Reaching meaningful interoperability between proprietary health care systems is a ubiquitous task in medical informatics, where communication servers are traditionally used for referring and transforming data from the source to target systems. The Mirth Connect Server, an open-source communication server, offers, in addition to the exchange functionality, functions for simultaneous manipulation of data. The standard Fast Healthcare Interoperability Resources (FHIR) has recently become increasingly prevalent in national health care systems. FHIR specifies its own standardized mechanisms for transforming data structures using StructureMaps and the FHIR mapping language (FML). In this study, a generic approach is developed, which allows for the application of declarative mapping rules defined using FML in an exchangeable manner. A transformation engine is required to execute the mapping rules. FHIR natively defines resources to support the conversion of instance data, such as an FHIR StructureMap. This resource encodes all information required to transform data from a source system to a target system. In our approach, this information is defined in an implementation-independent manner using FML. Once the mapping has been defined, executable Mirth channels are automatically generated from the resources containing the mapping in JavaScript format. These channels can then be deployed to the Mirth Connect Server. The resulting tool is called FML2Mirth, a Java-based transformer that derives Mirth channels from detailed declarative mapping rules based on the underlying StructureMaps. Implementation of the translate functionality is provided by the integration of a terminology server, and to achieve conformity with existing profiles, validation via the FHIR validator is built in. The system was evaluated for its practical use by transforming Labordatenträger version 2 (LDTv.2) laboratory results into Medical Information Object (Medizinisches Informationsobjekt) laboratory reports in accordance with the National Association of Statutory Health Insurance Physicians' specifications and into the HL7 (Health Level Seven) Europe Laboratory Report. The system could generate complex structures, but LDTv.2 lacks some information to fully comply with the specification. The tool for the auto-generation of Mirth channels was successfully presented. Our tests reveal the feasibility of using the complex structures of the mapping language in combination with a terminology server to transform instance data. Although the Mirth Server and the FHIR are well established in medical informatics, the combination offers space for more research, especially with regard to FML. Simultaneously, it can be stated that the mapping language still has implementation-related shortcomings that can be compensated by Mirth Connect as a base technology.