3D Database Research Articles

Spectral operator representations

Machine learning in atomistic materials science has grown to become a powerful tool, with most approaches focusing on atomic geometry, typically decomposed into local atomic environments. This approach, while well-suited for machine-learned interatomic potentials, is conceptually at odds with learning complex intrinsic properties of materials, often driven by spectral properties commonly represented in reciprocal space (e.g., band gaps or mobilities) which cannot be readily partitioned in real space. For such applications, methods that represent the electronic rather than the atomic structure could be more promising. In this work, we present a general framework focused on electronic-structure descriptors that take advantage of the natural symmetries and inherent interpretability of physical models. We apply this framework first to material similarity and then to accelerated screening, where a model trained on 217 materials correctly labels 75% of entries in the Materials Cloud 3D database, which meet common screening criteria for promising transparent-conducting materials.

A neurosurgical nursing training system based on 3D printing models: practice and exploration of precision medicine

BackgroundIn recent years, the concept of precision medicine has gradually permeated the field of nursing, presenting new challenges for neurosurgical nursing staff. Traditional teaching methods often struggle to adequately convey complex anatomical knowledge and nursing skills, thereby affecting the learning outcomes and clinical decision-making abilities of nurses. As an innovative educational tool, three-dimensional (3D) printing technology has demonstrated significant potential in medical education in recent years. Therefore, this project aims to explore the advantages and feasibility of using 3D printed models as a novel teaching tool in neurosurgical nursing.MethodsThe study involved 80 nursing personnel who participated in the neurosurgical rotation training at Shaoxing People’s Hospital from 2022 to 2023. The control group (40 individuals) used only traditional teaching tools such as textbooks, multimedia courseware, and laboratory equipment for theoretical and practical training based on the curriculum. The experimental group (40 individuals) incorporated a 3D printing model database as an innovative teaching tool on the basis of traditional teaching methods, and used patient-specific 3D printed models for precise nursing training. After the training, both groups were assessed for theoretical and practical abilities, professional values, job satisfaction, and the prognosis of intracranial aneurysm patients they cared for.ResultsThe experimental group demonstrated superior scores in theoretical and practical abilities, professional values, and job satisfaction compared to the control group. During the training period, patients with intracranial aneurysms receiving precision nursing care from the experimental group showed better quality of life and neurological functional outcomes compared to the control group.ConclusionsThe nursing training system based on 3D printing models can enhance the learning efficiency and nursing work satisfaction of nursing personnel. It may have a positive impact on the professional values of nursing personnel, thereby laying a solid foundation for providing high-quality, precise nursing services in the field of neurosurgery in the future.

BIM/IFC as input for registering apartment rights in a 3D Land Administration Systems – A prototype webservice

The need for 3D Land Administration Systems (LAS) is growing. In this respect, research is carried out in the field of 3D LAS with respect to data sources, registration of 3D Rights, Restrictions and Responsibilities and dissemination services. Within this context, BIM/IFC models are considered promising sources for 3D LAS, even though the reuse of such models from practice has not yet been examined adequately. Evaluating BIM/IFC-models from practice is crucial, since they are created for different purposes, fulfilling various design criteria. This paper investigates the technical challenges encountered when using real-world BIM/IFC-models for apartment rights’ registration in a 3D LAS. It addresses the validation of five Dutch real-world BIM/IFC-models against four technical criteria, namely: existence of IfcSpace; geometric validity; no overlap and georeferencing. The results of the validation show that the collected BIM/IFC-models lack georeference, IfcSpace and a reference to attributes related to the respective legal units in the Dutch 3D LAS. After validation the models are stored in a 3D LAS Database management system (DBMS), in which the legal spaces are enriched with information of the Rights, Restrictions and Responsibilities (RRR’s) in line with the Land Administration Domain Model (LADM - ISO 19152:2012). The contents of the 3D LAS DBMS are visualised in a web viewer. Additionally, the design for a webservice is introduced, aiming to automate the process of validation, conversion and visualisation. The paper concludes with recommendations and guidelines for creators of BIM/IFC-models based on the outcome of the validation, as well as challenges and recommendations for implementing a validation webservice.

A fast methodology for identifying thermal parameters based on improved POD and particle swarm optimization and its applications

The identification method based on the traditional Proper Orthogonal Decomposition (POD) reduced-order model has the problem of low efficiency, due to the large amount of both data and computation, when dealing with complicated problems with a large number of spatially distributed nodes. To deal with this issue, an improved POD reduced-order model is proposed in this work. The improved POD reduced-order model only requires the establishment of a three-dimensional (3D) database of training samples varied with both time and measurement locations. Therefore, the amount of data and computation is independent of the total number of spatially distributed nodes, which enables the amount of data and computation to be greatly reduced. To identify thermal parameters in heat conduction problems, a database of transient temperature field is constructed with different training parameters and space nodes by using polygonal boundary element method, and a set of POD basis vectors is obtained by the POD reduced-order model. Then, a surrogate model combined with the improved particle swarm optimization (PSO) is employed for the identification of thermal parameters. Three different inverse heat conduction problems are designed and analyzed to verify the performance of the improved methodology. The results show that the efficiency of the modified method is superior to the traditional POD method with comparable accuracy. The more of the number of spatially distributed nodes, the more obvious advantages of the efficiency. Furthermore, this method has been tested on noisy data, proving its reliability in dealing with problems arising from measurement errors.

High-throughput magnetic co-doping and design of exchange interactions in topological insulators

Using high-throughput automation of impurity embedding simulations, we create a database of 3d and 4d transition metal defects embedded into the prototypical topological insulators (TIs) Bi2Te3 and Bi2Se3. We simulate both single impurities as well as impurity dimers at different impurity-impurity distances inside the topological insulator matrix. We extract changes to magnetic moments, analyze the polarizability of nonmagnetic impurity atoms via nearby magnetic impurity atoms and calculate the exchange coupling constants for a Heisenberg Hamiltonian. We uncover chemical trends in the exchange coupling constants and discuss the impurities' abilities with respect to magnetic order in the fields of quantum anomalous Hall insulators and topological quantum computing. In particular, we confirm that co-doping of different magnetic dopants is a viable strategy to engineer the magnetic ground state in magnetic TIs. Published by the American Physical Society 2024

Three-dimensional reconstruction of laser-direct-drive inertial confinement fusion hot-spot plasma from x-ray diagnostics on the OMEGA laser facility (invited).

A deep-learning convolutional neural network (CNN) is used to infer, from x-ray images along multiple lines of sight, the low-mode shape of the hot-spot emission of deuterium-tritium (DT) laser-direct-drive cryogenic implosions on OMEGA. The motivation of this approach is to develop a physics-informed 3-D reconstruction technique that can be performed within minutes to facilitate the use of the results to inform changes to the initial target and laser conditions for the subsequent implosion. The CNN is trained on a 3D radiation-hydrodynamic simulation database to relate 2D x-ray images to 3D emissivity at stagnation. The CNN accounts for the lack of an absolute spatial reference and the different bands of photon energies in the x-ray images. While previous work [O. M. Mannion etal., Phys. Plasmas 28, 042701 (2021) and A. Lees etal., Phys. Rev. Lett. 127, 105001 (2021)] studied the effect of mode-1 asymmetries on implosion performance using nuclear diagnostics, this work focuses on the effect of mode 2 inferred from x-ray diagnostics on implosion performance. A current analysis of 19 DT cryogenic implosions indicates there is an upper limit of ∼20% reduction in the neutron yield caused by an ℓ = 2 amplitude for ℓ2/ℓ0 ≤ 0.32. These conclusions are supported by 2D simulations.

3D Geological Modeling and Metallogenic Prediction of Kamust Sandstone-Type Uranium Deposit in the Eastern Junggar Basin, NW China

Sandstone-type uranium deposits hold significant value and promise within China’s uranium resource portfolio, with the majority of these deposits found at the junctions of basins and mountains within Mesozoic and Cenozoic basins. The Kamust uranium mining area, located in the eastern part of the Junggar Basin, represents a significant recent discovery. Prior research on this deposit has been confined to two-dimensional analyses, which pose limitations for a comprehensive understanding of the deposit’s three-dimensional characteristics. To address the issue of uranium resource reserve expansion, this study employs 3D geological modeling and visualization techniques, guided by uranium deposit models and mineral prediction methods. First, a 3D model database of the Kamust uranium deposit was constructed, comprising drill holes, uranium ore bodies, ore-controlling structures, interlayer oxidation zones, and provenance areas. This model enables a transparent and visual representation of the spatial distribution of favorable mineralization horizons, structures, stratigraphy, and other predictive elements in the mining area. Second, based on the three-dimensional geological model, a mineral prediction model was established by summarizing the regional mineralization mechanisms, ore-controlling factors, and exploration indicators. Combined with big-data technology, this approach facilitated the quantitative analysis and extraction of ore-controlling factors, providing data support for the three-dimensional quantitative prediction of deep mineralization in the Kamust uranium deposit. Finally, using three-dimensional weights of evidence and three-dimensional information-quantity methods, comprehensive information analysis and quantitative prediction of deep mineralization were conducted. One prospective area was quantitatively delineated, located east of the Kalasay monocline, which has been well-validated in geological understanding. The research indicates that the area east of the Kalasay monocline in the Kamust mining district has significant exploration potential.

3D whole body preclinical micro-CT database of subcutaneous tumors in mice with annotations from 3 annotators

A pivotal animal model for development of anticancer molecules is mice with subcutaneous tumors, grown by injection of xenografted tumor cells, where micro-Computed Tomography (µCT) of the mice is used to analyze the efficacy of the anticancer molecule. Manual delineation of the tumor region is necessary for the analysis, which is time-consuming and inconsistent, highlighting the need for automatic segmentation (AS) tools. This study introduces a preclinical µCT database, comprising 452 whole-body scans from 223 individual mice with subcutaneous tumors, spanning ten diverse µCT datasets conducted between 2014 and 2020 on a preclinical PET/CT scanner, making it the hitherto largest dataset of its kind. Each tumor is annotated manually by three expert annotators, allowing for robust model development. Inter-annotator agreement was analyzed, and we report an overall annotation agreement of 0.903 ± 0.046 (mean ± std) Fleiss’ Kappa and a mean deviation in volume estimation of 0.015 ± 0.010 cm3 (6.9% ± 4.7), which establishes a human baseline accuracy for delineation of subcutaneous tumors, while showing good inter-annotator agreement.

Immersive Photorealistic Three-Dimensional Neurosurgical Anatomy of the Cerebral Arteries: A Photogrammetry-Based Anatomic Study.

Neurosurgeons need a profound knowledge of the surgical anatomy of the cerebral arteries to safely treat patients. This is a challenge because of numerous branches, segments, and tortuosity of the main blood vessels that supply the brain. The objective of this study was to create high-quality three-dimensional (3D) anatomic photorealistic models based on dissections of the brain arterial anatomy and to incorporate this data into a virtual reality (VR) environment. Two formaldehyde-fixed heads were used. The vessels were injected with radiopaque material and colored silicone and latex. Before the dissections, the specimens were computed tomography scanned. Stratigraphical anatomic dissection of the neck and brain was performed to present the relevant vascular anatomy. A simplified surface scanning method using a mobile phone-based photogrammetry application was used, and the data were incorporated into a VR 3D modeling software for post-processing and presentation. Fifteen detailed layered photorealistic and two computed tomography angiography-based 3D models were generated. The models allow manipulation in VR environment with sufficient photographic detail to present the structures of interest. Topographical relevant anatomic structures and landmarks were annotated and uploaded for web-viewing and in VR. Despite that the VR application is a dedicated 3D modeling platform, it provided all necessary tools to be suitable for self-VR study and multiplayer scenarios with several participants in one immersive environment. Cerebral vascular anatomy presented with photogrammetry surface scanning method allows sufficient detail to present individual vessel's course and even small perforating arteries in photorealistic 3D models. These features, including VR visualization, provide new teaching prospects. The whole study was done with simplified algorithms and free or open-source software platforms allowing creation of 3D databases especially useful in cases with limited body donor-based dissection training availability.

Enhancing educational experience through establishing a VR database in craniosynostosis: report from a single institute and systematic literature review.

Craniosynostosis is a type of skull deformity caused by premature ossification of cranial sutures in children. Given its variability and anatomical complexity, three-dimensional visualization is crucial for effective teaching and understanding. We developed a VR database with 3D models to depict these deformities and evaluated its impact on teaching efficiency, motivation, and memorability. We included all craniosynostosis cases with preoperative CT imaging treated at our institution from 2012 to 2022. Preoperative CT scans were imported into SpectoVR using a transfer function to visualize bony structures. Measurements, sub-segmentation, and anatomical teaching were performed in a fully immersive 3D VR experience using a headset. Teaching sessions were conducted in group settings where students and medical personnel explored and discussed the 3D models together, guided by a host. Participants' experiences were evaluated with a questionnaire assessing understanding, memorization, and motivation on a scale from 1 (poor) to 5 (outstanding). The questionnaire showed high satisfaction scores (mean 4.49 ± 0.25). Participants (n = 17) found the VR models comprehensible and navigable (mean 4.47 ± 0.62), with intuitive operation (mean 4.35 ± 0.79). Understanding pathology (mean 4.29 ± 0.77) and surgical procedures (mean 4.63 ± 0.5) was very satisfactory. The models improved anatomical visualization (mean 4.71 ± 0.47) and teaching effectiveness (mean 4.76 ± 0.56), with participants reporting enhanced comprehension and memorization, leading to an efficient learning process. Establishing a 3D VR database for teaching craniosynostosis shows advantages in understanding and memorization and increases motivation for the study process, thereby allowing for more efficient learning. Future applications in patient consent and teaching in other medical areas should be explored.

Synthetic ground motions in heterogeneous geologies from various sources: the HEMEWS-3D database

Abstract. The ever-improving performances of physics-based simulations and the rapid developments of deep learning are offering new perspectives to study earthquake-induced ground motion. Due to the large amount of data required to train deep neural networks, applications have so far been limited to recorded data or two-dimensional (2D) simulations. To bridge the gap between deep learning and high-fidelity numerical simulations, this work introduces a new database of physics-based earthquake simulations. The HEterogeneous Materials and Elastic Waves with Source variability in 3D (HEMEWS-3D) database comprises 30 000 simulations of elastic wave propagation in 3D geological domains. Each domain is parametrized by a different geological model built from a random arrangement of layers augmented by random fields that represent heterogeneities. Elastic waves originate from a randomly located pointwise source parametrized by a random moment tensor. For each simulation, ground motion is synthesized at the surface by a grid of virtual sensors. The high frequency of waveforms (fmax⁡=5 Hz) allows for extensive analyses of surface ground motion. Existing and foreseen applications range from statistical analyses of the ground motion variability and machine learning methods on geological models to deep-learning-based predictions of ground motion that depend on 3D heterogeneous geologies and source properties. Data are available at https://doi.org/10.57745/LAI6YU (Lehmann, 2023).

No-reference stereoscopic image quality assessment based on binocular collaboration

Stereoscopic images typically consist of left and right views along with depth information. Assessing the quality of stereoscopic/3D images (SIQA) is often more complex than that of 2D images due to scene disparities between the left and right views and the intricate process of fusion in binocular vision. To address the problem of quality prediction bias of multi-distortion images, we investigated the visual physiology and the processing of visual information by the primary visual cortex of the human brain and proposed a no-reference stereoscopic image quality evaluation method. The method mainly includes an innovative end-to-end NR-SIQA neural network with a picture patch generation algorithm. The algorithm generates a saliency map by fusing the left and right views and then guides the image cropping in the database based on the saliency map. The proposed models are validated and compared based on publicly available databases. The results show that the model and algorithm together outperform the state-of-the-art NR-SIQA metric in the LIVE 3D database and the WIVC 3D database, and have excellent results in the specific noise metric. The model generalization experiments demonstrate a certain degree of generality of our proposed model.

Possibility of 3D Model Collections with LiDAR: Simply, Easily, and Inexpensively in Paleontology

Until several years ago, it was difficult for the general public to acquire 3D data. Recently, portable devices have been equipped with LiDAR (Light Detection And Ranging). LiDAR is a method for determining ranges by targeting an object or a surface with a laser and measuring the time for the reflected light to return to the receiver. It is easy to acquire 3D data by LiDAR at low cost, so making 3D digital specimens and using 3D databases have become more popular. This study aims to to investigate the possibility of creating 3D digital model collections in paleontology using a simple, easy and inexpensive approach that applies portable devices equipped with LiDAR. Two Apple iPad Pro® (3rd and 4th generation) and an iPhone® 15 Pro equipped with LiDAR are used with the Scaniverse application. The scanning distance of Scaniverse is from 0.3 m to 5.0 m for 3D modelling. Targets of paleontological 3D models in our study, range from hand-sized specimens to exhibits several meters in size, exhibition rooms and outcrops, including a 5 cm ammonite and an ~3 m full-body replica of Naumann’s elephant, Palaeoloxodon naumanni. In this case study, it was difficult to make 3D models of specimens under 10 cm diameter. On the other hand, 3D modelling of specimens greater than 10 cm, and up to 5 m long produced reasonable results. These 3D model collections can be used as exhibits and for education by making 3D printings and virtual reality (VR) models. Because the LiDAR technology is now built into common devices, problems may arise because anyone could make and share 3D models simply, easily, and inexpensively. Several issues of ownership, such as copyright, could arise from creating these models because digital data policies are not uniform or codified between museums and institutions. In the future, rules to govern these collections internationally need to be developed.

MeshWGAN: Mesh-to-Mesh Wasserstein GAN With Multi-Task Gradient Penalty for 3D Facial Geometric Age Transformation.

As the metaverse develops rapidly, 3D facial age transformation is attracting increasing attention, which may bring many potential benefits to a wide variety of users, e.g., 3D aging figures creation, 3D facial data augmentation and editing. Compared with 2D methods, 3D face aging is an underexplored problem. To fill this gap, we propose a new mesh-to-mesh Wasserstein generative adversarial network (MeshWGAN) with a multi-task gradient penalty to model a continuous bi-directional 3D facial geometric aging process. To the best of our knowledge, this is the first architecture to achieve 3D facial geometric age transformation via real 3D scans. As previous image-to-image translation methods cannot be directly applied to the 3D facial mesh, which is totally different from 2D images, we built a mesh encoder, decoder, and multi-task discriminator to facilitate mesh-to-mesh transformations. To mitigate the lack of 3D datasets containing children's faces, we collected scans from 765 subjects aged 5-17 in combination with existing 3D face databases, which provided a large training dataset. Experiments have shown that our architecture can predict 3D facial aging geometries with better identity preservation and age closeness compared to 3D trivial baselines. We also demonstrated the advantages of our approach via various 3D face-related graphics applications.

RADIOTHERAPY 3D ISODOSEZONES GRAPHICAL OPTIMIZATION FOR HYPERFRACTIONATED TREATMENT PLANNING DOSIMETRY IN LUNG AND HEAD-NECK TUMORS WITH BIOLOGICAL EFFECTIVE DOSE MODEL

In recent lung and prostate cancer-radiotherapy contributions, [101-5], 3D imaging-processing Isodosezones [ Casesnoves, 2022 ], delimited by 3D Isodoselines were explained in lung cancer and other tumor types, such as prostate or lung. The radiotherapy model applied was the classical BED one algorithm. Modern biological-model-based Treatment Planning Optimization can get objective improvements by using Isodosezones/lines when selecting the optimal dose delivery/schedule for any personalized treatment. Improved programming, from [ Casesnoves, May 7th, 2024 ], and engineered software is perfectioned-developed for numerical hyperfractionated 3D TPO lung and head-neck cancer imaging-processing with upgraded previous database. Mathematical algorithms are explained-detailed. Developed programming patters and arrays are briefed. A series of imaging-processing graphics results obtained with the 3D Isodosezones Pareto-Multiobjective Optimization programming database are shown and explained in detailed. Applications in radiotherapy-oncology medical physics are subsequently briefed.

Перспектива развития VR-технологий в образовании и социальной жизни

VR-based technologies are in demand in modern education. They create virtual environment and simulate processes similar to real ones. As a result, students can practice actions that form and consolidate the necessary competencies. This article describes the possibilities of using virtual reality to teach food-industry university students to design production sites, e.g., an independent virtual simulation where students could work on their own projects and developments. The proposed technology offers an improved import-substituting software that creates realistic models of food production, e.g., virtual food processing workshops where students could test and improve their skills in dealing with key parameters and technological processes. The program recreates technological solutions in virtual reality, which simplifies, speeds up, and reduces the cost of developing skills in production site design. This application is the most promising direction for VR technology in education. The software product was developed in the VR laboratory of Kemerovo State University. It allows students to design industrial buildings of various sizes, workshops, and production facilities of various capacities, as well as public catering places and their interior, open public spaces, e.g., city parks, etc. The product has a database for storing and using education materials, design blanks, and ready-made 3D models of equipment created in Unreal Engine. The 3D model database contains digital models of real-life devices and equipment used at food industry enterprises. The projects can be displayed in a visual digital environment to study the principles of equipment operation, monitor and change their parameters, and simulate faults and deviations. The database makes it possible to design small enterprises and large industrial complexes for food production in virtual environment.

Three-dimensional characterization of particle size, shape, and internal porosity for Apollo 11 and Apollo 14 lunar regolith and JSC-1A lunar regolith soil simulant

Samples of soils collected by the Apollo 11 mission (10084,2036) and the Apollo 14 mission (14163,940) were obtained from the NASA Curation and Analysis Planning Team for Extraterrestrial Materials (CAPTEM) program. The particle size, shape, and internal porosity were characterized in three dimensions (3D) using a combination of X-ray computed tomography (XCT) and mathematical analysis, with various size and shape parameters measured and calculated for each particle. High-resolution scanning electron microscopy (SEM) was used to image the particles that were too small for the two XCT instruments used. Similar characterization was carried out on samples of JSC-1A lunar soil simulant, updating a previous analysis. Approximately 14,000 lunar regolith particles and 128,000 JSC1-A particles, covering a wide range of size and shape, were characterized for this paper and the results stored in a publicly accessible database. This large number of particles enabled, for the first time, statistically valid particle shape distributions to be generated. The 3D shape distributions of the two regoliths and JSC-1A were quantitatively compared and it was found that the way particle shape and porosity depends on particle size was different between regolith and simulant. The measured size distribution of particles in the lunar soils was applied to estimate the relative contributions of different sizes to the ensemble average particle single scattering albedo and phase function. By linking our particle counts to published sieve weight fractions for the lunar samples, we find that ∼80% of the total cross-section area is contributed by particles <20 μm diameter and ∼ 50% by particles <8 μm diameter. The orientation-averaged two-dimensional projected areas of the actual regolith particles were computed so that this estimate was also based on real particle shapes. Such small sizes dominating the total cross-section area suggest that calculations of the elements of the scattering matrix for individual particles may be possible with modest computing capabilities leading to the development of improved models for the quantitative interpretation of remote sensing spectrophotometry and polarimetry. This 3D characterization and database will enable other computational work to be done with real lunar regolith particle shapes, including discrete element method mechanical modeling, packing simulations, further light scattering calculations, dust contamination modeling, and modeling of lunar rover interactions with collected and packed regolith particles.

Neotectonics on the Namuncurá (Burdwood) Bank: unveiling seafloor strike-slip processes along the North Scotia Ridge

The North Scotia Ridge is the offshore morphostructural expression of the left-lateral transcurrent South America–Scotia plate boundary. Several blocks make up the ridge, including the scarcely studied Namuncurá Bank (also known as the Burdwood Bank). We present the first detailed study of active structures on the seafloor of the western Namuncurá Bank from a database of 3D and 2D seismic data, multibeam bathymetry and sub-bottom profiles. This work assesses the architecture, style of deformation and Cenozoic evolution of Namuncurá Bank, where several groups of faults and en echelon folding affect the seabed and shallow sub-bottom. These features compound the northernmost structures associated with a releasing bend, fitting well with a left-lateral Riedel shear model oriented at N74°E, slightly rotated with respect to the present day plate boundary stress regime. The current tectonic scenario started with a main deformational phase in the Neogene, partially distributed by the Malvinas fold–thrust belt, while modern deformation continues to be conditioned by pre-existing structures. This study allows a better understanding of the tectonics of the North Scotia Ridge, a morphostructure that influences the circulation of the Antarctic Circumpolar Current, thus impacting the global climate.

A multi-level quantitative analysis method on the scale, shape and quantity of rockeries in Chinese classical gardens: taking Wanfang Anhe rockery in the Old Summer Palace as an example

Currently, the use of digital technology for the protection and research of cultural heritage has become a trend in this field. Rockeries in Chinese classical gardens have become an important cultural heritage type because of their unique shape, ingenious skills and rich connotations. Based on relevant historical information and 3D digital technology, this paper puts forward a multi-level quantitative analysis method on the scale, shape and quantity of rockeries in Chinese classical gardens, aiming at exploring the objective description and quantitative analysis path of rockeries at different levels. This method develops four levels: overall, regional, hierarchical, and individual and their corresponding quantitative contents, which in turn enable data extraction and analysis of the rockery through the different levels. The proposed method was applied to seven different Chinese classical garden rockeries, and taking Wanfang Anhe Rockery in the Old Summer Palace as an example for objective and comprehensive quantitative analysis and verification. The results show that this method is feasible and effective for quantitative analysis of the scale, shape and quantity of rockeries, which can help understand the basic background of stone rockeries and enhance a refined understanding of stone rockery construction, thereby providing data for preventive protection and informatization management of stone rockeries. The 3D rockery model database based on the overall, regional, hierarchical and individual quantitative analysis and numbering method brings a good application prospect for preventive protection and informatization management of the rockery.

From EU-SoilHydroGrids to HU-SoilHydroGrids: A leap forward in soil hydraulic mapping

Spatially explicit, quantitative information on soil hydraulic properties is required in various modelling schemes. At European scale, EU-SoilHydroGrids proved its applicability in a number of studies, in ecological predictions, geological and hydrological hazard assessment, agri-environmental models, among others. Inspired by its continental antecedent, an analogous, but larger scale, national, 3D soil hydraulic database was elaborated for the territory of Hungary (HU-SoilHydroGrids) supported by various improvements (i–iv) in the computation process. Pedotransfer functions (PTFs) were built in the form of i) advanced machine learning methods and ensemble models, and trained on the ii) national soil hydrophysical dataset. The set of predictors used in PTFs was supplemented by iii) additional environmental auxiliary variables. Spatial layers of the soil hydraulic parameters were generated using iv) 100 m resolution information on primary soil properties, namely DOSoReMI.hu. HU-SoilHydroGrids provides information on the most frequently required soil hydraulic properties (water content at saturation, field capacity and wilting point, saturated hydraulic conductivity and van Genuchten parameters for the description of the moisture retention curve) with national coverage at 100 m spatial resolution down to 2 m depth for six GSM standard depth layers. The HU-SoilHydroGrids has significantly lower squared error in the case of describing the moisture retention curve and hydraulic conductivity than the EU-SoilHydroGrids. The derived 3D soil hydraulic database (ver1.0) is presently available in National Laboratory for Water Science and Water Safety for project partners in order to test its functional performance in describing hydrological and ecological processes.