3D Density Research Articles

SELECTED QUALITATIVE ASPECTS OF LIDAR POINT CLOUDS: GEOSLAM ZEB-REVO AND FARO FOCUS 3D X130

Abstract. This paper presents a comparison of LiDAR point clouds acquired using two, different measurement techniques: static TLS (Terrestrial Laser Scanning) performed with a FARO Focus3D X130 laser scanner and a SLAM-based (Simultaneous Localization and Mapping) unit of MLS (Mobile Laser Scanning), namely GeoSLAM ZEB-REVO. After the two point clouds were brought into a single coordinate system, they were compared with each other in terms of internal accuracy and density. The density aspect was visualized using 2D density rasters, and calculated using 3 methods available in CloudCompare software. Thus, one should consider before choosing how to acquire a LiDAR point cloud whether a short measurement time is more important (ZEB-REVO) or whether higher density and measurement accuracy is more important (FARO Focus3D X130). In BIM/HBIM modeling applications, logic dictates that the TLS solution should be chosen, despite the longer data acquisition and processing time, but with a cloud with far better quality parameters that allow objects on the point cloud to be recognized. In a situation where the TLS point cloud is 20 times more dense, it allows to model objects at the appropriate level of geometric detail.

Nanoscale Three-Dimensional Network Structure of a Mesoporous Particle Unveiled via Adaptive Multidistance Coherent X-ray Tomography.

Mesoporous nanoparticles provide rich platforms to devise functional materials by customizing the three-dimensional (3D) structures of nanopores. With the pore network as a key tuning parameter, the noninvasive and quantitative characterization of these 3D structures is crucial for the rational design of functional materials. This has prompted researchers to develop versatile nanoprobes with a high penetration power to inspect various specimens sized a few micrometers at nanoscale 3D resolutions. Here, with adaptive phase retrievals on independent data sets with different sampling frequencies, we introduce multidistance coherent X-ray tomography as a noninvasive and quantitative nanoprobe to realize high-resolution 3D imaging of micrometer-sized specimens. The 3D density distribution of an entire mesoporous silica nanoparticle was obtained at 13 nm 3D resolution for quantitative physical and morphological analyses of its 3D pore structure. The morphological features of the whole 3D pore network and pore connectivity were examined to gain insight into the potential functions of the particles. The proposed multidistance tomographic imaging scheme with quantitative structural analyses is expected to advance studies of functional materials by facilitating their structure-based rational design.

Tides in clouds: control of star formation by long-range gravitational force

ABSTRACT Gravity drives the collapse of molecular clouds through which stars form, yet the exact role of gravity in cloud collapse remains a complex issue. Studies point to a picture where star formation occurs in clusters. In a typical, pc-sized cluster-forming region, the collapse is hierarchical, and the stars should be born from regions of even smaller sizes (${\approx} 0.1\,\rm pc$). The origin of this spatial arrangement remains under investigation. Based on a high-quality surface density map towards the Perseus region, we construct a 3D density structure, compute the gravitational potential, and derive eigenvalues of the tidal tensor (λmin, λmid, λmax, λmin < λmid < λmax), analyse the behaviour of gravity at every location, and reveal its multiple roles in cloud evolution. We find that fragmentation is limited to several isolated, high-density ‘islands’. Surrounding them, is a vast amount of the gas ($75~{{ \rm per\ cent}}$ of the mass, $95~{{ \rm per\ cent}}$ of the volume) that stays under the influence of extensive tides where fragmentation is suppressed. This gas will be transported towards these regions to fuel star formation. The spatial arrangement of regions under different tides explains the hierarchical and localized pattern of star formation inferred from the observations. Tides were first recognized by Newton, yet this is the first time its dominance in cloud evolution has been revealed. We expect this link between cloud density structure and role gravity to be strengthened by future studies, resulting in a clear view of the star formation process.

Multiscale structural analyses of Mesozoic shallow-water carbonates, Viggiano Mt., southern Italy

The high-angle faults bounding the High Agri Valley Basin eastwards are well-exposed at the Viggiano Mt., southern Italy. There, these faults crosscut Mesozoic shallow-water carbonates and permit the multiscale analyses of fault and fracture geometry and distribution. Aiming at assessing the control exerted by carbonate lithofacies and scales of observation, we combine field and digital structural analyses to compute the values of 1D and 2D fracture density and intensity, and the dimensional properties of single fault and fracture sets. As a result, from outcrop to reservoir scales we document a scale-variant geometry of faults and fractures, and the great variation of both fracture density and intensity among the studied carbonate lithofacies. Furthermore, we compute a P21 dimensional scaling factor of ca. 20 for over 3 order magnitude, whereas inconsistent results are achieved for the P20 values. Not considering the control exerted by the single carbonate lithofacies, at a reservoir scale we document that the small-scale faults greatly impact the computed P21 values.

Comparison of distance measurements to dust clouds using GRB X-ray haloes and 3D dust extinction

ABSTRACT X-ray photons from energetic sources such as gamma-ray bursts (GRBs) can be scattered on dust clouds in the Milky Way, creating a time-evolving halo around the GRB position. X-ray observations of such haloes allow the measurement of dust cloud distances in the Galaxy on which the scattering occurs. We present the first systematic comparison of the distances to scattering regions derived from GRB haloes with the 3D dust distribution derived from recently published optical-to-near infrared extinction maps. GRB haloes were observed around seven sources by the Swift XRT and the XMM–Newton EPIC instruments, namely GRB 031203, GRB 050713A, GRB 050724, GRB 061019, GRB 070129, GRB 160623A, and GRB 221009A. We used four 3D extinction maps that exploit photometric data from different surveys and apply diverse algorithms for the 3D mapping of extinction, and compared the X-ray halo-derived distances with the local maxima in the 3D extinction density distribution. We found that in all GRBs, we can find at least one local maximum in the 3D dust extinction map that is in agreement with the dust distance measured from X-ray rings. For GRBs with multiple X-ray rings, the dust distance measurements coincide with at least three maxima in the extinction map for GRB 160623A, and five maxima for GRB 221009A. The agreement of these independent distance measurements shows that the methods used to create dust extinction maps may potentially be optimized by the X-ray halo observations from GRBs.

An Efficient Breast Cancer Detection Using Jelly Electrophorus Optimization Based Deep 3D Convolution Neural Networks (CNN)

Breast cancer is one of the world’s most serious diseases that affect millions of women every year, and the number of people affected is increasing. The only practical way to lessen the impact of a disease is through early detection. Researchers have developed a variety of methods for identifying breast cancer, and using histopathology images as a tool has been quite successful. As an enhancement, this research develops a jelly electrophorus optimization-based 3D density connected deep Convolution Neural Networks (CNN) for the identification of breast cancer using histopathology images and input is collected and pre-processing is performed for improve the histopathology image’s properties. Then the feature extraction is performed through VGG-16, AlexNet, ResNet-101, statistical features. Finally, these concatenated features are fed forwarded to 3D density connected 3D deep Convolution Neural Networks (CNN) classifier it automatically detects breast cancer effectively with the help of jelly electrophorus optimization. The proposed jelly electrophorus optimization adjusts the classifier’s weights and bias. In terms of accuracy, sensitivity, and specificity, the proposed JEO-3D deep Convolution Neural Networks (CNN) approach attains values of 93.73%, 95.31%, and 94.14% for dataset 1 and 88.75%, 90.32%, and 89.15% for dataset 2, which is more successful.

The Accuracy Assessment of Lithospheric Density Models

The Earth’s synthetic gravitational and density models can be used to validate numerical procedures applied for global (or large-scale regional) gravimetric forward and inverse modeling. Since the Earth’s lithospheric structure is better constrained by tomographic surveys than a deep mantle, most existing 3D density models describe only a lithospheric density structure, while 1D density models are typically used to describe a deep mantle density structure below the lithosphere-asthenosphere boundary. The accuracy of currently available lithospheric density models is examined in this study. The error analysis is established to assess the accuracy of modeling the sub-lithospheric mantle geoid while focusing on the largest errors (according to our estimates) that are attributed to lithospheric thickness and lithospheric mantle density uncertainties. Since a forward modeling of the sub-lithospheric mantle geoid also comprises numerical procedures of adding and subtracting gravitational contributions of similar density structures, the error propagation is derived for actual rather than random errors (that are described by the Gauss’ error propagation law). Possible systematic errors then either lessen or sum up after applying particular corrections to a geoidal geometry that are attributed to individual lithospheric density structures (such as sediments) or density interfaces (such as a Moho density contrast). The analysis indicates that errors in modeling of the sub-lithospheric mantle geoid attributed to lithospheric thickness and lithospheric mantle density uncertainties could reach several hundreds of meters, particularly at locations with the largest lithospheric thickness under cratonic formations. This numerical finding is important for the calibration and further development of synthetic density models of which mass equals the Earth’s total mass (excluding the atmosphere). Consequently, the (long-to-medium wavelength) gravitational field generated by a synthetic density model should closely agree with the Earth’s gravitational field.

Aqua3DNet: Real-time 3D pose estimation of livestock in aquaculture by monocular machine vision

We present a low-cost monocular 3D position estimation method for perception in aquaculture monitoring. Video surveillance of aquaculture has many advantages but given the size of farms and the complexity of their habitats, it is not feasible for farmers to continuously monitor fish health. We formulate a novel end-to-end deep visual learning pipeline called Aqua3DNet that estimates fish pose using a bottom-up approach to detect and assign key features in one pass. In addition, a depth estimation model using Saliency Object Detection (SOD) masks is implemented to track the 3D position of the fish over time, which is used in this paper to create 3D density heat maps of the fish. The evaluation of the algorithm's performance shows that the detection accuracy reaches 80.63%, the F1 score reaches 87.34%, and the frames per second (fps) reaches 5.12. Aqua3DNet achieves comparable performance to other aquaculture-based computer vision and depth estimation models, with minimal decrease in speed despite the synthesis of the two models.

Toward a 3D kinetic tomography of Taurus clouds

Context. Three-dimensional (3D) kinetic maps of the Milky Way interstellar medium are an essential tool in studies of its structure and of star formation. Aims. We aim to assign radial velocities to Galactic interstellar clouds now spatially localized based on starlight extinction and star distances from Gaia and stellar surveys. Methods. We developed an automated search for coherent projections on the sky of clouds isolated in 3D extinction density maps on the one hand, and regions responsible for CO radio emissions at specific Doppler shifts on the other hand. The discrete dust structures were obtained by application of the Fellwalker algorithm to a recent 3D extinction density map. For each extinction cloud, a technique using a narrow sliding spectral window moved along the contour-bounded CO spectrum and geometrical criteria was used to select the most likely velocity interval. Results. We applied the new contour-based technique to the 3D extinction density distribution within the volume encompassing the Taurus, Auriga, Perseus, and California molecular complexes. From the 45 clouds issued from the decomposition, 42 were assigned a velocity. The remaining structures correspond to very weak CO emission or extinction. We used the non-automated assignments of radial velocities to clouds of the same region presented in Paper I and based on KI absorption spectra as a validation test. The new fully automated determinations were found to be in good agreement with these previous measurements. Conclusions. Our results show that an automated search based on cloud-contour morphology can be efficient and that this novel technique may be extended to wider regions of the Milky Way and at larger distance. We discuss its limitations and potential improvements after combination with other techniques.

Implications of a multiscale structure of the yeast nuclear pore complex

Nuclear pore complexes (NPCs) direct the nucleocytoplasmic transport of macromolecules. Here, we provide a composite multiscale structure of the yeast NPC, based on improved 3D density maps from cryogenic electron microscopy and AlphaFold2 models. Key features of the inner and outer rings were integrated into a comprehensive model. We resolved flexible connectors that tie together the core scaffold, along with equatorial transmembrane complexes and a lumenal ring that anchor this channel within the pore membrane. The organization of the nuclear double outer ring reveals an architecture that may be shared with ancestral NPCs. Additional connections between the core scaffold and the central transporter suggest that under certain conditions, a degree of local organization is present at the periphery of the transport machinery. These connectors may couple conformational changes in the scaffold to the central transporter to modulate transport. Collectively, this analysis provides insights into assembly, transport, and NPC evolution.

Abundant time-wavering solutions of a modified regularized long wave model using the EMSE technique

This research article presents the application of the enhanced modified simple equation integral technique to obtain abundant time-wavering solutions of the modified regularized long wave (RLW) model. The model is known for its significance in exploring wave phenomena in various fields, including shallow water dynamics, pressure waves in liquids and gas bubbles, nonlinear transverse waves in magneto-hydrodynamics, and ion-acoustic waves in plasma. By implementing the enhanced modified simple equation integral technique, we construct arbitrary time-varying wave solutions for the model, resulting in a diverse range of solitonic waveforms. These solutions include kink waves, anti-kink waves, bright and dark bell waves, double periodic waves, and combinations of solitons and periodic waves. The obtained solutions are visually presented through 2D and 3D density and contour plots. Our findings demonstrate the effectiveness and potential of the enhanced modified simple equation integral technique in identifying innovative time-varying soliton solutions within the modified RLW model.

Analysis of tissue lipidomics and computed tomography pulmonary fat attenuation volume (CTPFAV ) in idiopathic pulmonary fibrosis.

There is increasing interest in the role of lipids in processes that modulate lung fibrosis with evidence of lipid deposition in idiopathic pulmonary fibrosis (IPF) histological specimens. The aim of this study was to identify measurable markers of pulmonary lipid that may have utility as IPF biomarkers. IPF and control lung biopsy specimens were analysed using a unbiased lipidomic approach. Pulmonary fat attenuation volume (PFAV) was assessed on chest CT images (CTPFAV ) with 3D semi-automated lung density software. Aerated lung was semi-automatically segmented and CTPFAV calculated using a Hounsfield-unit (-40 to -200HU) threshold range expressed as a percentage of total lung volume. CTPFAV was compared to pulmonary function, serum lipids and qualitative CT fibrosis scores. There was a significant increase in total lipid content on histological analysis of IPF lung tissue (23.16 nmol/mg) compared to controls (18.66 mol/mg, p = 0.0317). The median CTPFAV in IPF was higher than controls (1.34% vs. 0.72%, p < 0.001) and CTPFAV correlated significantly with DLCO% predicted (R2 = 0.356, p < 0.0001) and FVC% predicted (R2 = 0.407, p < 0.0001) in patients with IPF. CTPFAV correlated with CT features of fibrosis; higher CTPFAV was associated with >10% reticulation (1.6% vs. 0.94%, p = 0.0017) and >10% honeycombing (1.87% vs. 1.12%, p = 0.0003). CTPFAV showed no correlation with serum lipids. CTPFAV is an easily quantifiable non-invasive measure of pulmonary lipids. In this pilot study, CTPFAV correlates with pulmonary function and radiological features of IPF and could function as a potential biomarker for IPF disease severity assessment.

Inferring vehicle spacing in urban traffic from trajectory data

This study presents a new method to infer the average two-dimensional (2D) spacing between interacting vehicles in urban traffic from trajectory data. In this context, 2D spacing reflects the amount of road space consumed by pairs of interacting vehicles, and is related to 2D density at the macroscopic level. Due to complex interaction and conflicts in urban traffic, the inherent assumptions in traditional traffic flow models, such as unidirectional flow and homogeneity, are often violated. Such violation challenges direct measurement of urban vehicle spacing. The proposed method addresses this challenge by focusing on the relative movement between interacting vehicles and aggregating the accumulated presence of vehicles in similar scenarios. We apply the method to a large-scale urban trajectory dataset called pNEUMA, and validate the consistency of the method through bootstrapping. By applying the method we obtain a new empirical relation between the average 2D spacing and the relative speeds between interacting vehicles. There are similarities between this empirical relation with the classical Fundamental Diagram of traffic flow in terms of shape and interpretation, and so we term it the “interaction Fundamental Diagram” (iFD). However, there are also key differences. The iFD does not represent steady-state (homogeneous and stationary) longitudinal behaviour; it describes the average amount of road space needed for vehicle interactions at different relative speeds. We believe these iFD relations contribute to understanding vehicle interaction in urban traffic, and can offer new insights for designing safer and more efficient urban intersections.

Construction and testing of a model for predicting droplet deposition based on Gaussian process regression

To realize precision spraying, predicting the pesticide application dose based on the structural characteristics of the plant canopy is a crucial step. However, most of the current precision spraying techniques are based on canopy characteristics with no consideration given to the effect of canopy characteristics on droplet particle population. As a result, the droplet deposition value is far from being ideal. Herein, we explored the effects of canopy density and spraying volume on the distribution of droplet deposition in simulated citrus tree canopies and constructed a prediction model for droplet deposition. In this research, the three-dimensional (3D) reconstruction of fruit tree canopy was obtained using binocular camera and a new method was proposed to describe simulated citrus tree canopy density using three-dimensional point cloud. The optimal description of the interrelationship between 3D point cloud and fruit tree canopy density was determined by comparing the determination coefficients, Akaike information criterion and relative errors of the four fitting functions. Through our experiments, a droplet deposition prediction model based on Gaussian process regression was established by changing the duty cycle of the solenoid valve to adjust the spray volume, with simulated citrus trees as the target and water sensitive paper as the sampling method for collecting droplet deposition data. The experimental results show that the distribution of droplet deposition in the upper and lower layers of the canopy varies, but within the same layer droplets can produce relatively uniform deposition in similar canopy density areas with correlation coefficients greater than 0.6. When the canopy density reached 4.35 m2/m3, the amount of droplet deposition was anomalous. The prediction model, after training, has good ability of predicting droplet deposition with R2 higher than 0.79. At the same time, it was found in the research that differences occurred between the prediction accuracy of the droplet deposition prediction model in the upper canopy layer and that in the lower canopy layers, in which the R2 of the prediction model in the lower layer could reach 0.82, while in the upper layer it was 0.79. It is expected that our research on droplet deposition prediction can provide a new research perspective for precision spraying technology in plant protection operations.

Possibilities of on-board gravimetric and hydromagnetic survey in solving engineering-geological problems on the shelf

This article shows the possibilities of using on-board gravimetry and hydromagnetometry in combination with high-resolution seismic surveys in the framework of site surveys on the Arctic shelf. Geotechnical surveys were carried out in the southern part of the Kara Sea shelf on a study area of 25 km2 in order to identify potentially hazardous areas for setting up a floating drilling rig. The studies were carried out using a regular network of observations, consisting of 51 line and 26 secant profiles. The length of each profile is 5 km. Gravimetric research were carried out with the Chekan-AM marine on-board gravimeter in conjunction with magnetometric research using SeaSPY 2 towed marine magnetometers. The depth of research when performing engineering and geological surveys using the presented set of methods is the first 100 meters, up to 1 km. In this case, objects and phenomena of both technogenic and geological nature can represent a potential hazard. As the experience of carrying out this type of work in the south of the Arctic shelf shows, paleoincisions and paleovalleys are common hazards of the geological nature of the region under study. These structures are traditionally filled with weakly consolidated, often gas-saturated, sediments with inclusions of coarse-grained material. Paleoincisions are clearly manifested in the high-frequency component of the magnetic field, and the local component of the anomalous magnetic field was calculated to reveal them. As a result of a complex interpretation of gravity field anomalies and magnetic survey data, a curved linear zone was localized, crossing the entire study area. The identified anomalous zone is confined to the boundaries of the paleoincision, which was originally discovered according to seismoacoustic studies. Based on the results of gravity surveys, an area of negative anomalies was identified in the eastern part of the study area. According to the materials of seismoacoustic in this zone, paleocuts of a complex spatial and deep configuration are traced. It is noteworthy that these structures are not manifested in a magnetic field. Based on the obtained values of the gravitational field and seismoacoustic data, a seismic-density section of meridional strike was constructed across the entire area. As a result of 2D density modeling, the densities for the undercut paleoincision were selected and two deconsolidations were found at a depth of 200 meters. One of the model “artifacts” does not appear according to seismoacoustic studies and hydromagnetometry. The detected areas of decompaction can be caused by the gas saturation of the sedimentary strata and must be taken into account when setting up a floating drilling platform. The interpretation of the anomalous gravitational field in the specified complex of geophysical methods with a priori geological information makes it possible to predict the density structure of the studied rock mass and gives recommendations for further research.

Reconstructing the Volume Density Profile of Prestellar Cores with the Anisotropic Inverse Abel Transform Method

Most studies of the 3D density structure of prestellar cores have used isotropic evolution models, which are projected into 2D for direct comparison with observation data. In this study, we introduced the anisotropic inverse Abel transform method for reconstructing the 3D volume density profile of prestellar cores. We demonstrated that this approach could accurately preserve information about the realistic 3D structure with numerical simulation. This method has great advantages compared to the shape-assumption methods, particularly in high-density regions. We applied this method to the Herschel 2D column density maps of three prestellar cores, and the results showed good agreement with theoretical models. By changing the direction of the inversion axis of symmetry, we confirmed that the density profiles of prestellar cores exhibit nearly cylindrical symmetry.

Formulation and demonstrations of three-dimensional background-oriented schlieren using a mirror for near-wall density measurements

Three-dimensional background-oriented schlieren (3D-BOS) is an effective method for reconstructing 3D density fields from optically measured data, but it has limitations in measuring near-wall regions, where most of the light paths are blocked. This paper proposes a new extension, 3D-BOS using Mirror, which uses a wall as a mirror to provide sufficient light paths. In this paper, first, the conventional formulations are modified for the proposed method to handle the mirror reflections of the light paths. Subsequently, the proposed method is validated using artificially generated model data of an ideal axisymmetric distribution. The proposed method can reconstruct the distribution as accurately as the conventional method for all the number of cameras examined. Finally, the proposed method is experimentally demonstrated using a candle plume. The proposed method can capture cylindrical low-density regions near the wall surface.Graphical abstract

Analysis of the Effects of Process Variables and Alloy Composition on the Relative density and Mechanical Properties of 3D Printed Aluminum Alloys

Analysis of the Effects of Process Variables and Alloy Composition on the Relative density and Mechanical Properties of 3D Printed Aluminum Alloys

Data-constrained Solar Modeling with GX Simulator

To facilitate the study of solar flares and active regions, we have created a modeling framework, the freely distributed GX Simulator IDL package, that combines 3D magnetic and plasma structures with thermal and nonthermal models of the chromosphere, transition region, and corona. Its object-based modular architecture, which runs on Windows, Mac, and Unix/Linux platforms, offers the ability to either import 3D density and temperature distribution models, or to assign numerically defined coronal or chromospheric temperatures and densities, or their distributions, to each individual voxel. GX Simulator can apply parametric heating models involving average properties of the magnetic field lines crossing a given voxel, as well as compute and investigate the spatial and spectral properties of radio, (sub)millimeter, EUV, and X-ray emissions calculated from the model, and quantitatively compare them with observations. The package includes a fully automatic model production pipeline that, based on minimal users input, downloads the required SDO/HMI vector magnetic field data, performs potential or nonlinear force-free field extrapolations, populates the magnetic field skeleton with parameterized heated plasma coronal models that assume either steady-state or impulsive plasma heating, and generates non-LTE density and temperature distribution models of the chromosphere that are constrained by photospheric measurements. The standardized models produced by this pipeline may be further customized through specialized IDL scripts, or a set of interactive tools provided by the graphical user interface. Here, we describe the GX Simulator framework and its applications.

Application of the polynomial function method to the variable-coefficient Kadomtsev–Petviashvili equation

In this paper, we research a (2+1)-dimensional variable-coefficient Kadomtsev–Petviashvili equation in fluid dynamics and plasma physics. The lump, lump-soliton and lump-periodic solutions are derived based on the variable-coefficient polynomial function method. The effect of variable coefficients on the amplitude and velocity of solitons is analyzed and shown by some 3D graphs, contour plots and density graphs.