2D Sections Research Articles

Estimation of Inferior Vena Cava Size from Ultrasound Imaging in X-Plane

Ultrasound (US) scans of the inferior vena cava (IVC) provide useful information on the volume status of a patient. However, their investigation is user-dependent and prone to measurement errors. An important technical problem is the objective difficulty in studying a very compliant blood vessel like IVC, which makes large respirophasic movements and shows a complicated three-dimensional geometry. Using bi-dimensional (2D) B-mode views either in a long or short axis has improved the characterization of IVC dynamics compared to measurements along a single direction (M-mode). However, specific movements of the IVC can also challenge the information provided by these 2D sections. Thus, these two orthogonal views, provided by an US system in the X-plane, are integrated here using an innovative method. It is tested on simulated videos of the IVC by performing complicated movements, which are compensated by the new method, overcoming the biased measurements provided by 2D scans. The method is then applied on example experimental data.

DiffSim: a user-friendly tool for precise magmatic timescale determination and error propagation via major element diffusion chronometry in magmatic phases

Diffusion chronometry is a technique gaining interest in the scientific community related to volcanology and petrology; however, modelling can be challenging for non-expert users. Here, we present DiffSim, a user-friendly standalone freeware that allows users to calculate magmatic timescales simulating 1D diffusion of major elements in olivine, orthopyroxene, titanomagnetite, and melt (inclusions). The freeware works solving the Fick’s second law equation (for both Cartesian and spherical polar coordinates, depending on the phase) using finite differences through the Crank-Nicolson method. Users must specify the initial composition vs. distance profile, the time resolution, and the intensive conditions (such as temperature, pressure, and oxygen fugacity). For orthorhombic phases, such as olivine and orthopyroxene, users must also specify the plunge and the trend of the (001)-axis and the angle traverse of the 2D section being studied. The best-fitting profile, comparing the natural (measured) and the modelled (calculated) profiles, is obtained using the least-squares fitting method in accordance with the total time specified by the user for performing the diffusion modelling. To determine the uncertainties of the timescale calculation, DiffSim propagates errors based on the uncertainties associated with each intensive condition and the experimental diffusivity measurements. DiffSim is available as executable freeware, allowing researchers and students to use diffusion chronometry to elucidate information about crustal processes with ease and precision.

Seismic data denoising using the 3D curvelet transform method

One of the major difficulties in processing and interpreting seismic data is the contamination of seismic signals by noise from numerous sources. Conventional denoising methods are mostly used for processing 2D seismic data, but noise also exists in the 3D data space, resulting in poor results using conventional denoising methods. Consequently, here, for seismic data denoising, a multiscale and multidirectional 3D curvelet transform was adopted. Our study combined the core principle of the 3D curvelet approach with the threshold iteration method to denoise simulated and actual seismic data with varying signal-to-noise ratios, and the results were quantitatively compared with the processing outcomes of existing denoising methods. The effectiveness of our method is illustrated using both genuine 2D and 3D post-stack seismic data, and synthetic 2D sections with added white and colored noise. Finally, we demonstrate how to prepare the data for frequency-domain full-waveform inversion using curvelet denoising. Despite the complexity of the procedure used to create the training samples, testing results using synthetic and real seismic data demonstrate that this method has mastered the capacity to suppress Gaussian and super-Gaussian noise from various training samples.

A new repository of electrical resistivity tomography and ground-penetrating radar data from summer 2022 near Ny-Ålesund, Svalbard

Abstract. We present the geophysical data set acquired in summer 2022 close to Ny-Ålesund (western Svalbard, Brøggerhalvøya Peninsula, Norway) as part of the project ICEtoFLUX. The aim of the investigation is to characterize the role of groundwater flow through the active layer as well as through and/or below the permafrost. The data set is composed of electrical resistivity tomography (ERT) and ground-penetrating radar (GPR) surveys, which are well-known geophysical techniques for the characterization of glacial and hydrological processes and features. Overall, 18 ERT profiles and 10 GPR lines were acquired, for a total surveyed length of 9.3 km. The data have been organized in a consistent repository that includes both raw and processed (filtered) data. Some representative examples of 2D models of the subsurface are provided, that is, 2D sections of electrical resistivity (from ERT) and 2D radargrams (from GPR). The resistivity models revealed deep resistive structures, probably related to the heterogeneous permafrost, which are often interrupted by electrically conductive regions that may relate to aquifers and/or faults. The interpretation of these data can support the identification of the active layer, the occurrence of spatial variation in soil conditions at depth, and the presence of groundwater flow through the permafrost. To a large extent, the data set can provide new insight into the hydrological dynamics and polar and climate change studies of the Ny-Ålesund area. The data set is of major relevance because there are few geophysical data published about the Ny-Ålesund area. Moreover, these geophysical data can foster multidisciplinary scientific collaborations in the fields of hydrology, glaciology, climate, geology, and geomorphology, etc. The geophysical data are provided in a free repository and can be accessed at https://doi.org/10.5281/zenodo.10260056 (Pace et al., 2023).

Formation of the junctions between lymph follicles in the Peyer's patches even before postweaning activation

Peyer’s patches (PPs), which contain an abundance of B and T cells, play a key role in inducing pivotal immune responses in the intestinal tract. PPs are defined as aggregated lymph follicles, which consist of multiple lymph follicles (LFs) that may interact with each other in a synergistic manner. LFs are thought to be spherical in shape; however, the characteristics of their structure are not fully understood. To elucidate changes in the structure of PPs as individuals grow, we generated serial 2D sections from entire PPs harvested from mice at 2, 4, and 10 weeks of age and performed a 3D analysis using a software, Amira. Although the number of LFs in PPs was not changed throughout the experiment, the volume and surface area of LFs increased significantly, indicating that LFs in PPs develop continuously by recruiting immune cells, even after weaning. In response to the dramatic changes in the intestinal environment after weaning, the development of germinal centers (GCs) in LFs was observed at 4 and 10 weeks (but not 2 weeks) of age. In addition, GCs gradually began to form away from the center of LFs and close to the muscle layer where export lymphatic vessels develop. Importantly, each LF was joined to the adjacent LF; this feature was observed even in preweaning nonactivated PPs. These results suggest that PPs may have a unique organization and structure that enhance immune functions, allowing cells in LFs to have free access to adjacent LFs and egress smoothly from PPs to the periphery upon stimulation after weaning.

Quantum Interference between Quasi-2D Fermi Surface Sheets in UTe_{2}.

UTe_{2} is a spin-triplet superconductor candidate for which high quality samples with long mean free paths have recently become available, enabling quantum oscillation measurements to probe its Fermi surface and effective carrier masses. It has recently been reported that UTe_{2} possesses a 3D Fermi surface component [Phys. Rev. Lett. 131, 036501 (2023)PRLTAO0031-900710.1103/PhysRevLett.131.036501]. The distinction between 2D and 3D Fermi surface sections in triplet superconductors can have important implications regarding the topological properties of the superconductivity. Here we report the observation of oscillatory components in the magnetoconductance of UTe_{2} at high magnetic fields. We find that these oscillations are well described by quantum interference between quasiparticles traversing semiclassical trajectories spanning magnetic breakdown networks. Our observations are consistent with a quasi-2D model of this material's Fermi surface based on prior dHvA-effect measurements. Our results strongly indicate that UTe_{2}-which exhibits a multitude of complex physical phenomena-possesses a remarkably simple Fermi surface consisting exclusively of two quasi-2D cylindrical sections.

High-fidelity simulations of airfoil vortex-induced vibrations: from 2D to blade-like aspect ratios

Large edgewise vibrations due to vortex shedding can be suffered by a wind turbine blade when the rotor is stopped or idling and there is massively separated flow. High-fidelity simulations of these vortex-induced vibrations (VIV) with a full-blade model are very computationally expensive, and so currently reported results of this type are limited to short time series or reduced parameter spaces, far from being sufficient to predict the lock-in range and other characteristics of a full-scale blade response to VIV under real conditions. This computational cost has led researchers to, alternatively, study VIV using simplified approaches, like simulations of 2D and short-span airfoil sections. To help bridge the gap between expensive full-blade and short-span airfoil section simulations, in this work the VIV response of an airfoil section is obtained for three different aspect ratios —from 2D to a blade-like aspect ratio—, using CFD simulations coupled with a one-degree-of-freedom structural oscillator model. The results obtained show that inside the lock-in range the airfoil’s initial VIV response is very similar for all aspect ratios studied, despite notable differences in the Strouhal number obtained. In contrast, outside lock-in the aerodynamic forces vary substantially from one case to another.

Modal effects of span-layout types on coupled flutter of long-span suspension bridges

This study provides a theoretical explanation for a perplexing experimental phenomenon observed frequently in suspension bridge flutter testing, where the flutter critical wind speed (Ucr) predicted by two-dimensional (2D) section model testing is higher than that predicted by three-dimensional (3D) full aeroelastic model testing. Six long-span suspension bridges with either a single simply supported span or multiple continuously supported spans were taken as research examples, then the comparative studies on the flutter critical wind speeds, flutter frequencies, modal energy ratios and aerodynamic damping corresponding to 2D and 3D coupled flutter states were carried out to illustrate the flutter modal effects. The research findings indicate that the Ucr of 2D testing being higher than that of 3D testing is an inherent characteristic for single-span simply-supported suspension bridges, which can be attributed to the prominent aerodynamic negative damping associated with 2nd-order vertical bending mode. However, due to the aerodynamic positive damping associated with 3rd-order vertical bending mode, the Ucr of 2D testing is consistently lower than that of 3D testing in the cases of multi-spans continuously-supported suspension bridges. Additionally, to eliminate unsafe 2D evaluations, a reasonable modal matching principle is recommended for section model testing of single-span simply-supported suspension bridges.

Peritectic solidification patterns in the Zn–Ag system captured in three- and four-dimensions

Microstructure selection in two-phase peritectic alloys has been a long-standing topic of fundamental importance. The bicontinuous microstructures arising from peritectic solidification have presented significant challenges for analysis due (in part) to our reliance on two-dimensional (2D) sections, which limits our ability to interpret the full three-dimensional (3D) complexity. Additionally, understanding growth mechanisms based solely on postmortem data has proven to be challenging because the extent of the solid-state peritectic transformation is unknown. Here, we employed X-ray imaging techniques to acquire detailed 3D data and visualize in real-time the dynamics of peritectic solidification in a model system of composition Zn-9.53 wt.% Ag. This paper offers a detailed examination of the origin of two-phase (Zn) + AgZn3 microstructures during directional solidification: specifically, our work investigates the influence of velocity, thermal gradient, and sample size on microstructure selection, namely, rod-like, singly-banded, and multiply-banded structures. Importantly, we find at low velocities V (0.07–0.1 μm/s) and a low thermal gradient G (3 K/mm) the emergence of peritectic (Zn) channels, interwoven within and between primary AgZn3 columnar grains. While these microstructures are suggestive of coupled growth morphologies, real-time imaging proves that the two solids are instead decoupled at the growth front. Meanwhile, at thermal gradients 10× higher, we observe a partially dendritic and partially banded structure that has not been reported before, to the best of our knowledge. We initiate a discussion on the formation of such structures, with broad implications to a wide range of metallic, semi-metallic, and organic peritectic alloys.

Imaging tree root systems using ground penetrating radar (GPR) data in Brazil

Trees sequester carbon dioxide from the atmosphere through photosynthesis, storing it in branches, stems, and roots, where the belowground carbon fraction, approximately ¼ of the total amount, exhibits significant interspecies root biomass variability. Estimating the amount of carbon stored in tree roots of different species is key to understanding an important aspect of climate change and exploring how natural forests, urban tree planting policies, and reforestation projects might help to address it. In this context, one of the most prominent Non-Destructive Testing methods capable of estimating the diameter and length of roots at different depths is ground penetrating radar (GPR). It has been widely used for geological, archaeological, and geotechnical studies due to its accuracy in locating buried material in different contexts, although standards for the correct management of datasets related to belowground root systems are still been developed. This paper reports a GPR signal processing flow to estimate the root diameter of three species of tropical forest trees, and to demonstrate the method’s viability, a dataset was collected in a study area with a 900 MHz shielded antenna. A multi-stage data processing flow is then presented, including raw data, file format conversion, zero-time adjustment, background removal, signal gain, Stolt FK migration, and time-to-depth conversion with hyperbolic adjustment velocity. The resulting data were converted from true amplitude data to a trace envelope. High amplitudes on the envelope section, with lateral continuity in parallel sections, were interpreted as roots. However, the interpretation of outcomes encounters notable complexities, primarily attributable to the intricate nature of subsurface root architectures, the soil matrix characterized by significant clay content, and the co-occurrence of buried materials proximate to the arboreal subjects. Consequently, amplitudes discerned within ground penetrating radar (GPR) 2D sections necessitate cautious interpretation, as they are not immediately indicative of subsurface roots. To overcome this difficulty, this study used direct measurements of the roots in the field, to confirm the GPR data. Despite these complexities, the study demonstrates GPR’s efficacy, particularly in the uppermost soil layer-a pivotal carbon reservoir with a 96% correlation (R2) between GPR-derived coarse-root diameter estimates and field measurements.

Abstract 4217: An engineered breast tumor microenvironment model, with single-cell spatial resolution, to assess spatial dynamics of tumor evolution

Abstract Cellular heterogeneity is a prominent feature of the tumor microenvironment, and the organization of these cells has been linked to clinical outcomes such as disease progression and drug resistance. While retrospective analysis of patient tumors has produced a myriad of insights, samples are limited and highly complex making it challenging to validate causality. Here we present an engineered breast tumor microenvironment model, with single cell spatial resolution, to systematically identify which cell phenotypes and their spatial arrangements may be driving ductal carcinoma in situ disease progression. A microfluidic dispenser (Biopixlar, Fluicell) was optimized to enable the spatial patterning of single cells to replicate native histology. To demonstrate the high spatial precision of our method, we first replicated an annotated 2D section of a breast tumor biopsy region of interest (ROI) using MCF10A, MDA-MB-231, primary mammary fibroblasts, THP-1 derived macrophages, and primary mesenchymal stem cells. The XY coordinate of each cell was identified to create a print map matching the original biopsy. Deposited cells adhered to their intended target with an average print fidelity of 2.4 µm. Next, the stromal compartment of the ROI was altered to include phenotypes associated with tumor promoting microenvironments (i.e. cancer associated fibroblasts, M2 macrophages) and the core of the MCF10A ring filled with MDA-MB-231. Each deposited cell contained a fluorescent tag corresponding with its cell type to facilitate real time spatial tracking and annotation. The tumor microenvironments were live cell imaged for 24 hours at 5 minute intervals. MCF10A cells spread to form their junctions and create a cohesive ring, MDA-MB-231 cells proliferated and rapidly moved around within the confined space, and the cells of the stromal compartment spread to create a dense tissue like structure. The microenvironments were cultured for an additional 2-6 days, fixed, and stained for markers of proliferation, phenotype shifts, cell-cell junctions, and morphology. Unlocking the relative contributions of the specific cell types in ductal carcinoma in situ tumor microenvironment to the overall evolution of invasive breast cancer may hold the answer for many questions in early detection, treatment, and cancer avatar models. Citation Format: Haylie R. Helms, Kody A. Oyama, Alexander E. Davies, Ellen M. Langer, Luiz E. Bertassoni. An engineered breast tumor microenvironment model, with single-cell spatial resolution, to assess spatial dynamics of tumor evolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4217.

Direct three-dimensional segmentation of prostate glands with nnU-Net.

In recent years, we and others have developed non-destructive methods to obtain three-dimensional (3D) pathology datasets of clinical biopsies and surgical specimens. For prostate cancer risk stratification (prognostication), standard-of-care Gleason grading is based on examining the morphology of prostate glands in thin 2D sections. This motivates us to perform 3D segmentation of prostate glands in our 3D pathology datasets for the purposes of computational analysis of 3D glandular features that could offer improved prognostic performance. To facilitate prostate cancer risk assessment, we developed a computationally efficient and accurate deep learning model for 3D gland segmentation based on open-top light-sheet microscopy datasets of human prostate biopsies stained with a fluorescent analog of hematoxylin and eosin (H&E). For 3D gland segmentation based on our H&E-analog 3D pathology datasets, we previously developed a hybrid deep learning and computer vision-based pipeline, called image translation-assisted segmentation in 3D (ITAS3D), which required a complex two-stage procedure and tedious manual optimization of parameters. To simplify this procedure, we use the 3D gland-segmentation masks previously generated by ITAS3D as training datasets for a direct end-to-end deep learning-based segmentation model, nnU-Net. The inputs to this model are 3D pathology datasets of prostate biopsies rapidly stained with an inexpensive fluorescent analog of H&E and the outputs are 3D semantic segmentation masks of the gland epithelium, gland lumen, and surrounding stromal compartments within the tissue. nnU-Net demonstrates remarkable accuracy in 3D gland segmentations even with limited training data. Moreover, compared with the previous ITAS3D pipeline, nnU-Net operation is simpler and faster, and it can maintain good accuracy even with lower-resolution inputs. Our trained DL-based 3D segmentation model will facilitate future studies to demonstrate the value of computational 3D pathology for guiding critical treatment decisions for patients with prostate cancer.

Petascale pipeline for precise alignment of images from serial section electron microscopy

The reconstruction of neural circuits from serial section electron microscopy (ssEM) images is being accelerated by automatic image segmentation methods. Segmentation accuracy is often limited by the preceding step of aligning 2D section images to create a 3D image stack. Precise and robust alignment in the presence of image artifacts is challenging, especially as datasets are attaining the petascale. We present a computational pipeline for aligning ssEM images with several key elements. Self-supervised convolutional nets are trained via metric learning to encode and align image pairs, and they are used to initialize iterative fine-tuning of alignment. A procedure called vector voting increases robustness to image artifacts or missing image data. For speedup the series is divided into blocks that are distributed to computational workers for alignment. The blocks are aligned to each other by composing transformations with decay, which achieves a global alignment without resorting to a time-consuming global optimization. We apply our pipeline to a whole fly brain dataset, and show improved accuracy relative to prior state of the art. We also demonstrate that our pipeline scales to a cubic millimeter of mouse visual cortex. Our pipeline is publicly available through two open source Python packages.

Identifikasi Lapisan Akuifer Menggunakan Metode Geolistrik Resisitivitas Konfigurasi Dipole – Dipole Di Kelurahan Padang Mulya Kecamatan Koba

Padang Mulya Village, Koba District is part of the Koba Groundwater Basin area. This area has the potential of abundant aquifer layers. An aquifer is a layer of rock that can store water in large quantities. However, the continued increase in exploration of the aquifer layer will result in damage to the aquifer environment. In this case it is necessary to identify the aquifer layers to determine the depth and lithology of the constituent rocks. The resistivity geoelectric method of the dipole-dipole configuration is the most sensitive geophysical method for identifying aquifer layers. Measurements were made on six tracks to obtain data variations on current strength and potential difference. From these data variations in apparent resistivity values will be obtained. 2D modeling of the apparent resistivity value using the backward modeling method is carried out on each track in order to obtain a 2D cross-section of the subsurface structure. The 2D section of each track has an aquifer layer with a depth of 0 meters to 20 meters and is composed of clay, loamy sand, rather dense gravel sand and sandstone.

Spatial Computer Model of the UCl<sub>3</sub>–NaCl–MgCl<sub>2</sub>–PuCl<sub>3</sub> Isobaric Phase Diagram

A four-dimensional (4D, in concentration–temperature coordinates) computer model of the isobaric phase diagram of uranium, sodium, magnesium, and plutonium chlorides, as well as four three-dimensional (3D) computer models of the phase diagrams of the ternary systems forming it, has been constructed. The technology of assembling a 4D model of 46 hypersurfaces and 17 phase regions was used in the design. The obtained 4D model of the UCl3–NaCl–MgCl2–PuCl3 phase diagram makes it possible to visualize a four-dimensional object as a whole (with all its hypersurfaces and phase regions) by any arbitrarily given 2D and 3D sections, as well as it is able to reproduce published (experimental or thermodynamically calculated) 2D sections. The scope of application of the results of the work is the development of materials for fuel components of fourth-generation molten salt reactors and pyrochemical recycling of spent fuel rods. For the first time, a comprehensive, complete description of phase diagrams composed of uranium, plutonium, sodium, and magnesium chlorides has been obtained.

Spatial correlation of 2D hard-tissue histology with 3D microCT scans through 3D printed phantoms

Hard-tissue histology—the analysis of thin two-dimensional (2D) sections—is hampered by the opaque nature of most biological specimens, especially bone. Therefore, the cutting process cannot be assigned to regions of interest. In addition, the applied cutting-grinding method is characterized by significant material loss. As a result, relevant structures might be missed or destroyed, and 3D features can hardly be evaluated. Here, we present a novel workflow, based on conventual microCT scans of the specimen prior to the cutting process, to be used for the analysis of 3D structural features and for directing the sectioning process to the regions of interest. 3D printed fiducial markers, embedded together with the specimen in resin, are utilized to retrospectively register the obtained 2D histological images into the 3D anatomical context. This not only allows to identify the cutting position, but also enables the co-registration of the cell and extracellular matrix morphological analysis to local 3D information obtained from the microCT data. We have successfully applied our new approach to assess hard-tissue specimens of different species. After matching the predicted microCT cut plane with the histology image, we validated a high accuracy of the registration process by computing quality measures namely Jaccard and Dice similarity coefficients achieving an average score of 0.90 ± 0.04 and 0.95 ± 0.02, respectively. Thus, we believe that the novel, easy to implement correlative imaging approach holds great potential for improving the reliability and diagnostic power of classical hard-tissue histology.

3D Laser Scanning and UAVs in cultural heritage: The case of Old Navarino castle in Pylos, Greece

The archaeological site of Palaiokastro (Old Navarino castle), is located in Messenia on the Coryphasium peninsula, at the southern end of the beach of Voidokoilia in the Navarino Bay, SW Peloponnese. Palaiokastro was built during Frankish rule of the Peloponnese, in the 13th century, over the classical Acropolis of Pylos.The aim of this study is the initial documentation of the current situation of the medieval castle of Palaiokastro applying innovative technology including terrestrial laser scanner (TLS) and unmanned aerial vehicles (UAVs). TLS and UAV photogrammetry have been used in an integrated design to rapidly facilitate the acquisition of the whole gate, eliminating all possible occlusions. TLS was exploited for the acquisition of the facades while the UAV was used to capture the top view of castle gate. The recent improvement of the post-processing algorithms provides us with the ability to implement fusion methods of TLS and UAV models and also deliver an accurate 3D model of the whole gate.The combination of photogrammetry from the UAV with the data of the terrestrial laser scanner was used in order to give us a multitude of products such as textured 3D model, orthophotos, 2D floor plans, elevations and sections which are necessary for the complete and accurate geometric documentation of the current situation of the Southwest gate of Palaiokastro Castle. The various products mentioned assist in the better management of the study data and identification of the different construction phases of the South Gate.

Cell Block-Based Two-Dimensional and Immunocytochemical Analyses Could Reduce Atypical/Indeterminate Case Frequency in Breast Fine-Needle Aspiration Cytology: A Retrospective Analysis

Introduction: In fine-needle aspiration of the breast (FNAB), the “atypical” category encompasses both benign and malignant lesions, particularly papillary proliferative lesions, as per the latest WHO classification. We aimed to reduce atypical cases and improve diagnostic accuracy by investigating the utility of cell block (CB) analysis. Methods: FNAB CB samples (2018–2022) were reviewed using smear only or CBs. CB-based diagnosis was performed with 2D morphological analysis and immunocytochemistry using ER, CK5/6, p63, SMA, and CD56. Samples were reclassified as “benign,” “atypical,” “suspicious of malignancy,” “malignant,” or “insufficient/inadequate.” Atypical cases were reexamined. Diagnoses were validated histologically. Results: On examining the FNAB samples (n = 149; 32 atypical), 2D CB sectioning achieved a clearer definition of myoepithelial cells and fibrovascular cores than Papanicolaou staining. Immunocytochemistry was evaluated for 36 cases: estrogen receptor (ER)⁻ and CK5/6⁺ tumors were reclassified as benign; ER⁺ and CK5/6⁻ tumors as malignant; p63⁻ tumors as invasive; papillary malignant tumors with a smooth muscle actin (SMA)⁺ fibrovascular core and p63⁻ myoepithelial cells as encapsulated papillary carcinoma; and CD56⁺ carcinomas as neuroendocrine carcinoma. Diagnostic rates were as follows: benign (44% FNAB, 51% CB), atypical (21% FNAB, 3% CB), suspicious of malignancy and malignant (28% FNAB, 40% CB), and insufficient/inadequate (7% FNAB, 6% CB). CB achieved >85% sensitivity, specificity, and positive and negative predictive values. Conclusion: CBs represent 3D FNA cell morphology using 2D sections, enabling adaption of pathology criteria to the cytological material. Immunocytochemical staining of CBs can predict low nuclear grade papillary tumors and reduce atypical case frequency, improving diagnostic accuracy.

Reduced order modelling of thickness effects on a cantilevered hydrofoil in homogeneous isotropic turbulence

The response of a cantilevered hydrofoil excited by honeycomb-generated turbulence is studied with a reduced order analytical model that considers the thickness effects of NACA sections. This is achieved by extending a gust response model of the unsteady lift to include realistic 2D sections instead of using a flat plate assumption. The general chordwise thickness profiles are included in the model using the generalized Joukowski transformation. The problem is cast into a constrained optimization problem which is solved with the use of the Lagrange multiplier method. The frequency response function (FRF) of NACA sections with the same maximum thickness to chord ratio but with different leading-edge thickness profiles are calculated to investigate the effect of the hydrofoil leading edge thickness on the high frequency response. This FRF is combined with the Uncorrelated Wall Plane Wave (UWPW) technique to simulate the pressure jump amplitude on the hydrofoil due to the turbulence interaction which excites the hydrofoil in heaving and pitching motion according to Theodorsen’s hydroelastic theory. Finaly, the structural velocity spectra are compared with available experimental results of the turbulence ingestion and the effect of the different leading edge thickness profiles on the vibration response is demonstrated for various NACA sections.

Quantitative 3D characterization of chromite ore particles

The main techniques used to characterize raw materials are currently bulk or 2D. This is a consequence of the current lack of standardized and automated methods to characterize particulate materials in 3D. Here, we apply a workflow to characterize a crushed chromite ore with nine particle size classes below 1 mm using X-ray computed tomography. All data processing of all samples follows the same sequence of steps, which means that the analysis can be automated with limited user input as opposed to traditional 3D image processing methods that require user input specific to each particle size fraction. Results of chromite composition, particle size distribution and chromite liberation are obtained for individual particles and compared with the results from x-ray diffraction and 2D-based automated mineralogy. The results shows a consistent accuracy across all size classes down to 75 μm. For the larger particle sizes (>600 μm) the chromite liberation curves are more consistent than those obtained from 2D-based automated mineralogy, possibly due to the stereological bias of 2D sections. The particle size distributions is the property for which the 2D bias causes a larger divergence from 3D results across all particle sizes. In conclusion, the workflow is more automatable (thus, faster and cheaper) and less bias (thus, more accurate and standardisable) than other 3D image analysis methods. Additionally, it stands as complementary to established techniques for particle-based characterization, especially to measure particle properties that 2D-based methods may not measure representatively for larger particle sizes and when sampling is limited. Further testing of the workflow in progressively more complex materials is necessary, but its potential to transform the way mineral particulate materials are characterized is demonstrated.