Dynamic Image Analysis Research Articles

Determining the Soil Particle Shape by Use of Dynamic Image Analysis

In Soil Science, it is well established that the geometry of individual soil particles, including their shape and size, has a significant impact on a number of key physical properties of the soil and on the processes involved with it. The shape and size of soil particles directly impact aspects such as permeability, water retention, stability of soil aggregates and the availability of nutrients for plants. Therefore, accurate determination of these characteristics of soil particles becomes extremely important for understanding and effective soil management. Nowadays, dynamic image analysis (DIA) is emerging as an exceptionally versatile and effective technique that enables precise determination of particle characteristics, including shape and size, in a dynamic and non-invasive manner. DIA enables the automatic analysis of thousands of microscopic images, allowing rapid and accurate study of the morphology of soil particles at micro and macro scales. The use of dynamic image analysis in soil research provides insight into the complex structures of soil particles and better prediction of their impact on various soil processes. Moreover, DIA enables the examination of a large number of samples in a short time, which contributes to the efficiency and precision of soil testing. Therefore, dynamic image analysis is becoming a widely used technique for determining particles' characteristics, such as shape and size. In the context of an ever-increasing awareness of the sustainable use of natural resources and the need to optimize agricultural and engineering practices, dynamic image analysis is becoming an indispensable tool for soil scientists, environmental scientists and engineers. Its versatile use can contribute to further expanding our knowledge about soil and developing innovative solutions for sustainable soil and environmental management.

Macrodebitage Writ Small? Studying Stoneknapping with Experimental Archaeology, Dynamic Image Analysis, and Statistics

ABSTRACT Microscopic artifacts help archaeologists study ancient societies and site formation processes. They have struggled to analyze them objectively, though. The traditional microscope-based approach has limited the number of samples and increased intra- and inter-observer errors. Here, we present an alternative based on experimental archaeology, Dynamic Image Analysis (DIA), and statistics. We ask whether microdebitage – the almost invisible debris from stone-knapping – has the same shape as macrodebitage or lithic artifacts wider than 4 mm. We collaborated with four modern stone-knappers to gather lithic debris. A new type of particle analyzer allowed us to measure five relevant variables for 23,694 knapping debris items. We use DIA to count, describe, and size-grade the debitage. We then analyze the resulting spreadsheet statistically. The results indicate highly significant statistical differences between microdebitage and macrodebitage as well as among microdebitage size classes. Combining experimental archaeology, DIA, and statistics enables the quantitative study of microdebitage.

Experimental study on the influence of particle morphology on compression characteristics of coral sand in South China Sea

Particle morphology is an important physical parameter that influences the engineering properties of coral sand, especially its compressibility. According to the quantitative analysis of particle morphology via the dynamic image analysis technology, a series of one-dimensional compression tests on coral sand and quartz sand with different particle morphology and densities were performed to reveal the effect of particle morphology on the compressibility of coral sand. The results demonstrated that the morphology of particles can be quantified using the shape-angularity group indicator (SAGI), whereas the SAGI of coral sand was greater than that of quartz sand. Coral sand exhibited a yield stress ranging from 1 to 2.5 MPa, and compressive deformations in both coral sand and quartz sand were dominated by irreversible plastic deformation. As the SAGI and densification increased, the number of particle coordination increased while the contact stress between grains decreased, which caused the yield stress of coral sand specimens to increase as well as the compression index and particle crushing rate to decrease. The SAGI of quartz sand particles remained relatively unchanged while that of coral sand particles gradually decreased after crushing, i.e., the coral sand particles developed a more regular shape after crushing.

Particle shape descriptors as a tool for classification of grain breakage

This study explores particle breakage of a calcareous sand, utilising dynamic image analysis and direct shear tests at varying normal stress levels to analyse the sand crushing mechanism. Tests were arrested at four phase transition points encountered during shear. Particle breakage was traced along a proposed scale based on the literature. Distinct behaviours in shape descriptors for particles of different diameters were observed under changing stress conditions. Agglomerated particle-level behaviour indicates that applied stress levels lead to different soil responses; at low stress, grains roll or slide, whereas at high stresses, grain movement is restricted. Particle breakage was evident even at minimal stress, with increasing grain size reduction as shear strain and stress levels heightened. This study introduces a parameter loading intensity (LI), amalgamating the effects of force chains and loading duration to model grain crushing. Relationships among the shape-angularity group indicator (SAGI), convexity (Cx) and sphericity (S) were also established, enabling calculation of these descriptors, after any loading intensity is applied, based on the initial values. Finally, a methodology for forecasting changes in S and Cx, under any given LI for materials with a known SAGI is presented.

TME-analyzer: a new interactive and dynamic image analysis tool that identified immune cell distances as predictors for survival of triple negative breast cancer patients

Spatial distribution of intra-tumoral immune cell populations is considered a critical determinant of tumor evolution and response to therapy. The accurate and systemic search for contexture-based predictors would be accelerated by methods that allow interactive visualization and interrogation of tumor micro-environments (TME), independent of image acquisition platforms. To this end, we have developed the TME-Analyzer, a new image analysis tool, which we have benchmarked against 2 software tools regarding densities and networks of immune effector cells using multiplexed immune-fluorescent images of triple negative breast cancer (TNBC). With the TME-Analyzer we have identified a 10-parameter classifier, predominantly featuring cellular distances, that significantly predicted overall survival, and which was validated using multiplexed ion beam time of flight images from an independent cohort. In conclusion, the TME-Analyzer enabled accurate interactive analysis of the spatial immune phenotype from different imaging platforms as well as enhanced utility and aided the discovery of contextual predictors towards the survival of TNBC patients.

The influence of vesicularity on grain morphology in basaltic pyroclasts from Mauna Loa and Kīlauea volcanoes

Vesicularity of individual pyroclasts from airfall tephra deposits is an important parameter that is commonly measured at basaltic volcanoes. Conventional methods used to determine pyroclast vesicularity on a large number of clasts has the potential to be time consuming, particularly when rapid analysis is required. Here we propose dynamic image analysis on two-dimensional (2D) projection shapes of crushed pyroclasts from tephra deposits as a new method to estimate vesicularity. This method relies on the influence of vesicles and uses grain morphology as a proxy for vesicle size and abundance. Pyroclasts from a variety of basaltic tephra deposits from the volcanoes of Mauna Loa and Kīlauea were analyzed. Vesicularities between 52–98% were measured via nitrogen-gas pycnometry. The same pyroclasts were then crushed and sieved, and their grain shapes measured using dynamic image analysis on a CAMSIZER®. This yields values for the mean sphericity, elongation, compactness, and Krumbein roundness of the grains. Our data show that grains become increasingly irregular with increasing vesicularity, with the degree of correlation between shape parameters and vesicularity depending on the size of measured grains. Shape irregularities in small grains (60–250 µm) are mostly area-based, with elongation being the best vesicularity indicator, whereas shape irregularities in large grains (250–700 µm) are mostly perimeter-based, with Krumbein roundness as the best vesicularity indicator. Using mean shape parameter values with all grain sizes included, grain elongation is the most well-correlated shape parameter with vesicularity, with the best fitted model explaining 76% of variation in the observations. Microscope images of thin sections of intact pyroclasts, as well as from crushed pyroclasts, were analyzed using CSDCorrections 1.6 software in ImageJ to find local vesicularity, vesicle size, grain size, grain elongation, and vesicle spatial distribution by stereological conversion. Observed correlation between grain shape and vesicularity can be explained by the local effect of vesicles on the shape of the solid structure in between those vesicles. Grain shape depends not only on vesicularity, but also on vesicle to grain size ratio and the spatial distribution of vesicles. The influence of vesicles on grain shape is best captured by grains with the size of the solid structure in between vesicles, which generally increases with decreasing vesicularity. Dynamic image analysis is a useful tool to quickly gauge vesicularity, which could be used in near-real-time during an eruption response. However, this method is best suited for highly vesicular (> 80%) basaltic pyroclasts from tephra deposits with few microlites and phenocrysts. Further research on crushing techniques, optimum grain size for shape measurements, and Krumbein roundness measurements for the grain size range of 250–700 µm might enable application of this method to lower vesicularity pyroclasts.

Croscarmellose Sodium as Pelletization Aid in Extrusion-Spheronization

Only few excipients are known to be suitable as pelletization aids. In this study, the potential use of croscarmellose sodium (CCS) as pelletization aid was investigated. Furthermore, the impact of cations on extrusion-spheronization (ES) of CCS was studied and different grades of CCS were tested. The influence of different cations on the swelling of CCS was investigated by laser diffraction. Mixtures of CCS with lactose monohydrate as filler with or without the inclusion of different cations were produced. The mixtures were investigated by mixer torque rheometry and consequently extruded and spheronized. Resulting pellets were analyzed by dynamic image analysis. In addition, mixtures of different CCS grades with dibasic calcium phosphate anhydrous (DP) and a mixture with praziquantel (PZQ) as filler were investigated. Calcium and magnesium cations caused a decrease of the swelling of CCS and influenced the use of CCS as pelletization aid since they needed to be included for successful ES. Aluminum, however, led to an aggregation of the CCS particles and to failure of extrusion. The inclusion of cations decreased the uptake of water by the mixtures which also reduced the liquid-to-solid-ratio (L/S) for successful ES. This was shown to be dependent on the amount of divalent cations in the mixture. With DP or PZQ as filler, no addition of cations was necessary for a successful production of pellets, however the optimal L/S for ES was dependent on the CCS grade used. In conclusion, CCS can be used as a pelletization aid.Graphical

Use of automation, dynamic image analysis, and process analytical technologies to enable data rich particle engineering efforts at the Drug Substance / Drug Product interface: A case study using Lovastatin

Automation plays a vital role in reducing development time in the pharmaceutical industry, both for drug substance (DS) and drug product (DP). Many aspects of crystallization development (solubility, kinetics, solid form characterization, concentration) have been positively impacted by automation; both in hardware and data processing, in the last two decades. However, wet milling, a critical unit operation used to manipulate particle properties in a crystallization process, has been non-conducive for automation. This study discusses efforts towards automation of wet milling, coupled with off-the-shelf automation tools for faster execution of physical property design workflows. The hardware and software configuration used, along with challenges and prospects to achieve milling automation are discussed. Lovastatin was used as a model compound to demonstrate the capabilities of the automated platform to achieve morphology and size manipulation. Five different batches of lovastatin were produced using different combinations of milling and thermal cycling. Milling followed by thermal cycling led to formation of rougher, fused particles with a lower aspect ratio compared to those produced by thermal cycling followed by milling. In-situ particle video microscopy was used to decipher that the initial increase in particle size during thermal cycling was driven by a fusion of primary particles followed by growth. Key material property descriptors such as bulk/tap density, flow function coefficient, surface area, and particle size by laser diffraction were collected using traditional means while particle size, aspect ratio and smoothness were also measured using image analysis. Lastly, principal component analysis (dimensionality reduction) was performed to determine the key property relationships impacting flowability. It was found that fines as measured by d10 (10th percentile of the volumetric size distribution) and Hausner ratio had a high positive and negative correlation, respectively with flowability. The on demand milling platform combined with data rich trials using PAT is estimated to accelerate process development for particle engineering and reduce the drug substance delivery time to drug product team.

Diagnostic Potential of Supplemental Static and Dynamic 68Ga-FAPI-46 PET for Primary 18F-FDG-Negative Pulmonary Lesions.

PET using 68Ga-labeled fibroblast activation protein (FAP) inhibitors (FAPIs) holds high potential for diagnostic imaging of various malignancies, including lung cancer (LC). However, 18F-FDG PET is still the clinical gold standard for LC imaging. Several subtypes of LC, especially lepidic LC, are frequently 18F-FDG PET-negative, which markedly hampers the assessment of single pulmonary lesions suggestive of LC. Here, we evaluated the diagnostic potential of static and dynamic 68Ga-FAPI-46 PET in the 18F-FDG-negative pulmonary lesions of 19 patients who underwent surgery or biopsy for histologic diagnosis after PET imaging. For target validation, FAP expression in lepidic LC was confirmed by FAP immunohistochemistry. Methods: Hematoxylin and eosin staining and FAP immunohistochemistry of 24 tissue sections of lepidic LC from the local tissue bank were performed and analyzed visually. Clinically, 19 patients underwent static and dynamic 68Ga-FAPI-46 PET in addition to 18F-FDG PET based on individual clinical indications. Static PET data of both examinations were analyzed by determining SUVmax, SUVmean, and tumor-to-background ratio (TBR) against the blood pool, as well as relative parameters (68Ga-FAPI-46 in relation to18F-FDG), of histologically confirmed LC and benign lesions. Time-activity curves and dynamic parameters (time to peak, slope, k 1, k 2, k 3, and k 4) were extracted from dynamic 68Ga-FAPI-46 PET data. The sensitivity and specificity of all parameters were analyzed by calculating receiver-operating-characteristic curves. Results: FAP immunohistochemistry confirmed the presence of strongly FAP-positive cancer-associated fibroblasts in lepidic LC. LC showed markedly elevated 68Ga-FAPI-46 uptake, higher TBRs, and higher 68Ga-FAPI-46-to-18F-FDG ratios for all parameters than did benign pulmonary lesions. Dynamic imaging analysis revealed differential time-activity curves for LC and benign pulmonary lesions: initially increasing time-activity curves with a decent slope were typical of LC, and steadily decreasing time-activity curve indicated benign pulmonary lesions, as was reflected by a significantly increased time to peak and significantly smaller absolute values of the slope for LC. Relative 68Ga-FAPI-46-to-18F-FDG ratios regarding SUVmax and TBR showed the highest sensitivity and specificity for the discrimination of LC from benign pulmonary lesions. Conclusion: 68Ga-FAPI-46 PET is a powerful new tool for the assessment of single 18F-FDG-negative pulmonary lesions and may optimize patient stratification in this clinical setting.

Quantification of shape parameters of Co-Cr-Mo-Si multiphase compounds and their role in the processing of metal injection molding feedstocks

Particle shape is one of the most important powder attributes affecting the properties of multiphase compounds intended for metal injection molding. This work reports the processability of gas (GA) and water (WA) atomized Co-Cr-Mo-Si alloy related to quantitative analyses of particle shape using a newly developed algorithm based on the Euclidean distance mapping, which results are compared with those of commercially available dynamic image analysis. Both methods reveal similar values for the parameters that quantify the shape of the powders, such as circularity, aspect ratio, and symmetry. The alloys were mixed with wax/high-density polyethylene (50/50 wt%) binder using a double sigma mixer to produce homogeneous feedstocks. The critical solid loading and flow performance corresponding to the differences in powder shapes were derived from the torque and capillary rheometers, respectively, to obtain the optimum molding parameters. A stable and repeatable viscosity was observed for the GA feedstock, whereas the compound containing WA was prone to phase separation during flow. The defect-free sintered specimens were examined by metallographic analysis; the GA powder compound could be sintered to a maximum of 99.2 % of the theoretical density, whereas the irregular WA powder reached a maximum of 98.8 % of the theoretical density, and the carbon residue was found to be higher for the GA feedstock. The GA samples had a significantly higher ultimate tensile strength owing to their larger symmetry, which resulted in a lower porosity and stress concentration.

Analysis and simulation of wet-granulation processes

BackgroundSize enlargement by wet-granulation is one of the most important unit operation in several industrial fields: pharmaceutics, food processing, animal nutrition, agronomics, and so on. A lot of techniques have been used in order to measure the particle size distributions (PSD) and a few different approaches are available to model the PSD evolution during the process, mainly based on population balance equations (PBE). However, difficulties in both the activities (reliable measurement and robust modeling) have hindered their diffusion in industrial practice, keeping the granulation closer to an art than to a science. MethodsIn this work, a fast and reliable method to measure PSD, based on dynamic image analysis (DIA) is presented and used in two case histories, one on a batch process on lab scale, and the other on a continuous process on plant scale. Significant findingsThe evolution of PSD was successfully described by models based on PBE, confirming the validity and the usefulness of the two approaches (experimental/modeling). The resulting model could be used as a basis for the process analysis and – to some extent – to predict the system's behavior in different conditions.

A review and analysis of particle size parameters and their relationships to physical properties of growing media

AbstractAn expanded description of particle morphology and the analysis of its relationships with physical properties may help to optimize the selection of raw materials and particle size fractions used as growing media constituents. Previous works have described the outlines of these relations based mostly on sieving procedures to characterize particle size distribution. They have shown limited and sometimes contradictory results due to the different methods used, size fractions selected, and physical properties measured. Also, sieve analysis, which separates particles based on their width, is less accurate for non‐spherical particles, which is the case for most growing media constituents. Recent works have promoted the use of dynamic image analysis (DIA) to precisely analyze both particle length and width. Five raw materials were chosen (white and black peats, coir, pine bark, and wood fiber) and sieved to obtain various particle size fractions. For each particle size fraction and the raw materials, the mean weight diameter (MWD), derived from sieving, was calculated, whereas mean particle length and width were determined using a DIA tool, the QicPic device. Also, physical properties were assessed from water retention curves established using Hyprop systems. The statement that the larger the particle size, the higher the air‐filled porosity (AFP), the lower the water holding capacity (WHC) was more precisely redefined. Large variations in WHC and AFP mainly occurred for finest particle size fractions, whereas changes were conversely very small or non‐existent for larger particle sizes. From data obtained for each particle size fractions, regression models were established to relate mean particle length and width (both determined using DIA) and MWD (determined from sieving) with WHC and AFP. Mean particle length was identified as the most relevant parameter for predicting WHC and AFP of the raw materials tested.

The RATT PARROT: serendipitous discovery of a peculiarly scintillating pulsar in MeerKAT imaging observations of the Great Saturn – Jupiter Conjunction of 2020. I. Dynamic imaging and data analysis

ABSTRACT We report on a radiopolarimetric observation of the Saturn–Jupiter Great Conjunction of 2020 using the MeerKAT L-band system, initially carried out for science verification purposes, which yielded a serendipitous discovery of a pulsar. The radiation belts of Jupiter are very bright and time variable: coupled with the sensitivity of MeerKAT, this necessitated development of dynamic imaging techniques, reported on in this work. We present a deep radio ‘movie’ revealing Jupiter’s rotating magnetosphere, a radio detection of Callisto, and numerous background radio galaxies. We also detect a bright radio transient in close vicinity to Saturn, lasting approximately 45 min. Follow-up deep imaging observations confirmed this as a faint compact variable radio source, and yielded detections of pulsed emission by the commensal MeerTRAP search engine, establishing the object’s nature as a radio emitting neutron star, designated PSR J2009−2026. A further observation combining deep imaging with the PTUSE pulsar backend measured detailed dynamic spectra for the object. While qualitatively consistent with scintillation, the magnitude of the magnification events and the characteristic time–scales are odd. We are tentatively designating this object a pulsar with anomalous refraction recurring on odd time-scales (PARROT). As part of this investigation, we present a pipeline for detection of variable sources in imaging data, with dynamic spectra and light curves as the products, and compare dynamic spectra obtained from visibility data with those yielded by PTUSE. We discuss MeerKAT’s capabilities and prospects for detecting more of such transients and variables.

Automatic Damage Detection of Pavement through DarkNet Analysis of Digital, Infrared, and Multi-Spectral Dynamic Imaging Images.

It is important to maintain the safety of road driving by automatically performing a series of processes to automatically measure and repair damage to the road pavement. However, road pavements include not only damages such as longitudinal cracks, transverse cracks, alligator cracks, and potholes, but also various elements such as manholes, road marks, oil marks, shadows, and joints. Therefore, in order to separate categories that exist in various road pavements, in this paper, 13,500 digital, IR, and MSX images were collected and nine categories were automatically classified by DarkNet. The DarkNet classification accuracies of digital images, IR images, and MSX images are 97.4%, 80.1%, and 91.1%, respectively. The MSX image is a enhanced image of the IR image and showed an average of 6% lower accuracy than the digital image but an average of 11% higher accuracy than the IR image. Therefore, MSX images can play a complementary role if DarkNet classification is performed together with digital images. In this paper, a method for detecting the directionality of each crack through a two-dimensional wavelet transform is presented, and this result can contribute to future research on detecting cracks in pavements.

Comparison of tracer kinetic models for 68Ga-PSMA-11 PET in intermediate-risk primary prostate cancer patients

Background68Ga-PSMA-11 positron emission tomography enables the detection of primary, recurrent, and metastatic prostate cancer. Regional radiopharmaceutical uptake is generally evaluated in static images and quantified as standard uptake values (SUVs) for clinical decision-making. However, analysis of dynamic images characterizing both tracer uptake and pharmacokinetics may offer added insights into the underlying tissue pathophysiology. This study was undertaken to evaluate the suitability of various kinetic models for 68Ga-PSMA-11 PET analysis. Twenty-three lesions in 18 patients were included in a retrospective kinetic evaluation of 55-min dynamic 68Ga-PSMA-11 pre-prostatectomy PET scans from patients with biopsy-demonstrated intermediate- to high-risk prostate cancer. Three kinetic models—a reversible one-tissue compartment model, an irreversible two-tissue compartment model, and a reversible two-tissue compartment model, were evaluated for their goodness of fit to lesion and normal reference prostate time-activity curves. Kinetic parameters obtained through graphical analysis and tracer kinetic modeling techniques were compared for reference prostate tissue and lesion regions of interest.ResultsSupported by goodness of fit and information loss criteria, the irreversible two-tissue compartment model optimally fit the time-activity curves. Lesions exhibited significant differences in kinetic rate constants (K1, k2, k3, Ki) and semiquantitative measures (SUV and %ID/kg) when compared with reference prostatic tissue. The two-tissue irreversible tracer kinetic model was consistently appropriate across prostatic zones.ConclusionsAn irreversible tracer kinetic model is appropriate for dynamic analysis of 68Ga-PSMA-11 PET images. Kinetic parameters estimated by Patlak graphical analysis or full compartmental analysis can distinguish tumor from normal prostate tissue.

Differences in ultrasonic cavitation damage between new and used engine coolants with varying time in operation

This study investigates the cavitation erosion performance of heavy-duty engine coolants before and after operation in trucks using an ultrasonic test rig based on ASTM G32. Fresh coolants with 35% and 50% v/v glycol were compared with used coolants. One coolant was obtained from a gasoline-fueled vehicle with a mileage of 27000 km, and two from diesel-fueled vehicles with mileages of 16000 and 180 000 km, respectively. Surface tension and boiling point at atmospheric pressure were measured, a chemical analysis was carried out, and suspended particles were quantified by dynamic image analysis. The results showed that the used coolants caused a lower mass loss in ultrasonic cavitation testing than the fresh ones, and that they had higher boiling points, lower pH and a higher number of suspended particles, especially of those smaller than 30μm. Surface tension was higher for the used coolants from Diesel engines.The lower mass loss caused by all three used coolants can be attributed mainly to their high boiling point and high particle count. The presence of particles is believed to promote the heterogeneous nucleation of smaller, more stable bubbles, which may protect the exposed surface by shockwave absorption and microjet deflection. Some dissolved ions in the used coolants may help reduce their aggressivity by inhibiting bubble coalescence, reducing bubble collapse energy, despite increasing surface tension. Surface tension has complex interactions with the solutes, particles and bubble formation and cannot, in isolation, explain the differences in performance of the coolants.

Characterization and Microstructure of Recycled Eroded Particles from Die-Sink Electro Discharge Machining of H11 Alloy for Applicability in Additive Manufacturing

Different waste streams from electro discharge machining (EDM) were investigated for an upcycled usage in processes for additive manufacturing (AM). These erosion sludges accumulate in filter cartridges and at the bottom of machining basins. The enclosed particles were extracted, sieved and investigated via laser diffraction, dynamic image analysis, scanning electron microscopy, optical emission spectroscopy, elemental analysis and flowability measurements. Additionally, thermal, crystallographic and metallographic investigations as well as X-ray micro-computed tomography (µ-CT) were utilized for the characterization of particle and material properties. In general, eroded powders fulfill the requirements for AM regarding particle size and shape very well, which is confirmed in morphological investigations and powder flow characteristics showing similar properties as the H11 AM reference material. The chemical composition of the powders is equal to the machined H11 alloy, except for the high carbon content. Carbon is entrapped in the iron lattice originating from pyrolysis of the present dielectric fluid and the graphite electrode during rapid solidification, which leads to a transition from martensite to cementite structures. This change is observed in the microstructure of powders, in which acicular primary cementite and austenite are present. After remelting with slow heating and cooling rates the microstructure changed to ledeburite II with retained austenite and martensitic phases. The pore size and shape distributions obtained by µ-CT measurements showed a pore formation in the compact sample. These results provide a fundament of major properties as well as handling and recycling suggestions for eroded particles enclosed in waste sludges.Graphical

Ultrasound-enhanced separation characteristics of gas-solid fluidized bed for fine-grained fluorite ore

Due to the increasing mechanization of mining, there is an urgent need to develop dry separation technology for effective pre-enrichment of fine-grained fluorite ore and promote the efficient use of fluorite in arid or water-scarce areas. Therefore, we tried to enhance the separation performance of fine-grained fluorite ore by introducing ultrasound into the gas–solid separation fluidized bed. Fluidization test and high-speed dynamic image analysis were used to reveal the mechanism of density separation of two-component materials enhanced by ultrasound. The effects of gas velocity, static bed height, separation time and amplitude transformer diameter on density segregation of two-component materials were further studied. In addition, a gas–solid fluidized bed separation system under the action of ultrasound was established for the pre-enrichment of fluorite ore with different particle sizes. The study showed that the stability of the bed is improved by the introduction of ultrasound. And the separation efficiency was increased by 15.46% compared with ordinary fluidized bed. The possible deviation (E) values of 1–0.5 mm and 0.5–0.25 mm fluorite ore were 0.22 g/cm3 and 0.175 g/cm3 respectively. This study provides new insights into the separation of fine-grained fluorite ore by gas–solid fluidized bed under the action of ultrasound.

Kinetic modeling and parametric imaging of 18 F-PSMA-11: An evaluation based on total-body dynamic positron emission tomography scans.

The prostate-specific membrane antigen (PSMA) targeted positron-emitting tomography (PET) tracers are increasingly used in clinical practice, with novel tracers constantly being developed. Recently, 18 F-PSMA-11 has been gaining growing interest for several merits; however, direct in vivo visualization of its kinetic features in humans remains lacking. To visualize the kinetic features of 18 F-PSMA-11 in healthy subjects and patients with prostate cancer derived from the total-body dynamic PET scans. A total of 8 healthy volunteers (7 males; 1 female) and 3 patients with prostate cancer underwent total-body PET/CT imaging at 1 and 2h post injection (p.i.) of 18 F-PSMA-11, of which 7 healthy subjects and 3 patients underwent total-body dynamic PET scans lasting 30min. Reversible two-tissue compartments (2TC) and Patlak models were fitted based on the voxel-based time activity curves (TACs), with the parametric images generated subsequently. Additionally, semi-automated segmentation of multiple organs was performed in the dynamic images to measure the SUVmean at different time points and in the parametric images to estimate the mean value of the kinetic parameters of these organs. 18 F-PSMA-11 showed quick accumulation within prostate cancer, as early as 45s after tracer injection. It was rapidly cleared from blood circulation and predominantly excreted through the urinary system. High and rapid radiotracer accumulation was observed in the liver, spleen, lacrimal glands, and salivary glands, whereas gradual accumulation was observed in the skeleton. Prostate cancer tissue is visualized in all parametric images, and best seen in DV and Patlak Ki images. Patlak Ki showed a good correlation with 2TC Ki values (r=0.858, p<0.05) but less noise than 2TC images. A scanning time point of 30-35min p.i. was then suggested for satisfactory tumor to background ratio. Prostate cancer tissue is visible in most parametric images, and is better shown by Patlak Ki and 2TC DV images. Patlak Ki is consistent with, and thus is preferred over, 2TC Ki images for substantially quicker calculation. Based on the dynamic imaging analysis, a shorter uptake time (30-35min) might be preferred for a better balance of tumor to background ratio.

Application of dynamic image analysis to the optical characterisation of fibrous bulk material

Dynamic image analysis provides an automated evaluation method to determine the size and shape of multiple particles. This method represents a common application for ordinary bulk material. The latest draft of ISO 13322–2:2021 describes the state of the art, but lacks instructions for handling fibrous bulk material. Interlocking fibres complicate the measurement conditions and require a disentanglement of fibrous samples during a pre-dispersion step. A further error source includes the fibre orientation inside the measurement zone of the device. If the thresholding algorithm fails to differentiate between the fibre projection area and the background, a subsequent image optimisation solves the problem. This article addresses the mentioned problems by analysing cotton cellulose and polyacrylonitrile fibres. Besides the execution of a pre-dispersion step, the experiments compare the discrepancies between dry and wet dispersion. Here, the software packages PAQXOS and ImageJ perform the image evaluation. In this case, the wet dispersion setup with a subsequent image evaluation by ImageJ provides comprehensible results.