A new method for the rapid identification of external water types in rainwater pipeline networks using UV-Vis absorption spectroscopy.

Ultraviolet-visible (UV-Vis) absorption spectroscopy, due to its high sensitivity and capability for real-time online monitoring, is one of the most promising tools for the rapid identification of external water in rainwater pipe networks. However, difficulties in obtaining actual samples lead to insufficient real samples, and the complex composition of wastewater can affect the accurate traceability analysis of external water in rainwater pipe networks. In this study, a new method for identifying external water in rainwater pipe networks with a small number of samples is proposed. In this method, the Generative Adversarial Network (GAN) algorithm was initially used to generate spectral data from the absorption spectra of water samples; subsequently, the multiplicative scatter correction (MSC) algorithm was applied to process the UV-Vis absorption spectra of different types of water samples; following this, the Variational Mode Decomposition (VMD) algorithm was employed to decompose and recombine the spectra after MSC; and finally, the long short-term memory (LSTM) algorithm was used to establish the identification model between the recombined spectra and the water source types, and to determine the optimal number of decomposed spectra K. The research results show that when the number of decomposed spectra K is 5, the identification accuracy for different sources of domestic sewage, surface water, and industrial wastewater is the highest, with an overall accuracy of 98.81%. Additionally, the performance of this method was validated by mixed water samples (combinations of rainwater and domestic sewage, rainwater and surface water, and rainwater and industrial wastewater). The results indicate that the accuracy of the proposed method in identifying the source of external water in rainwater reaches 98.99%, with detection time within 10 s. Therefore, the proposed method can become a potential approach for rapid identification and traceability analysis of external water in rainwater pipe networks.

Development of a Monte Carlo simulation platform for the systematic evaluation of photon-counting detector-based micro-CT.

PURPOSE: This study aimed to develop a photon-counting detector (PCD) based micro-CT simulation platform for assessing the performance of three different PCD sensor materials: cadmium telluride (CdTe), gallium arsenide (GaAs), and silicon (Si). The evaluation encompasses the components of primary and scatter signals, performance of imaging contrast agents, and detector efficiency. METHODS: Simulations were performed using the Geant4 Monte Carlo toolkit, and a micro-PCD-CT system was meticulously modeled based on realistic geometric parameters. RESULTS: The simulation can obtain HU values consistent with measured results for iodine and calcium hydroxyapatite contrast agents. The two major components of scatter signals for CdTe and GaAs based PCD are fluorescent X-ray photons and photoelectrons, whereas for Si, the components are photoelectrons and Compton electrons. Scattering counts of CdTe and GaAs sensors can be effectively reduced by using energy thresholds, whereas those of Si sensor are insensitive to the applied threshold. The optimal threshold values for CdTe and GaAs are 30 and 15 keV, respectively. For contrast agent imaging, GaAs exhibits enhanced sensitivity to low photon energies compared to CdTe, while it's contrast-to-noise ratio (CNR) values are slightly lower than those of CdTe at the same contrast agent concentration. Among the three sensor materials, Si has the lowest CNR and detector efficiency; CdTe exhibits the highest efficiency, except in low-energy ranges (< 45 keV), where GaAs has superior efficiency. CONCLUSIONS: The proposed methods are expected to benefit PCD optimization and applications, including energy threshold selection, scattering correction, and may reduce the need for large-scale experiments.

Bold rats (Niviventer confucianus) are more effective in seed dispersal: evidence both under enclosure conditions and in the field.

Rodents are important seed dispersers of plants because they move seeds far away from the parent trees and hoard seeds in the soil, benefiting seed dispersal and regeneration. Traits of plant seeds and animals are associated with rodent-mediated seed dispersal, but animal personality, the consistent individual behavioral differences in time and environments, has not been fully considered. Here, we first measured the personality of 26 Niviventer confucianus in the laboratory, and 10 individuals in the field of one population, and then tested their behavior of seed consumption and hoarding both in semi-natural enclosures and the field. We tested the hypothesis that individuals with different personalities have different preferences for seed consumption and hoarding, which has different implications for seed dispersal and regeneration. Under the enclosure conditions, all parameters of personality are repeatable; bold individuals harvested fewer seeds but scatter-hoarded more seeds and dispersed farther than timid ones, whereas active individuals consumed more seeds, but left fewer seeds on the ground surface than inactive ones. In the field, boldness, activity, and exploration of the animals are repeatable; bold individuals scatter-hoarded more seeds to farther distances than timid ones, whereas active individuals harvested and consumed more seeds than inactive ones. These results suggest that bold rats tended to scatter hoard seeds and disperse them to a longer distance, implying they are more effective in seed dispersal. In the future, animal personality (e.g. boldness and activity) should be considered in seed dispersal studies and ecological-based manipulation in seed dispersal and regeneration of forests.

Size and fluorescence calibrated imaging flow cytometry: From arbitrary to standard units.

Imaging flow cytometry (IFCM) is a technique that can detect, size, and phenotype extracellular vesicles (EVs) at high throughput (thousands/minute) in complex biofluids without prior EV isolation. However, the generated signals are expressed in arbitrary units, which hinders data interpretation and comparison of measurement results between instruments and institutes. While fluorescence calibration can be readily achieved, calibration of side scatter (SSC) signals presents an ongoing challenge for IFCM. Here, we present an approach to relate the SSC signals to particle size for IFCM, and perform a comparability study between three different IFCMs using a plasma EV test sample (PEVTES). SSC signals for different sizes of polystyrene (PS) and hollow organosilica beads (HOBs) were acquired with a 405 nm 120 mW laser without a notch filter before detection. Mie theory was applied to relate scatter signals to particle size. Fluorescence calibration was accomplished with 2 µm phycoerythrin (PE) and allophycocyanin (APC) MESF beads. Size and fluorescence calibration was performed for three IFCMs in two laboratories. CD235a-PE and CD61-APC stained PEVTES were used as EV-containing samples. EV concentrations were compared between instruments within a size range of 100-1000 nm and a fluorescence intensity range of 3-10,000 MESF. 81 nm PS beads could be readily discerned from background based on their SSC signals. Fitting of the obtained PS bead SSC signals with Mie theory resulted in a coefficient of determination >0.99 between theory and data for all three IFCMs. 216 nm HOBs were detected with all instruments, and confirmed the sensitivity to detect EVs by SSC. The lower limit of detection regarding EV-size for this study was determined to be ~100 nm for all instruments. Size and fluorescence calibration of IFCM data increased cross-instrument data comparability with the coefficient of variation decreasing from 33% to 21%. Here we demonstrate - for the first time - scatter calibration of an IFCM using the 405 nm laser. The quality of the scatter-to-diameter relation and scatter sensitivity of the IFCMs are similar to the most sensitive commercially available flow cytometers. This development will support the reliability of EV research with IFCM by providing robust standardization and reproducibility, which are pre-requisites for understanding the biological significance of EVs.

Tear Film Hyperosmolarity is Associated with Increased Variation of Light Scatter Following Cataract Surgery.

Purpose: To study the association between tear film hyperosmolarity and ocular light scatter in a cataract surgery population. Patients and Methods: Contiguous, 20-second objective scatter index (OSI) scans were recorded in hyperosmolar (≥320 mOsm/L) and normal subjects (<308 mOsm/L) with cataract nuclear opacity ≥3. OSI was measured at screening, baseline and 90 days following surgery. Along with symptoms of ocular surface disease, slit-lamp examination included corneal staining (0-3), tear film breakup time (TBUT) and evaluation of meibomian gland disease (MGD). An additional cohort of hyperosmolar subjects were measured for OSI at screening, baseline, and 5, 10, 15 and 30 minutes following instillation of 0.18% sodium hyaluronate (HA). Results: Thirty-one eyes of 31 patients were included. There was a significant difference in post-operative OSI variation when comparing hyperosmolar (0.65±0.30, N=11) to normal subjects (0.33±0.11, N=10, p=0.005). Of note, there were no significant differences in OSI variation when subjects were sorted by staining (p=0.9), TBUT (p=0.7), symptoms (p=0.7), or MGD status (p=0.9). Instillation of 0.18% HA (N=10) did not alter OSI at 5 minutes, but significant reductions in OSI of 28.8%, 38.5% and 36.7% (all p < 0.001) were observed at 10, 15 and 30 minutes. Conclusion: Hyperosmolar patients exhibited significantly increased variation in light scatter following cataract surgery that was undifferentiated by staining or TBUT. Elevated osmolarity may be indicative of light scatter equivalent to that of a grade 2-3 cataract.

Towards Sustainable and Dynamic Modeling Analysis in Korean Pine Nuts: An Online Learning Approach with NIRS.

Due to its advantages such as speed and noninvasive nature, near-infrared spectroscopy (NIRS) technology has been widely used in detecting the nutritional content of nut food. This study aims to address the problem of offline quantitative analysis models producing unsatisfactory results for different batches of samples due to complex and unquantifiable factors such as storage conditions and origin differences of Korean pine nuts. Based on the offline model, an online learning model was proposed using recursive partial least squares (RPLS) regression with online multiplicative scatter correction (OMSC) preprocessing. This approach enables online updates of the original detection model using a small amount of sample data, thereby improving its generalization ability. The OMSC algorithm reduces the prediction error caused by the inability to perform effective scatter correction on the updated dataset. The uninformative variable elimination (UVE) algorithm appropriately increases the number of selected feature bands during the model updating process to expand the range of potentially relevant features. The final model is iteratively obtained by combining new sample feature data with RPLS. The results show that, after OMSC preprocessing, with the number of features increased to 100, the new online model's R2 value for the prediction set is 0.8945. The root mean square error of prediction (RMSEP) is 3.5964, significantly outperforming the offline model, which yields values of 0.4525 and 24.6543, respectively. This indicates that the online model has dynamic and sustainable characteristics that closely approximate practical detection, and it provides technical references and methodologies for the design and development of detection systems. It also offers an environmentally friendly tool for rapid on-site analysis for nut food regulatory agencies and production enterprises.

The relationship between sex hormone levels and ocular surface parameters in girls with idiopathic central precocious puberty.

Purpose: The study aimed to investigate the correlation between the change of sex hormone levels and ocular surface parameters in girls with idiopathic central precocious puberty(ICPP). Methods: Eighteen girls with ICPP and 18 age-matched normal girls participated in this study, all of the participants had undergone physical measurements, laboratory tests, imaging examination and ocular surface assessments. Results: The Objective Scatter Index (OSI) in the ICPP group was significantly higher than in the control group (P = 0.031), girls with ICPP showed slightly lower MNITBUT compared to the normal control group, although this difference was not statistically significant. Bivariate analysis revealed a positive association between estradiol and OSI (r=0.383, P=0.021), Additionally, in the study population, both Luteinizing hormone (LH) and Follicle-stimulating hormone (FSH) were negatively correlated with Mean noninvasive tear breakup time (MNITBUT) (r=-0.359, P=0.031)(r=-0.357, P=0.032). Conclusion: In comparison with the normal control group, alterations in the OSI were observed in girls with ICPP. This alteration may be associated with an elevation in estrogen levels. Although there was a slight non-significant decrease in NITBUT in ICPP girls, the negative correlation between LH and FSH with MNITBUT suggests new perspective for further investigation.

Healing patterns of alveolar bone following ridge preservation procedures.

OBJECTIVES: Examine the histomorphometric bone composition, following alveolar ridge preservation techniques and unassisted socket healing. MATERIALS AND METHODS: Forty-two patients (42) requiring a single rooted tooth extraction were randomly allocated into three groups (n = 14 per group): Group 1: Guided Bone Regeneration (GBR) using deproteinised bovine bone mineral (DBBM) and a porcine collagen membrane; Group 2: Socket Seal (SS) technique using DBBM and a porcine collagen matrix; Group 3: Unassisted socket healing (Control). Trephined bone biopsies were harvested following a 4-month healing period. Forty-two samples underwent Back-Scattered Electrons -Scanning Electron Microscopy (BSE-SEM) imaging, with 15 samples examined using Xray Micro-Tomography (XMT) (n = 6 for each GBR/SS and n = 3 Control). Images were analysed to determine the percentage (%) of connective tissue, new bone formation, residual DBBM particles and direct bone to DBBM particle contact (osseointegration). RESULTS: BSE-SEM analysis demonstrated that new bone formation was higher in the Control (45.89% ± 11.48) compared to both GBR (22.12% ± 12.7/p < .004) and SS (27.62% ± 17.76/p < .005) groups. The connective tissue percentage in GBR (49.72% ± 9), SS (47.81% ± 12.57) and Control (47.81% ± 12.57) groups was similar. GBR (28.17% ± 16.64) and SS (24.37% ± 18.61) groups had similar levels of residual DBBM particles. XMT volumetric analysis indicated a lower level of bone and DBBM particles in all test groups, when matched to the BSE-SEM area measurements. Osseointegration levels (DBBM graft and bone) were recorded at 35.66% (± 9.8) for GBR and 31.18% (± 19.38) for SS. CONCLUSION: GBR and SS ARP techniques presented with less bone formation when compared to unassisted healing. GBR had more direct contact/osseointegration between the DBBM particles and newly formed bone.

Scatter radiation levels in X-ray rooms during chest radiography.

This research focused on the determination of scatter radiation levels in x-ray rooms during chest radiography. 108 patients were examined. Four x-ray machines (A, B, C, and D) were used during the research from three centers. Three positions were considered in this study; position Q just beside the (Bucky stand), position R, which is 150 cm from the left of the Bucky stand towards the door and position T, 200 cm from the Bucky stand to the radiographer's protective screen respectively. Two machines (A and B) from center 1 and one machine from center 2 (C) and one machine from center 3 (D). The body mass index (BMI) of the participants ranged from 20 to 25 kgm-2 with mean value of 23.97 kgm-2. The background radiation level was read using Radalert 100 m before any exposure, and the mean background level was 0.298 mR/h. The mean of the scatter radiation doses obtained from positions Q with respect to the four machines A, B, C, and D, were 0.109, 0.201, 0.204, 0.200 mR/h (9.166, 16.903, 17.156, 16.819 mSv/yr) and their standard deviations were ±0.052, ±0.053, ±0.064, and ±0.081 respectively. The results were comparable with previous studies. The study recommends staff education and training in determination of radiation levels for enhanced work safety.

Scatter estimation and correction using time-of-flight and deconvolution in x-ray medical imaging.

Objective.Time-of-flight (TOF) scatter rejection requires a total timing jitter, including the detector timing jitter and the x-ray source's pulses width, of 50 ps or less to mitigate most of the effects of scattered photons in radiography and CT imaging. However, since the total contribution of the source and detector to the timing jitter can be retrieved during an acquisition with nothing between the source and detector, it can be demonstrated that this contribution may be partially removed to improve the image quality.Approach.A scatter correction method using iterative deconvolution of the measured time point-spread function estimates the number of scattered photons detected in each pixel. To evaluate the quality of the estimation, GATE was used to simulate the radiography of a water cylinder with bone inserts, and a head and torso in a system with total timing jitters from 100 ps up to 500 ps full-width-at-half-maximum (FWHM).Main results.With a total timing jitter of 200 ps FWHM, 89% of the contrast degradation caused by scattered photons was recovered in a head and torso radiography, compared to 28% with a simple time threshold method. Corrected images using the estimation have a percent root-mean square error between 2% and 14% in both phantoms with timing jitters from 100 to 500 ps FWHM which is lower than the error achieved with scatter rejection alone at 100 ps FWHM.Significance.TOF x-ray imaging has the potential to mitigate the effects of the scattering contribution and offers an alternative to anti-scatter grids that avoids loss of primary photons. Compare to simple TOF scatter rejection using only a threshold, the deconvolution estimation approach has lower requirements on both the source and detector. These requirements are now within reach of state-of-the-art systems.

Improved Non-Negative Matrix Factorization-Based Noise Reduction of Leakage Acoustic Signals.

The detection of gas leaks using acoustic signals is often compromised by environmental noise, which significantly impacts the accuracy of subsequent leak identification. Current noise reduction algorithms based on non-negative matrix factorization (NMF) typically utilize the Euclidean distance as their objective function, which can exacerbate noise anomalies. Moreover, these algorithms predominantly rely on simple techniques like Wiener filtering to estimate the amplitude spectrum of pure signals. This approach, however, falls short in accurately estimating the amplitude spectrum of non-stationary signals. Consequently, this paper proposes an improved non-negative matrix factorization (INMF) noise reduction algorithm that enhances the traditional NMF by refining both the objective function and the amplitude spectrum estimation process for reconstructed signals. The improved algorithm replaces the conventional Euclidean distance with the Kullback-Leibler (KL) divergence and incorporates noise and sparse constraint terms into the objective function to mitigate the adverse effects of signal amplification. Unlike traditional methods such as Wiener filtering, the proposed algorithm employs an adaptive Minimum Mean-Square Error-Log Spectral Amplitude (MMSE-LSA) method to estimate the amplitude spectrum of non-stationary signals adaptively across varying signal-to-noise ratios. Comparative experiments demonstrate that the INMF algorithm significantly outperforms existing methods in denoising leakage acoustic signals.

Seed traits and burial state affect plant seed secondary dispersal mediated by rodents.

Seed dispersal is an important ecological process and has important implications for plant population expansion and regeneration. Seed dispersal not only reduces the probability of death due to seed density but also facilitates seedling establishment. Many studies have focused on the effect of one or two factors on seed dispersal. However, little is known about studies on the effect of multiple factors and their interactions on seed dispersal. Here, we conducted a field experiment to explore how seed size, soil burial, and seed peeling affect the dispersal and hoarding of seeds of Quercus liaotungensis in dispersal animals. We found that large seeds were preferentially selected by animals, and the predation after dispersal, hoarding after dispersal, predation distance after dispersal, and hoarding distance after dispersal of large seeds were significantly greater than small seeds, which is more beneficial to the plant expansion and regeneration. Soil burial increased the time of seed intact in situ, significantly increased predation in situ, and reduced predation after dispersal, predation distance after dispersal, and hoarding distance after dispersal, which is not beneficial to the plant population expansion and regeneration. Seed peeling reduced the time of seed intact in situ, and the predation after dispersal was significantly greater than that of unpeeled seeds, which is not beneficial to the plant population. We did not find the interactions between seed size, soil burial, and seed peeling on dispersal. The effects of a single factor may be more than their interactions between seed size, soil burial and seed peeling on dispersal. These results implied that seed size, soil burial and seed peeling may affect plant population expansion and regeneration by affecting the dispersal and hoarding of animals.

Hepatocyte Growth Factor Has Unique Functions in Keratinocytes that Differ from those of IL-17A and TNF and May Contribute to Inflammatory Pathways in Hidradenitis Suppurativa.

Hidradenitis suppurativa (HS) is a chronic inflammatory disease that is difficult to control, and its mechanism remains unclear. Hepatocyte GF (HGF) has been reported to be significantly upregulated in the serum and skin of patients with HS, especially in the lesions with tunnels. In this study, we examined the transcriptome of HGF-treated keratinocytes and compared it with genetic profiling of HS lesions. HGF was highly expressed in HS skin, especially in the deep dermis, compared with that in healthy controls, and its source was mainly fibroblasts. HGF upregulated more genes in keratinocytes than IL-17A or TNF-a, and these genes included multiple epithelial-mesenchymal transition-related genes. Differentially expressed genes in HGF-stimulated keratinocytes were involved in activation of epithelial-mesenchymal transition-related pathways. These HGF-induced genes were significantly upregulated in HS lesions compared with those in healthy skin and nonlesions and were more strongly associated with HS tunnels. In summary, HGF was highly expressed in HS and induced epithelial-mesenchymal transition-related genes in keratinocytes; HGF-induced genes were highly associated with gene profiling of HS with tunnels, suggesting that HGF may be involved in HS tunnel formation through epithelial-mesenchymal transition.

A deep neural network for positioning and inter-crystal scatter identification in multiplexed PET detectors: a simulation study.

Objective.High-resolution positron emission tomography (PET) relies on the accurate positioning of annihilation photons impinging the crystal array. However, conventional positioning algorithms in light-sharing PET detectors are often limited due to edge effects and/or the absence of additional information for identifying and correcting scattering within the crystal array (known as inter-crystal scattering). This study explores the feasibility of deep neural network (DNN) techniques for more precise event positioning in finely segmented and highly multiplexed PET detectors with light-sharing.Approach.Initially, a Geant4 Application for Tomographic Emission (GATE) simulation was used to study the spatial and statistical properties of inter-crystal scatter (ICS) events in finely segmented LYSO PET detectors. Next, a DNN for crystal localisation was designed, trained and tested with light distributions of photoelectric (P) and Compton + photoelectric (CP) events simulated using optical GATE and an analytical method to speed up data generation. Using the statistical properties of ICS events, an energy-guided positioning algorithm was then built into the DNN. The positioning algorithm enables selection of the unique or first crystal of interaction in P and CP events, respectively. Performance of the DNN was compared with Anger logic using light distributions from simulated 511 keV point sources placed at different locations around a single PET detector module.Main results. The fraction of events forward and backward scattered in the LYSO detector was 0.54 and 0.46, respectively, whereas naïve application of the Klein-Nishina formulation predicts 70% forward scatter. Despite coarse photodetector data due to signal multiplexing, the DNN demonstrated a crystal classification accuracy of 90% for P events and 82% for CP events. For crystal positioning, the DNN outperformed Anger logic by at least 34% and 14% for P and CP events, respectively. Further improvement is somewhat constrained by the physics-specifically, the ratio of backward to forward scattering of gamma rays within the crystal array being close to 1. This prevents selecting the first crystal of interaction in CP events with a high degree of certainty.Significance.Light sharing and multiplexed PET detectors are common in high-resolution PET, yet their traditional positioning algorithms often underperform due to edge effects and/or the difficulty in correcting ICS events. Our study indicates that DNN-based event positioning has the potential to enhance 2D coincidence event positioning accuracy by nearly a factor of 3 compared to Anger logic. However, further improvements are difficult to foresee without additional information such as event timing.

Identifying antibiotic-resistant strains via cell sorting and elastic-light-scatter phenotyping.

The proliferation and dissemination of antimicrobial-resistant bacteria is an increasingly global challenge and is attributed mainly to the excessive or improper use of antibiotics. Currently, the gold-standard phenotypic methodology for detecting resistant strains is agar plating, which is a time-consuming process that involves multiple subculturing steps. Genotypic analysis techniques are fast, but they require pure starting samples and cannot differentiate between viable and non-viable organisms. Thus, there is a need to develop a better method to identify and prevent the spread of antimicrobial resistance. This work presents a novel method for detecting and identifying antibiotic-resistant strains by combining a cell sorter for bacterial detection and an elastic-light-scattering method for bacterial classification. The cell sorter was equipped with safety mechanisms for handling pathogenic organisms and enabled precise placement of individual bacteria onto an agar plate. The patterning was performed on an antibiotic-gradient plate, where the growth of colonies in sections with high antibiotic concentrations confirmed the presence of a resistant strain. The antibiotic-gradient plate was also tested with an elastic-light-scattering device where each colony's unique colony scatter pattern was recorded and classified using machine learning for rapid identification of bacteria. Sorting and patterning bacteria on an antibiotic-gradient plate using a cell sorter reduced the number of subculturing steps and allowed direct qualitative binary detection of resistant strains. Elastic-light-scattering technology is a rapid, label-free, and non-destructive method that permits instantaneous classification of pathogenic strains based on the unique bacterial colony scatter pattern. KEY POINTS: • Individual bacteria cells are placed on gradient agar plates by a cell sorter • Laser-light scatter patterns are used to recognize antibiotic-resistant organisms • Scatter patterns formed by colonies correspond to AMR-associated phenotypes.

A rotating beam-blocker method for cone beam CT scatter correction.

BACKGROUND: Cone beam CT (CBCT) is widely utilized in clinics. However, the scatter artifact degrades the CBCT image quality, hampering the expansion of CBCT applications. Recently, beam-blocker methods have been used for CBCT scatter correction and proved their high cost-effectiveness. PURPOSE: A rotating beam-blocker (RBB) method for CBCT scatter correction was proposed to complete scatter correction and image reconstruction within a single scan in both full- and half-fan scan scenarios. METHODS: The RBB consisted of two open regions and two blocked regions, and was designed as a centrosymmetric structure. The open and blocked projections could be alternatively obtained within one single rotation. The open projections were corrected with the scatter signal calculated from the blocked projections, and then used to reconstruct the 3D image via the Feldkamp-Davis-Kress algorithm. The performance of the RBB method was evaluated on head and pelvis phantoms in scenarios with and without a bowtie filter. The images obtained from nine repeated scans in each scenario were used to calculate the evaluation metrics including the CT number error, spatial nonuniformity (SNU) and contrast-to-noise ratio (CNR). RESULTS: For the head phantom, the CT number error was decreased to <5 after scatter correction from >200 HU before correction when scanned without a bowtie filter, and to <4 from >160 HU when scanned with a full bowtie filter. For the pelvis phantom, the CT number error was reduced to <12 after scatter correction from >250 HU before correction when scanned without a bowtie filter, and to <10 from >190 HU when scanned with a half bowtie filter. After scatter correction, the uniformity and contrast were both improved, resulting in an SNU of >79% decrease and CNR of >2 times increase, respectively. CONCLUSIONS: High-quality CBCT images could be obtained in a single scan after using the proposed RBB method for scatter correction, enabling more accurate image guidance for surgery and radiation therapy applications. With almost no time delay between the successive open and blocked projections, the RBB method could eliminate the motion-induced anatomical mismatches between the corresponding open and blocked projections and could find particular usefulness in thoracic and abdominal imaging.

Substrate scent-induced disproportionate seed dispersal by rodents.

Conspecific adults impose strong negative density-dependent effects on seed survival nearby parent trees, however, the underlying mechanisms are diversified and remain unclear. In this study, we presented consistent evidence that parent-scented forest floor masked seed odor, reduced cache recovery rate by scatter-hoarding animals, and then increased seed dispersal far away from mother trees. Our results showed that seed odors of Korean pine Pinus koraiensis match well with the volatile profile of their forest floor. Moreover, scatter-hoarding animals selectively transported P. koraiensis seeds toward the areas where seed odor was more contrasting against the background substrate, possibly due to the fact that accumulation of conspecific volatile compounds in caches hindered seed detection by scatter-hoarding animals. Our study provides insight into the role of leaf litter in directing seed dispersal process, representing a novel mechanism by which P. koraiensis increases selection for seed dispersal far away from the parent tree.

Correction of scatter in CBCT with a new grid design.

Objective.This study aims at developing a simple and rapid Compton scatter correction approach for cone-beam CT (CBCT) imaging.Approach.In this work, a new Compton scatter estimation model is established based on two distinct CBCT scans: one measures the full primary and scatter signals without anti-scatter grid (ASG), and the other measures a portion of primary and scatter signals with ASG. To accelerate the entire data acquisition speed, a half anti-scatter grid (h-ASG) that covers half of the full detector surface is proposed. As a result, the distribution of scattered x-ray photons could be estimated from a single CBCT scan. Physical phantom experiments are conducted to validate the performance of the newly proposed scatter correction approach.Main results.Results demonstrate that the proposed half grid approach can quickly and precisely estimate the distribution of scattered x-ray photons from only one single CBCT scan, resulting in a significant reduction of shading artifacts. In addition, it is found that the h-ASG approach is less sensitive to the grid transmission fractions, grid ratio and object size, indicating a robust performance of the new method.Significance.In the future, the Compton scatter artifacts can be quickly corrected using a half grid in CBCT imaging.

Artificial intelligence-based joint attenuation and scatter correction strategies for multi-tracer total-body PET.

BACKGROUND: Low-dose ungated CT is commonly used for total-body PET attenuation and scatter correction (ASC). However, CT-based ASC (CT-ASC) is limited by radiation dose risks of CT examinations, propagation of CT-based artifacts and potential mismatches between PET and CT. We demonstrate the feasibility of direct ASC for multi-tracer total-body PET in the image domain. METHODS: Clinical uEXPLORER total-body PET/CT datasets of [18F]FDG (N = 52), [18F]FAPI (N = 46) and [68Ga]FAPI (N = 60) were retrospectively enrolled in this study. We developed an improved 3D conditional generative adversarial network (cGAN) to directly estimate attenuation and scatter-corrected PET images from non-attenuation and scatter-corrected (NASC) PET images. The feasibility of the proposed 3D cGAN-based ASC was validated using four training strategies: (1) Paired 3D NASC and CT-ASC PET images from three tracers were pooled into one centralized server (CZ-ASC). (2) Paired 3D NASC and CT-ASC PET images from each tracer were individually used (DL-ASC). (3) Paired NASC and CT-ASC PET images from one tracer ([18F]FDG) were used to train the networks, while the other two tracers were used for testing without fine-tuning (NFT-ASC). (4) The pre-trained networks of (3) were fine-tuned with two other tracers individually (FT-ASC). We trained all networks in fivefold cross-validation. The performance of all ASC methods was evaluated by qualitative and quantitative metrics using CT-ASC as the reference. RESULTS: CZ-ASC, DL-ASC and FT-ASC showed comparable visual quality with CT-ASC for all tracers. CZ-ASC and DL-ASC resulted in a normalized mean absolute error (NMAE) of 8.51 ± 7.32% versus 7.36 ± 6.77% (p < 0.05), outperforming NASC (p < 0.0001) in [18F]FDG dataset. CZ-ASC, FT-ASC and DL-ASC led to NMAE of 6.44 ± 7.02%, 6.55 ± 5.89%, and 7.25 ± 6.33% in [18F]FAPI dataset, and NMAE of 5.53 ± 3.99%, 5.60 ± 4.02%, and 5.68 ± 4.12% in [68Ga]FAPI dataset, respectively. CZ-ASC, FT-ASC and DL-ASC were superior to NASC (p < 0.0001) and NFT-ASC (p < 0.0001) in terms of NMAE results. CONCLUSIONS: CZ-ASC, DL-ASC and FT-ASC demonstrated the feasibility of providing accurate and robust ASC for multi-tracer total-body PET, thereby reducing the radiation hazards to patients from redundant CT examinations. CZ-ASC and FT-ASC could outperform DL-ASC for cross-tracer total-body PET AC.

Dual-source photon-counting CT: impact of residual cross-scatter on quantitative spectral results.

Dual-source photon-counting CT combines the high temporal resolution and high pitch of dual-source CT with the material quantification capabilities of photon-counting CT. It, however, results in cross-scatter that increases in severity with increased patient size and collimation. This cross-scatter must be corrected to ensure the removal of scatter artifacts and improve quantitative accuracy. To evaluate residual cross-scatter of a first-generation dual-source photon-counting CT and the effect of phantom size, collimation, and radiation dose, a phantom was scanned in single- and dual-source modes with and without its extension ring at three collimations and three radiation doses. Virtual monoenergetic images (VMI) at 50 keV, VMI 150 keV, and iodine density maps were reconstructed to determine variation between acquisition parameters in single- and dual-source modes. Additionally, differences relative to single-source acquisitions and to single-source and small collimation acquisitions were calculated to reflect residual cross-scatter with and without matched collimation. At VMI 50 keV, inserts exhibited accuracy and similar variation between single- and dual-source modes, averaging 5.4 ± 2.6 and 6.2 ± 2.5 HU, respectively, across phantom size, collimation, and radiation dose. Differences relative to single-source measured 5.1 ± 8.5 and 0.4 ± 4.2 HU while differences relative to single-source and small collimation acquisitions were 6.4 ± 10.8 HU and -0.5 ± 3.9 HU for VMI 50 and 150 keV, respectively. This minimal residual cross-scatter increases confidence in the quantitative accuracy of spectral results necessary for clinical applications of dual-source photon-counting CT with motion, such as cardiac imaging.