Small Field Of View Research Articles

Detecting the Early Optical Flashes of Gamma-Ray Bursts with Small Telescope Arrays

We present an observational approach for the independent detection of the early optical emission of long gamma-ray bursts (GRBs). For this purpose, we explore the potential of the Large Array Survey Telescope (LAST). This array of small optical telescopes can be used to scan a wide region of the sky, and to focus on a smaller field of view with increased sensitivity, as needed. The modularity of the array facilitates dynamic scanning of multiple fields, by shifting telescope pointing directions with high cadence. This can significantly increase the effective sky-coverage of a blind survey on short timescales. For events associated with gamma-ray counterparts, the valuable early time data can supplement high-energy observations. Regardless of gamma-ray association, detections can potentially be used to explore various phenomena associated with GRBs, such as orphan afterglows; dirty fireballs; and choked jets. We simulate a sample of GRBs and their respective optical signals at early times. After accounting for dynamic cadence, the light curves are given as input to a machine-learning classifier, used to identify astrophysical transients. We find that, by dedicating half of an LAST array to a blind search, one would expect to independently detect 7–11 GRBs yr–1, corresponding to an approximate intrinsic event rate of 0.12 deg–2 yr–1.

Experimental Examination of Additively Manufactured Patterns on Structural Nuclear Materials for Digital Image Correlation Strain Measurements

BackgroundThere are a limited number of commercially available sensors for monitoring the deformation of materials in-situ during harsh environment applications, such as those found in the nuclear and aerospace industries. Such sensing devices, including weldable strain gauges, extensometers, and linear variable differential transformers, can be destructive to material surfaces being investigated and typically require relatively large surface areas to attach (> 10 mm in length). Digital image correlation (DIC) is a viable, non-contact alternative to in-situ strain deformation. However, it often requires implementing artificial patterns using splattering techniques, which are difficult to reproduce.ObjectiveAdditive manufacturing capabilities offer consistent patterns using programmable fabrication methods.MethodsIn this work, a variety of small-scale periodic patterns with different geometries were printed directly on structural nuclear materials (i.e., stainless steel and aluminum tensile specimens) using an aerosol jet printer (AJP). Unlike other additive manufacturing techniques, AJP offers the advantage of materials selection. DIC was used to track and correlate strain to alternative measurement methods during cyclic loading, and tensile tests (up to 1100 µɛ) at room temperature.ResultsThe results confirmed AJP has better control of pattern parameters for small fields of view and facilitate the ability of DIC algorithms to adequately process patterns with periodicity. More specifically, the printed 100 μm spaced dot and 150 μm spaced line patterns provided accurate measurements with a maximum error of less than 2% and 4% on aluminum samples when compared to an extensometer and commercially available strain gauges.ConclusionOur results highlight a new pattern fabrication technique that is form factor friendly for digital image correlation in nuclear applications.

Semi-automated protocol to quantify and characterize fluorescent three-dimensional vascular images.

The microvasculature facilitates gas exchange, provides nutrients to cells, and regulates blood flow in response to stimuli. Vascular abnormalities are an indicator of pathology for various conditions, such as compromised vessel integrity in small vessel disease and angiogenesis in tumors. Traditional immunohistochemistry enables the visualization of tissue cross-sections containing exogenously labeled vasculature. Although this approach can be utilized to quantify vascular changes within small fields of view, it is not a practical way to study the vasculature on the scale of whole organs. Three-dimensional (3D) imaging presents a more appropriate method to visualize the vascular architecture in tissue. Here we describe the complete protocol that we use to characterize the vasculature of different organs in mice encompassing the methods to fluorescently label vessels, optically clear tissue, collect 3D vascular images, and quantify these vascular images with a semi-automated approach. To validate the automated segmentation of vascular images, one user manually segmented one hundred random regions of interest across different vascular images. The automated segmentation results had an average sensitivity of 83±11% and an average specificity of 91±6% when compared to manual segmentation. Applying this procedure of image analysis presents a method to reliably quantify and characterize vascular networks in a timely fashion. This procedure is also applicable to other methods of tissue clearing and vascular labels that generate 3D images of microvasculature.

A comparative investigation of three-dimensional printing models (rapid prototyping) made by imaging systems including multidetector computed tomography and cone-beam computed tomography systems

Abstract Introduction: Biomedical models (rapid prototyping) had a vast use in maxillofacial diagnosis and surgeries. Using this technology can lead to improvement in preoperative treatment planning and an increase in surgery quality. In this study, we investigated and compared the models derived from multidetector computed tomography (MDCT) and cone-beam computed tomography (CBCT) radiography systems. Aim: In this study, we investigated and compared the models derived from MDCT and CBCT radiography systems to see which is the most accurate. Materials and Methods: Five dried human mandibles were chosen in this study. These landmarks were chosen to investigate the reproduction ability: mental foramen, genial tubercle, central incisor, alveolar crest edge to the inferior mandibular border in midline, two bone defects in approximate dimensions of 3 × 3 mm2, first molar socket depth in the mesiobuccal line angle, mesiodistal length of tooth socket bone at the buccal and buccolingual width of tooth socket bone at mesial. Radiographs were taken using one MDCT and two CBCT systems. Then, models were built through a three-dimensional (3D) printer, and the mentioned landmarks were measured using a digital caliper. Data were entered in SPSS version 23 software and were analyzed with the ANOVA and Tukey tests. Results: In the reproduction of superior-inferior dimension and mesiodistal width of all mentioned landmarks, there were no significant differences between models made by data derived from Cranex 3D and NewTom 3G with a small field of view, in comparison with the gold standard (P > 0.05). However, there is a significant difference in the reproduction of landmarks between models made from MDCT and NewTom 3G with a large field of view, in comparison with the gold standard (P < 0.05). Conclusion: Models made from CBCT Devices with a small field of view have an acceptable and reliable accuracy for assessing bone structures. However, for CBCT devices with a large field of view and computed tomography-scan devices, models have less accuracy.

Large-scale flow field super-resolution via local-global fusion convolutional neural networks

Particle image velocimetry (PIV) techniques have a limited field of view of the flow field and can only capture high-resolution flow fields in localized areas. To obtain a larger measurement range, multiple cameras must be used to capture the flow field simultaneously and then stitch the parts together. However, this method can be expensive. We propose the local-global fusion convolutional neural network (LGF-CNN) for reconstructing large-field flow fields with high spatial resolution based only on two flow data types: local small-field high spatial resolution wake velocity fields and global large-field low spatial resolution velocity fields. The core of the model consists of convolutional neural network (CNN) architecture to learn the mapping relationship between the small field of view with high spatial resolution and the large field of view with low spatial resolution. Using the effectively trained LGF-CNN model, we demonstrate its ability to reconstruct high-resolution velocity fields around the circular cylinder. The LGF-CNN is rigorously validated on a number of representative datasets, including simulated data for Reynolds numbers of 200 and 500, as well as experimental data for a Reynolds number of 3.3 × 104 with the steady jet at the rear stagnation point of the cylinder. The results demonstrate the ability of LGF-CNN to generate accurate velocity fields with high spatial resolution, including reliable detection of high-frequency components. The proposed method could reduce the number of cameras required for large-field, high spatial resolution PIV measurements, thereby reducing experimental costs.

Reconstruction of Cosmological Initial Density Field with Observations from the Epoch of Reionization

The initial density distribution provides a basis for understanding the complete evolution of cosmological density fluctuations. While reconstruction in our local Universe exploits the observations of galaxy surveys with large volumes, observations of high-redshift galaxies are performed with a small field of view and therefore can hardly be used for reconstruction. Here, we propose reconstructing the initial density field using the H i 21 cm and CO line intensity maps from the epoch of reionization. Observations of these two intensity maps provide complementary information on the density field—the H i 21 cm field is a proxy of matter distributions in the neutral regions, while the CO line intensity maps are sensitive to the high-density, star-forming regions that host the sources for reionization. Technically, we employ the conjugate gradient method and develop the machinery for minimizing the cost function for the intensity mapping observations. Analytical expressions for the gradient of cost function are derived explicitly. We show that the resimulated intensity maps match the input maps of mock observations using semi-numerical simulations of reionization with an rms error ≲7% at all stages of reionization. This reconstruction is also robust with an rms error of ∼10% when an optimistic level of shot noise is applied to the CO map or white noise at the level of ≲10% of the standard deviation is applied to each map. Our proof-of-concept work demonstrates the robustness of the reconstruction method, thereby providing an effective technique for reconstructing the cosmological initial density distribution from high-redshift observations.

Feasibility of diffusion tensor imaging in cervical spondylotic myelopathy using MUSE sequence

The most frequent type of spinal cord injury is cervical spondylotic myelopathy (CSM). Conventional structural magnetic resonance imaging (MRI) is the gold diagnosis standard for CSM. Diffusion tensor imaging (DTI) could reflect microstructural changes in the spinal cord by tracing water molecular diffusion in early stages of CSM. However, due to the complex local anatomical structure and small field of view of the spinal cord, the imaging effect of traditional DTI imaging on the spinal cord is limited. MUSE (MUltiplexed Sensitivity-Encoding) -DTI is a novel diffusion-weighted imaging (DWI) sequence that achieves higher signal intensity through multiple excitation acquisition. MUSE sequence may improve the quality of spinal cord DTI imaging. Prospective study. This study aimed to investigate the clinical diagnosis value of a novel protocol of MUSE-DTI in patients with cervical spondylotic myelopathy (CSM). From August 2021 to March 2022, a total of 60 subjects (22-71 years) were enrolled, including 51 CSM patients (22 males, 29 females) and 9 healthy subjects (4 males and 5 females). Each subject underwent a MUSE-DTI examination and a clinical Japanese Orthopedic Association (JOA) scale. We measured values of FA (Fractional Anisotropy), MD (Mean Diffusivity), AD (Axial Diffusivity), and RD (Radial Diffusivity), and collected the clinical JOA scores of each subject before the MR examination. A 3.0T MR scanner (Signa Architect, GE Healthcare) performed the MUSE-DTI sequence on each subject. The cervical canal stenosis of subjects was classified from grade 0 to grade Ⅲ according to the method of an MRI grading system. FA, MD, AD, and RD maps were generated by postprocessing MUSE-DTI data on the GE workstation. Regions of interest (ROIs) were manually drawn at the C2 vertebral body level and C2/3-C6/7 intervertebral disc levels by covering the whole spinal cord. The clinical severity of myelopathy of subjects was assessed by the clinical Japanese Orthopedic Association scale (JOA). MUSE-DTI can acquire a high-resolution diffusion image compared to traditional DTI. The FAMCL values showed a decreasing trend from grade 0 to grade Ⅲ, while the MDMCL, ADMCL, and RDMCL values showed an overall increasing trend. Significant differences in MDMCL, ADMCL, and RDMCL values were found between adjacent groups among grades Ⅰ-Ⅲ (p<.05). The ADC2 values in CSM patients (grade I-Ⅲ) were significantly lower than in healthy individuals (grade 0) (p=.019). The clinical JOA score has a significant correlation with FAMCL (p=.035), MDMCL (p<.001), ADMCL (p<.001), and RDMCL (p<.001) values. MUSE-DTI displayed a better image quality compared to traditional DTI. MUSE-DTI parameters displayed a grade-dependent trend. All the MUSE-DTI parameters at MCL were correlated with the clinical JOA scores. The ADC2 values can reflect the secondary damage of distal spinal cord. Therefore, MUSE-DTI could be a reliable biomarker for clinical auxiliary diagnosis of spinal cord injury severity in cervical spondylotic myelopathy.

SSTU: Swin-Spectral Transformer U-Net for hyperspectral whole slide image reconstruction

Whole Slide Imaging and Hyperspectral Microscopic Imaging provide great quality data with high spatial and spectral resolution for histopathology. Existing Hyperspectral Whole Slide Imaging systems combine the advantages of the techniques above, thus providing rich information for pathological diagnosis. However, it cannot avoid the problems of slow acquisition speed and mass data storage demand. Inspired by the spectral reconstruction task in computer vision and remote sensing, the Swin-Spectral Transformer U-Net (SSTU) has been developed to reconstruct Hyperspectral Whole Slide images (HWSis) from multiple Hyperspectral Microscopic images (HMis) of small Field of View and Whole Slide images (WSis). The Swin-Spectral Transformer (SST) module in SSTU takes full advantage of Transformer in extracting global attention. Firstly, Swin Transformer is exploited in space domain, which overcomes the high computation cost in Vision Transformer structures, while it maintains the spatial features extracted from WSis. Furthermore, Spectral Transformer is exploited to collect the long-range spectral features in HMis. Combined with the multi-scale encoder-bottleneck-decoder structure of U-Net, SSTU network is formed by sequential and symmetric residual connections of SSTs, which reconstructs a selected area of HWSi from coarse to fine. Qualitative and quantitative experiments prove the performance of SSTU in HWSi reconstruction task superior to other state-of-the-art spectral reconstruction methods.

See farther and more: a master-slave UAVs based synthetic optical aperture imaging system with wide and dynamic baseline.

An open challenge remained in designing an optical system to capture the aerial image with a wide field of view (FoV) and high resolution. The optical system of one camera from a single unmanned aerial vehicle (UAV) can hardly promise the FoV and resolution. The conventional swarm UAVs can form the camera array with a short or fixed baseline. They can capture the images with a wide FoV and high resolution, but the cost is the requirement of many UAVs. We aim to design a camera array with a wide and dynamic baseline to reduce the demand for UAVs to organize a synthetic optical aperture. In this thought, we propose a master-slave UAVs-based synthetic optical aperture imaging system with a wide and dynamic baseline. The system consists of one master UAV and multiple slave UAVs. Master and slave UAVs provide the global and local FoVs, respectively, and improve the efficiency of image acquisition. In such a system, fusing UAV images becomes a new challenge due to two factors: (i) the small FoV overlap of slave UAVs and (ii) the gap in resolution scale from slave to master UAV images. To deal with it, a coarse-to-fine stitching method is proposed to stitch up the multi-view images into one to obtain a wide FoV with high resolution. A video stabilization method has also been designed for the proposed imaging system. Challenges caused by wide and dynamic baselines can thus be solved by the above methods. Actual data experiments demonstrate that the proposed imaging system achieves high-quality imaging results.

Low-cost reversible tandem lens mesoscope for brain imaging in rodents.

The development of imaging systems that are cost-efficient and modular is essential for modern neuroscience research. In the current study, we designed, developed, and characterized a low-cost reversible tandem lens mesoscope for brain imaging in rodents. Using readily available components, we assembled a robust imaging system that is highly efficient and cost-effective. We developed a mesoscope that offers high-resolution structural and functional imaging with cost-effective lenses and CMOS camera. The reversible tandem lens configuration of the mesoscope offers two fields of view (FOVs), which can be achieved by swapping the objective and imaging lenses. The large FOV configuration of provides a spatial resolution up to , and the small FOV configuration of provides a resolution of up to . We demonstrate the efficiency of our system for imaging neuronal calcium activity in both rat and mouse brains in vivo. The careful selection of the mesoscope components ensured its compactness, portability, and versatility, meaning that different types of samples and sample holders can be easily accommodated, enabling a range of different experiments both in vivo and in vitro. The custom-built reversible FOV mesoscope is cost-effective and was developed for under US$10,000 with excellent performance.

Hybrid Grid Pattern Star Identification Algorithm Based on Multi-Calibration Star Verification.

In order to solve the star identification problem in the lost space mode for scientific cameras with small fields of view and higher instruction magnitudes, this paper proposes a star identification algorithm based on a hybrid grid pattern. The application of a hybrid pattern generated by multi-calibration stars in the initial matching enables the position distribution features of neighboring stars around the main star to be more comprehensively described and avoids the interference of position noise and magnitude noise as much as possible. Moreover, calibration star filtering is adopted to eliminate incorrect candidates and pick the true matched navigation star from candidate stars in the initial match. Then, the reference star image is utilized to efficiently verify and determine the final identification results of the algorithm via the nearest principle. The performance of the proposed algorithm in simulation experiments shows that, when the position noise is 2 pixels, the identification rate of the algorithm is 96.43%, which is higher than that of the optimized grid algorithm by 2.21% and the grid algorithm by 4.05%; when the magnitude noise is 0.3 mag, the star identification rate of the algorithm is 96.45%, which is superior to the optimized grid algorithm by 2.03% and to the grid algorithm by 3.82%. In addition, in the actual star image test, star magnitude values of ≤12 mag can be successfully identified using the proposed algorithm.

Three-dimensional coherence beamforming using row-column arrays and matrix arrays

Much advancement in 3D ultrasound imaging has been achieved in recent years, allowing for its implementation in many research capacities. Translation of 3D imaging to a clinical setting has been hindered by small fields of view, expensive equipment and poor image quality. For ultrafast imaging, these challenges are accentuated by the need for a small number of transmission events. The row-column array is an emerging technology which can produce large field-of-view 3D ultrasound images, however, they can produce major artefacts when operated at high frame rates. Here we present some techniques which have been developed to improve the image quality and reduce the artifact level of row-column arrays by exploiting the incoherence of the transmission schemes. Presented will be the Row-Column specific Frame Multiply and Sum beamforming along with a technique for implementing Acoustic Sub-Aperture Processing which improves signal-to-noise ratio whilst also increasing the effective frame rate. Additional coherence-based algorithms, which have previously been developed for 2D imaging, are implemented and presented here for 3D imaging using a matrix array probe. All of the above algorithms have been optimised for super-resolution but should improve all types of 3D ultrasound imaging.

Impact of cone-beam computed tomography artifacts on dose calculation accuracy for lung cancer.

To implement image-guided adaptive radiotherapy (IGART), many studies investigated dose calculations on cone-beam computed tomography (CBCT). A high HU accuracy is crucial for a high dose calculation accuracy and many imaging sites showed satisfactory results. It has been shown that the dose calculation accuracy for lung cancer lags behind. To examine why the dose calculation accuracy for lung is insufficient, the relative effects of the field-of-view (FOV), breathing motion, and scatter on dose calculation accuracy were studied. A framework was built to simulate CBCT scans for lung cancer patients by forward projecting repeat CT (rCT) scans for two scan geometries: small (SFOV) and medium FOV (MFOV). Breathing motion was modeled by applying a 4D deformation vector field to the mid-position rCT. Scatter was modeled by Monte-Carlo simulations with/without an anti-scatter grid (ASG). Simulated projections were reconstructed using filtered back-projection with/without scatter correction. In case of the SFOV, the CBCT images were patched with the planning CT scan in axial direction. The treatment plan was recalculated on the rCT and simulated CBCT. The mean Hounsfield unit (HU) difference (ΔHUmean), the structural similarity index measure (SSIM), and γ metrics were calculated for the CBCT datasets of various imaging settings. The differences in HU, SSIM and dose calculation accuracy for CBCTs with and without breathing motion were negligible (mean ΔHUmean=6.4vs. 13.7, mean SSIM=0.941vs. 0.957, mean γ (ref=MFOV)=0.75). The SFOV resulted in a lower HU (mean ΔHUmean=-9.2vs. 13.7) and SSIM (mean SSIM=0.912vs. 0.957), and therefore in dose differences compared to the MFOV (mean γ=1.22). Scatter led to considerable discrepancies in all metrics. Adding only the ASG improved the results more than only applying a scatter correction algorithm. Combining ASG and scatter correction algorithm resulted in an even higher dose calculation accuracy. Scatter and FOV are the main contributors to dose inaccuracies and motion has only a minor effect on dose calculation accuracy. Therefore, utilizing an appropriate scatter correction and FOV is important to achieve sufficient dose calculation accuracy to facilitate IGART for lung.

The Accuracy of Guided Implant Surgery With Different Fields of View of Cone-Beam Computerized Tomography.

Although a smaller size field of view (FOV) of cone-beam computerized tomography (CBCT) reduces radiation exposure, its effect on the accuracy of static computer-aided implant surgery (s-CAIS) remains unknown. This study aimed to evaluate the impact of the size of FOV on the accuracy of s-CAIS and to investigate if the arch affects this effect. A total of 32 implant sites on 8 identical scannable models (maxillae and mandibles) were randomly allocated to 2 FOV sizes: test (5 × 5 cm) and control (10 × 10 cm). All models were scanned with an intraoral scanner (IOS). With the registration of the surface scan and CBCT image, a prosthetic-driven implant position was planned. Following the fabrication of surgical templates, a single-blinded surgeon placed all implants with the fully guided s-CAIS protocol. IOS captured the implant positions with the scan body attached. Implant-planning software measured the angular deviation, 3-dimensional (3D) deviation at the crest, and 3D deviation at the apex between preplanned and actual implant positions. Two-way analysis of variance was used to analyze the effect of FOV and arch on the deviations. The size of FOV did not show a significant effect (P > .198) on angular deviation, 3D deviation at the crest, or 3D deviation at the apex. No significant difference was found when comparing the effect of the size of FOV between the maxillary and mandibular implants. In conclusion, the use of small FOV CBCT demonstrated comparable accuracy of s-CAIS to the use of medium FOV CBCT.

Optical–Mechanical Integration Analysis and Validation of LiDAR Integrated Systems with a Small Field of View and High Repetition Frequency

Integrated systems are facing complex and changing environments with the wide application of atmospheric LiDAR in civil, aerospace, and military fields. Traditional analysis methods employ optical software to evaluate the optical performance of integrated systems, and cannot comprehensively consider the influence of optical and mechanical coupling on the optical performance of the integrated system, resulting in the unsatisfactory accuracy of the analysis results. Optical–mechanical integration technology provides a promising solution to this problem. A small-field-of-view LiDAR system with high repetition frequency, low energy, and single-photon detection technology was taken as an example in this study, and the Zernike polynomial fitting algorithm was programmed to enable transmission between optical and mechanical data. Optical–mechanical integration technology was employed to obtain the optical parameters of the integrated system under a gravity load in the process of designing the optical–mechanical structure of the integrated system. The experimental validation results revealed that the optical–mechanical integration analysis of the divergence angle of the transmission unit resulted in an error of 2.586%. The focal length of the telescope increased by 89 μm, its field of view was 244 μrad, and the error of the detector target surface spot was 4.196%. The continuous day/night detection results showed that the system could accurately detect the temporal and spatial variations in clouds and aerosols. The inverted optical depths were experimentally compared with those obtained using a solar photometer. The average optical depth was 0.314, as detected using LiDAR, and 0.329, as detected by the sun photometer, with an average detection error of 4.559%. Therefore, optical–mechanical integration analysis can effectively improve the stability of the structure of highly integrated and complex optical systems.

Feasibility of frozen soft tissues to simulate fresh soft tissue conditions in cone beam CT scans.

To evaluate the feasibility of frozen soft tissues in simulating fresh soft tissues of pig mandibles using cone beam CT (CBCT). Two fresh pig mandibles with soft tissues containing 2 tubes filled with a radiopaque homogeneous solution were scanned using 4 CBCT units and 2 field-of-view (FOV) sizes each. The pig mandibles were deep-frozen and scanned again. Three cross-sections were exported from each CBCT volume and grouped into pairs, with one cross-section representing a fresh and one a frozen mandible. Three radiologists compared the pairs and attributed a score to assess the relative image quality using a 5-point scale. Mean grey values and standard deviation were obtained from homogeneous areas in the tubes, compared using the Wilcoxon matched-pair signed-rank test and subjected to Pearson correlation analysis between fresh and frozen physical states (α = .05). Subjective evaluation revealed similarity of the CBCT image quality between fresh and frozen states. The distribution of mean grey values was similar between fresh and frozen states. Mean grey values of the frozen state in the small FOV were significantly greater than those of the fresh state (P = .037), and noise values of the frozen state in the large FOV were significantly greater than those of the fresh state (P = 0.007). Both mean grey values and noise exhibited significant and positive correlations between fresh and frozen states (P < 0.01). The freezing of pig mandibles with soft tissues may serve as a method to prolong their usability and working time when CBCT imaging is planned.

Full-field deformation measurement of 2D-DIC based on virtual camera array in small field of view

Full-field deformation measurement of 2D-DIC based on virtual camera array in small field of view

Improvement to the Epoch of Reionisation power spectrum using simulations with the Central Redundant Array Mega-tile (CRAM)

Abstract Detection of the 21 cm signal from the Epoch of Reionisation (EoR) ( $z \sim 6 - 10$ ) amidst the dominant foregrounds, which are 3–4 orders of magnitude greater than the weak cosmological signal, is a challenging task for the existing 21 cm experiments. The detection is further challenged by the large Field of View (FoV) of the instrument used for observation, as it becomes necessary to excise foregrounds present within the FoV to make a successful detection. In response to the challenges faced, in our previous work, we developed and installed a new instrument – the Central Redundant Array Mega-tile (CRAM) – and integrated it within the MWA Phase II configuration. It is a larger antenna tile configuration ( $8\times 8$ dipoles) with a smaller FoV at every frequency under consideration and has multiple sidelobes of reduced response when compared with the existing Murchison Widefield Array (MWA) tiles. In this paper, we aim to demonstrate through power spectrum simulations that using the larger tile, such as the CRAM, can reduce the impact of bright radio foregrounds near the field edge. For the pedagogical approach aimed with this work, we developed a power spectrum pipeline to estimate the cylindrically averaged power spectrum. The power spectrum is estimated for MWA-MWA baselines and CRAM-MWA baselines using analytical beams, simulated diffuse sky maps and a semi-numerical 21 cm signal. Employing a drift scanning strategy, we estimate 1D and 2D power spectra for a series of two-minute observations spanning 24 hrs using the diffuse sky maps. Our simulations predict a power reduction at the edge of the EoR wedge. The reduction in foreground power is confirmed with the Fisher analysis of the expected signal-to-noise ratio (SNR) improvement, which reports a higher SNR with the power estimations from CRAM baselines when compared with the regular MWA baselines. The reduced power obtained with the CRAM baselines is consistent with the fact that the larger tile configuration has reduced the impact of foregrounds from near the horizon.

Protostellar Cores in Sagittarius B2 N and M

We present 500 and 700 au resolution 1 and 3 mm Atacama Large Millimeter/submillimeter Array observations, respectively, of protostellar cores in protoclusters Sagittarius B2 (Sgr B2) North (N) and Main (M), parts of the most actively star-forming cloud in our Galaxy. Previous lower-resolution (5000 au) 3 mm observations of this region detected ∼150 sources inferred to be young stellar objects (YSOs) with M > 8 M ⊙. With a 10-fold increase in resolution, we detect 371 sources at 3 mm and 218 sources in the smaller field of view at 1 mm. The sources seen at low resolution are observed to fragment into an average of two objects. About one-third of the observed sources fragment. Most of the sources we report are marginally resolved and are at least partially optically thick. We determine that the observed sources are most consistent with Stage 0/I YSOs, i.e., rotationally supported disks with an active protostar and an envelope, that are warmer than those observed in the solar neighborhood. We report source-counting-based inferred stellar mass and the star formation rate of the cloud: 2800 M ⊙ and 0.0038 M ⊙ yr−1 for Sgr B2 N and 6900 M ⊙ and 0.0093 M ⊙ yr−1 for Sgr B2 M, respectively.

Transcutaneous Imaging of Rabbit Kidney Using 3-D Acoustic Wave Sparsely Activated Localization Microscopy with a Row-Column-Addressed Array.

Super-resolution ultrasound (SRUS) imaging through localizing and tracking microbubbles, also known as ultrasound localization microscopy (ULM), can produce sub-diffraction resolution images of micro-vessels. We have recently demonstrated 3-D selective SRUS with a matrix array and phase change contrast agents (PCCAs). However, this method is limited to a small field of view (FOV) and by the complex hardware required. This study proposed 3-D acoustic wave sparsely activated localization microscopy (AWSALM) using PCCAs and a 128+128 row-column-addressed (RCA) array, which offers ultrafast acquisition with over 6 times larger FOV and 4 times reduction in hardware complexity than a 1024-element matrix array. We first validated this method on an in-vitro microflow phantom and subsequently demonstrated non-invasively on a rabbit kidney in-vivo. Our results show that 3-D AWSALM images of the phantom covering a 25×25×40 mm 3 volume can be generated under 5 seconds with an 8 times resolution improvement over the system point spread function. The full volume of the rabbit kidney can be covered to generate 3-D microvascular structure, flow speed and direction super-resolution maps under 15 seconds, combining the large FOV of RCA with the high resolution of SRUS. Additionally, 3-D AWSALM is selective and can visualize the microvasculature within the activation volume and downstream vessels in isolation. Sub-sets of the kidney microvasculature can be imaged through selective activation of PCCAs. Our study demonstrates large FOV 3-D AWSALM using an RCA probe. 3-D AWSALM offers an unique in-vivo imaging tool for fast, selective and large FOV vascular flow mapping.