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W49A is a prominent giant molecular cloud (GMC) that exhibits strong star formation activities, yet its structural and kinematic properties remain uncertain. Our study aims to investigate the large-scale structure and kinematics of W49A, and elucidate the role of filaments and hub-filament systems (HFSs) in its star formation activity. We utilized continuum data from Herschel and the James Clerk Maxwell Telescope (JCMT) as well as the molecular lines 12CO (3-2), 13CO (3-2), and C18O (3-2) to identify filaments and HFS structures within W49A. Further analysis focused on the physical properties, kinematics, and mass transport within these structures. Additionally, recombination line emission from the H I/OH/Recombination (THOR) line survey was employed to trace the central H II region and ionized gas. Our findings reveal that W49A comprises one blue-shifted (B-S) HFS and one red-shifted (R-S) HFS, each with multiple filaments and dense hubs. Notably, significant velocity gradients were detected along these filaments, indicative of material transport toward the hubs. High mass accretion rates along the filaments facilitate the formation of massive stars in the HFSs. Furthermore, the presence of V-shaped structures around clumps in position-velocity diagrams suggests ongoing gravitational collapse and local star formation within the filaments. Our results indicate that W49A consists of one R-S HFS and one B-S HFS, and that the material transport from filaments to the hub promotes the formation of massive stars in the hub. These findings underscore the significance of HFSs in shaping the star formation history of W49A., Comment: 19 pages, 22 figures. Accepted to A&A

In cardiac Magnetic Resonance Imaging (MRI) analysis, simultaneous myocardial segmentation and T2 quantification are crucial for assessing myocardial pathologies. Existing methods often address these tasks separately, limiting their synergistic potential. To address this, we propose SQNet, a dual-task network integrating Transformer and Convolutional Neural Network (CNN) components. SQNet features a T2-refine fusion decoder for quantitative analysis, leveraging global features from the Transformer, and a segmentation decoder with multiple local region supervision for enhanced accuracy. A tight coupling module aligns and fuses CNN and Transformer branch features, enabling SQNet to focus on myocardium regions. Evaluation on healthy controls (HC) and acute myocardial infarction patients (AMI) demonstrates superior segmentation dice scores (89.3/89.2) compared to state-of-the-art methods (87.7/87.9). T2 quantification yields strong linear correlations (Pearson coefficients: 0.84/0.93) with label values for HC/AMI, indicating accurate mapping. Radiologist evaluations confirm SQNet's superior image quality scores (4.60/4.58 for segmentation, 4.32/4.42 for T2 quantification) over state-of-the-art methods (4.50/4.44 for segmentation, 3.59/4.37 for T2 quantification). SQNet thus offers accurate simultaneous segmentation and quantification, enhancing cardiac disease diagnosis, such as AMI., Comment: 10 pages, 8 figures, 6 tables

In this article, a notion of viscosity solutions is introduced for fully nonlinear second order path-dependent partial differential equations in the spirit of [Zhou, Ann. Appl. Probab., 33 (2023), 5564-5612]. We prove the existence, comparison principle, consistency and stability for the viscosity solutions. Application to path-dependent stochastic differential games is given., Comment: 27 pages. arXiv admin note: text overlap with arXiv:2005.05309

We report the detection of the ordered alignment between the magnetic field and kpc-scale bubbles in the nearby spiral galaxy, NGC\,628. Applying the Velocity Gradient Technique (VGT) on CO spectroscopic data from the ALMA-PHANGS, the magnetic field of NGC\,628 is measured at the scale of 191\,pc ($\sim$ 4\,$''$). The large-scale magnetic field is oriented parallel to the spiral arms and curves around the galactic bubble structures in the mid-infrared emission observed by the James Webb Space Telescope (JWST). Twenty-one bubble structures have been identified at the edges of spiral arms with scales over 300\,pc, which includes two kpc-scale structures. These bubbles are caused by supernova remnants and prolonged star formation and are similar to the outflow chimneys found in neutral hydrogen in galactic disks. At the edge of the bubbles, the shocks traced by the OIII emission present a curved magnetic field that parallels the bubble's shell. The magnetic field follows the bubble expansion and binds the gas in the shell to trigger further star formation. By analyzing the larger sample of 1694 bubbles, we found a distinct radial-size distribution of bubbles in NGC\,628 indicating the star formation history in the galaxy., Comment: 15 pages, 7 figures, Accepted by ApJ

Optimal control and the associated second-order path-dependent Hamilton-Jacobi-Bellman (PHJB) equation are studied for unbounded functional stochastic evolution systems in Hilbert spaces. The notion of viscosity solution without B-continuity is introduced in the sense of Crandall and Lions, and is shown to coincide with the classical solutions and to satisfy a stability property. The value functional is proved to be the unique continuous viscosity solution to the associated PHJB equation, without assuming any B-continuity on the coefficients. In particular, in the Markovian case, our result provides a new theory of viscosity solutions to the Hamilton-Jacobi-Bellman equation for optimal control of stochastic evolutionary equations -- driven by a linear unbounded operator -- in a Hilbert space, and removes the B-continuity assumption on the coefficients, which was initially introduced for first-order equations by Crandall and Lions (see J. Func. Anal. 90 (1990), 237-283; 97 (1991), 417-465), and was subsequently used by Swiech (Comm. Partial Differential Equations 19 (1994), 1999-2036) and Fabbri, Gozzi, and Swiech (Probability Theory and Stochastic Modelling 82, 2017, Springer, Berlin)., Comment: 113 pages. arXiv admin note: text overlap with arXiv:2009.05367

Dynamic magnetic resonance imaging (MRI) plays an indispensable role in cardiac diagnosis. To enable fast imaging, the k-space data can be undersampled but the image reconstruction poses a great challenge of high-dimensional processing. This challenge leads to necessitate extensive training data in many deep learning reconstruction methods. This work proposes a novel and efficient approach, leveraging a dimension-reduced separable learning scheme that excels even with highly limited training data. We further integrate it with spatiotemporal priors to develop a Deep Separable Spatiotemporal Learning network (DeepSSL), which unrolls an iteration process of a reconstruction model with both temporal low-rankness and spatial sparsity. Intermediate outputs are visualized to provide insights into the network's behavior and enhance its interpretability. Extensive results on cardiac cine datasets show that the proposed DeepSSL is superior to the state-of-the-art methods visually and quantitatively, while reducing the demand for training cases by up to 75%. And its preliminary adaptability to cardiac patients has been verified through experienced radiologists' and cardiologists' blind reader study. Additionally, DeepSSL also benefits for achieving the downstream task of cardiac segmentation with higher accuracy and shows robustness in prospective real-time cardiac MRI., Comment: 10 pages, 11 figures, 3 tables

We present an unbiased $\lambda$ 3 mm spectral line survey (between 84.5 and 115.8 GHz), conducted by the Purple Mountain Observatory 13.7 meter radio telescope, together with updated modeling results, towards the carbon-rich Asymptotic Giant Branch star, IRC+10216 (CW Leo). A total of 75 spectral lines (96 transitions) are detected, and identified to arise from 19 molecules: C$_2$H, $l$-C$_3$H, C$_4$H, CN, C$_3$N, HC$_3$N, HC$_5$N, HCN, HNC, CH$_3$CN, MgNC, CO, $c$-C$_3$H$_2$, SiC$_2$, SiO, SiS, CS, C$_2$S, C$_3$S, and their isotopologues. Among them, one molecular emission line (H$^{13}$CCCN $J=13-12$) is discovered in IRC+10216 for the first time. The excitation temperature, column density, and fractional abundance of the detected species are deduced by assuming they are in local thermodynamic equilibrium. In addition, the isotopic ratios of [$^{12}$C]/[$^{13}$C], [$^{32}$S]/[$^{34}$S], [$^{28}$Si]/[$^{29}$Si], and [$^{12}$C$^{34}$S]/[$^{13}$C$^{32}$S] are obtained and found to be consistent with previous studies. Finally, we summarize all of the 106 species detected in IRC+10216 to date with their observed and modeled column densities for the convenience of future studies., Comment: 71 pages, 39 figures, 10 tables. Accepted for publication in ApJS

High-latitude ($|b|>30^{\circ}$) molecular clouds have virial parameters that exceed 1, but whether these clouds can form stars has not been studied systematically. Using JCMT SCUBA-2 archival data, we surveyed 70 fields that target high-latitude Planck galactic cold clumps (HLPCs) to find dense cores with density of $10^{5}$-$10^{6}$ cm$^{-3}$ and size of $<0.1$ pc. The sample benefits from both the representativeness of the parent sample and covering densest clumps at the high column density end ($>1\times10^{21}$ cm$^{-2}$). At an average noise rms of 15 mJy/beam, we detected Galactic dense cores in only one field, G6.04+36.77 (L183), while also identifying 12 extragalactic objects and two young stellar objects. Compared to the low-latitude clumps, dense cores are scarce in HLPCs. With synthetic observations, the densities of cores are constrained to be $n_c\lesssim10^5$ cm$^{-3}$, should they exist in HLPCs. Low-latitude clumps, Taurus clumps, and HLPCs form a sequence where a higher virial parameter corresponds to a lower dense core detection rate. If HLPCs were affected by the Local Bubble, the scarcity should favor turbulence-inhibited rather than supernova-driven star formation. Studies of the formation mechanism of the L183 molecular cloud are warranted., Comment: 9 pages for the main text. 4 figures, 1 table. Published in Astrophysical Journal Letter

We report 850 $\mu$m continuum polarization observations toward the filamentary high-mass star-forming region NGC 2264, taken as part of the B-fields In STar forming Regions Observations (BISTRO) large program on the James Clerk Maxwell Telescope (JCMT). These data reveal a well-structured non-uniform magnetic field in the NGC 2264C and 2264D regions with a prevailing orientation around 30 deg from north to east. Field strengths estimates and a virial analysis for the major clumps indicate that NGC 2264C is globally dominated by gravity while in 2264D magnetic, gravitational, and kinetic energies are roughly balanced. We present an analysis scheme that utilizes the locally resolved magnetic field structures, together with the locally measured gravitational vector field and the extracted filamentary network. From this, we infer statistical trends showing that this network consists of two main groups of filaments oriented approximately perpendicular to one another. Additionally, gravity shows one dominating converging direction that is roughly perpendicular to one of the filament orientations, which is suggestive of mass accretion along this direction. Beyond these statistical trends, we identify two types of filaments. The type-I filament is perpendicular to the magnetic field with local gravity transitioning from parallel to perpendicular to the magnetic field from the outside to the filament ridge. The type-II filament is parallel to the magnetic field and local gravity. We interpret these two types of filaments as originating from the competition between radial collapsing, driven by filament self-gravity, and the longitudinal collapsing, driven by the region's global gravity., Comment: Accepted for publication in the Astrophysical Journal. 43 pages, 32 figures, and 4 tables (including Appendix)

In this paper we investigate a path dependent optimal control problem on the process space with both drift and volatility controls, with possibly degenerate volatility. The dynamic value function is characterized by a fully nonlinear second order path dependent HJB equation on the process space, which is by nature infinite dimensional. In particular, our model covers mean field control problems with common noise as a special case. We shall introduce a new notion of viscosity solutions and establish both existence and comparison principle, under merely Lipschitz continuity assumptions. The main feature of our notion is that, besides the standard smooth part, the test function consists of an extra singular component which allows us to handle the second order derivatives of the smooth test functions without invoking the Ishii's lemma. We shall use the doubling variable arguments, combined with the Ekeland-Borwein-Preiss Variational Principle in order to overcome the noncompactness of the state space. A smooth gauge-type function on the path space is crucial for our estimates., Comment: 54 pages

Single-pointing observations of NH$_3$ (1,1) and (2,2) were conducted towards 672 Planck Early Release Cold Cores (ECCs) using the Nanshan 26-m radio telescope. Out of these sources, a detection rate of 37% (249 cores) was achieved, with NH$_3$(1,1) hyperfine structure detected in 187 and NH$_3$(2,2) emission lines detected in 76 cores. The detection rate of NH3 is positively correlated with the continuum emission fluxes at a frequency of 857 GHz. Among the observed 672 cores, ~22% have associated stellar and IR objects within the beam size (~2$\arcmin$). This suggests that most of the cores in our sample may be starless. The kinetic temperatures of the cores range from 8.9 to 20.7 K, with an average of 12.3 K, indicating a coupling between gas and dust temperatures. The ammonia column densities range from 0.36 to 6.07$\times10^{15}$ cm$^{-2}$, with a median value of 2.04$\times10^{15}$ cm$^{-2}$. The fractional abundances of ammonia range from 0.3 to 9.7$\times10^{-7}$, with an average of 2.7 $\times10^{-7}$, which is one order of magnitude larger than that of Massive Star-Forming (MSF) regions and Infrared Dark Clouds (IRDCs). The correlation between thermal and non-thermal velocity dispersion of the NH$_3$(1,1) inversion transition indicates the dominance of supersonic non-thermal motions in the dense gas traced by NH$_3$, and the relationship between these two parameters in Planck cold cores is weaker, with lower values observed for both parameters relative to other samples under our examination. The cumulative distribution shapes of line widths in the Planck cold cores closely resemble those of the dense cores found in regions of Cepheus, and Orion L1630 and L1641, with higher values compared to Ophiuchus. A comparison of NH3 line-center velocities with those of $^{13}$CO and C$^{18}$O shows small differences (0.13 and 0.12 km s$^{-1}$ ), suggesting quiescence on small scales., Comment: 29 pages, 13 figures

We study the magnetic field structures in six giant filaments associated with the spiral arms of the Milky Way by applying the Velocity Gradient technique (VGT) to the 13CO spectroscopic data from GRS, Fugin, and SEDIGSM surveys. Compared to dust polarized emission, the VGT allows us to separate the foreground and background using the velocity information, from which the orientation of the magnetic field can be reliably determined. We find that in most cases, the magnetic fields stay aligned with the filament bodies, which are parallel to the disk midplane. Among these, G29, G47, and G51 exhibit smooth magnetic fields, and G24, G339, and G349 exhibit discontinuities. The fact that most filaments have magnetic fields that stay aligned with the Galactic disk midplane suggests that Galactic shear can be responsible for shaping the filaments. The fact that the magnetic field can stay regular at the resolution of our analysis (<= 10 pc) where the turbulence crossing time is short compared to the shear time suggests that turbulent motion can not effectively disrupt the regular orientation of the magnetic field. The discontinuities found in some filaments can be caused by processes including filament reassembly, gravitational collapse, and stellar feedback., Comment: 18 pages, 11 figures, accepted by ApJ

Magnetic resonance imaging (MRI) is an important non-invasive imaging method in clinical diagnosis. Beyond the common image structures, parametric imaging can provide the intrinsic tissue property thus could be used in quantitative evaluation. The emerging deep learning approach provides fast and accurate parameter estimation but still encounters the lack of network interpretation and enough training data. Even with a large amount of training data, the mismatch between the training and target data may introduce errors. Here, we propose one way that solely relies on the target scanned data and does not need a pre-defined training database. We provide a proof-of-concept that embeds the physical rule of MRI, the Bloch equation, into the loss of physics-informed neural network (PINN). PINN enables learning the Bloch equation, estimating the T2 parameter, and generating a series of physically synthetic data. Experimental results are conducted on phantom and cardiac imaging to demonstrate its potential in quantitative MRI.

Magnetic resonance imaging (MRI) is a widely used radiological modality renowned for its radiation-free, comprehensive insights into the human body, facilitating medical diagnoses. However, the drawback of prolonged scan times hinders its accessibility. The k-space undersampling offers a solution, yet the resultant artifacts necessitate meticulous removal during image reconstruction. Although Deep Learning (DL) has proven effective for fast MRI image reconstruction, its broader applicability across various imaging scenarios has been constrained. Challenges include the high cost and privacy restrictions associated with acquiring large-scale, diverse training data, coupled with the inherent difficulty of addressing mismatches between training and target data in existing DL methodologies. Here, we present a novel Physics-Informed Synthetic data learning framework for Fast MRI, called PISF. PISF marks a breakthrough by enabling generalized DL for multi-scenario MRI reconstruction through a single trained model. Our approach separates the reconstruction of a 2D image into many 1D basic problems, commencing with 1D data synthesis to facilitate generalization. We demonstrate that training DL models on synthetic data, coupled with enhanced learning techniques, yields in vivo MRI reconstructions comparable to or surpassing those of models trained on matched realistic datasets, reducing the reliance on real-world MRI data by up to 96%. Additionally, PISF exhibits remarkable generalizability across multiple vendors and imaging centers. Its adaptability to diverse patient populations has been validated through evaluations by ten experienced medical professionals. PISF presents a feasible and cost-effective way to significantly boost the widespread adoption of DL in various fast MRI applications., Comment: 38 pages, 19 figures, 5 tables

We studied the hub filament system G323.46-0.08 based on archival molecular line data from the SEDIGISM 13CO survey and infrared data from the GLIMPSE, MIPS, and Hi-GAL surveys. G323.46-0.08 consists of three filaments, F-north, F-west, and F-south, that converge toward the central high_mass clump AGAL 323.459-0.079. F-west and Part 1 of the F-south show clear large-scale velocity gradients 0.28 and 0.44 km s-1 pc-1, respectively. They seem to be channeling materials into AGAL 323.459-0.079. The minimum accretion rate was estimated to be 1216 M Myr-1. A characteristic V-shape appears around AGAL 323.459-0.079 in the PV diagram, which traces the accelerated gas motions under gravitational collapse. This has also been supported by model fitting results. All three filaments are supercritical and they have fragmented into many dense clumps. The seesaw patterns near most dense clumps in the PV diagram suggests that mass accretion also occurs along the filament toward the clumps. Our results show that filamentary accretion flows appear to be an important mechanism for supplying the materials necessary to form the central high-mass clump AGAL 323.459-0.079 and to propel the star forming activity taking place therein.

Magnetic resonance spectroscopy (MRS) is an important clinical imaging method for diagnosis of diseases. MRS spectrum is used to observe the signal intensity of metabolites or further infer their concentrations. Although the magnetic resonance vendors commonly provide basic functions of spectra plots and metabolite quantification, the widespread clinical research of MRS is still limited due to the lack of easy-to-use processing software or platform. To address this issue, we have developed CloudBrain-MRS, a cloud-based online platform that provides powerful hardware and advanced algorithms. The platform can be accessed simply through a web browser, without the need of any program installation on the user side. CloudBrain-MRS also integrates the classic LCModel and advanced artificial intelligence algorithms and supports batch preprocessing, quantification, and analysis of MRS data from different vendors. Additionally, the platform offers useful functions: 1) Automatically statistical analysis to find biomarkers for diseases; 2) Consistency verification between the classic and artificial intelligence quantification algorithms; 3) Colorful three-dimensional visualization for easy observation of individual metabolite spectrum. Last, both healthy and mild cognitive impairment patient data are used to demonstrate the functions of the platform. To the best of our knowledge, this is the first cloud computing platform for in vivo MRS with artificial intelligence processing. We have shared our cloud platform at MRSHub, providing free access and service for two years. Please visit https://mrshub.org/software_all/#CloudBrain-MRS or https://csrc.xmu.edu.cn/CloudBrain.html., Comment: 11 pages, 12 figures

We present observations of polarized dust emission at 850 $\mu$m from the L43 molecular cloud which sits in the Ophiuchus cloud complex. The data were taken using SCUBA-2/POL-2 on the James Clerk Maxwell Telescope as a part of the BISTRO large program. L43 is a dense ($N_{\rm H_2}\sim 10^{22}$-10$^{23}$ cm$^{-2}$) complex molecular cloud with a submillimetre-bright starless core and two protostellar sources. There appears to be an evolutionary gradient along the isolated filament that L43 is embedded within, with the most evolved source closest to the Sco OB2 association. One of the protostars drives a CO outflow that has created a cavity to the southeast. We see a magnetic field that appears to be aligned with the cavity walls of the outflow, suggesting interaction with the outflow. We also find a magnetic field strength of up to $\sim$160$\pm$30 $\mu$G in the main starless core and up to $\sim$90$\pm$40 $\mu$G in the more diffuse, extended region. These field strengths give magnetically super- and sub-critical values respectively and both are found to be roughly trans-Alfv\'enic. We also present a new method of data reduction for these denser but fainter objects like starless cores., Comment: Accepted for publication in ApJ. 23 pages, 9 figures (7 main text, 2 appendix)

We present BISTRO Survey 850 {\mu}m dust emission polarisation observations of the L1495A-B10 region of the Taurus molecular cloud, taken at the JCMT. We observe a roughly triangular network of dense filaments. We detect 9 of the dense starless cores embedded within these filaments in polarisation, finding that the plane-of-sky orientation of the core-scale magnetic field lies roughly perpendicular to the filaments in almost all cases. We also find that the large-scale magnetic field orientation measured by Planck is not correlated with any of the core or filament structures, except in the case of the lowest-density core. We propose a scenario for early prestellar evolution that is both an extension to, and consistent with, previous models, introducing an additional evolutionary transitional stage between field-dominated and matter-dominated evolution, observed here for the first time. In this scenario, the cloud collapses first to a sheet-like structure. Uniquely, we appear to be seeing this sheet almost face-on. The sheet fragments into filaments, which in turn form cores. However, the material must reach a certain critical density before the evolution changes from being field-dominated to being matter-dominated. We measure the sheet surface density and the magnetic field strength at that transition for the first time and show consistency with an analytical prediction that had previously gone untested for over 50 years (Mestel 1965)., Comment: 14 pages, 5 figures. ApJ accepted

We study the HII regions associated with the NGC 6334 molecular cloud observed in the sub-millimeter and taken as part of the B-fields In STar-forming Region Observations (BISTRO) Survey. In particular, we investigate the polarization patterns and magnetic field morphologies associated with these HII regions. Through polarization pattern and pressure calculation analyses, several of these bubbles indicate that the gas and magnetic field lines have been pushed away from the bubble, toward an almost tangential (to the bubble) magnetic field morphology. In the densest part of NGC 6334, where the magnetic field morphology is similar to an hourglass, the polarization observations do not exhibit observable impact from HII regions. We detect two nested radial polarization patterns in a bubble to the south of NGC 6334 that correspond to the previously observed bipolar structure in this bubble. Finally, using the results of this study, we present steps (incorporating computer vision; circular Hough Transform) that can be used in future studies to identify bubbles that have physically impacted magnetic field lines., Comment: Accepted for publication in Astrophysical Journal (ApJ)

Efficient collaboration between engineers and radiologists is important for image reconstruction algorithm development and image quality evaluation in magnetic resonance imaging (MRI). Here, we develop CloudBrain-ReconAI, an online cloud computing platform, for algorithm deployment, fast and blind reader study. This platform supports online image reconstruction using state-of-the-art artificial intelligence and compressed sensing algorithms with applications to fast imaging and high-resolution diffusion imaging. Through visiting the website, radiologists can easily score and mark the images. Then, automatic statistical analysis will be provided. CloudBrain-ReconAI is now open accessed at https://csrc.xmu.edu.cn/CloudBrain.html and will be continually improved to serve the MRI research community., Comment: 8 pages, 11 figures

We present 850 $\mu$m dust polarization observations of the massive DR21 filament from the B-fields In STar-forming Region Observations (BISTRO) survey, using the POL-2 polarimeter and the SCUBA-2 camera on the James Clerk Maxwell Telescope. We detect ordered magnetic fields perpendicular to the parsec-scale ridge of the DR21 main filament. In the sub-filaments, the magnetic fields are mainly parallel to the filamentary structures and smoothly connect to the magnetic fields of the main filament. We compare the POL-2 and Planck dust polarization observations to study the magnetic field structures of the DR21 filament on 0.1--10 pc scales. The magnetic fields revealed in the Planck data are well aligned with those of the POL-2 data, indicating a smooth variation of magnetic fields from large to small scales. The plane-of-sky magnetic field strengths derived from angular dispersion functions of dust polarization are 0.6--1.0 mG in the DR21 filament and $\sim$ 0.1 mG in the surrounding ambient gas. The mass-to-flux ratios are found to be magnetically supercritical in the filament and slightly subcritical to nearly critical in the ambient gas. The alignment between column density structures and magnetic fields changes from random alignment in the low-density ambient gas probed by Planck to mostly perpendicular in the high-density main filament probed by JCMT. The magnetic field structures of the DR21 filament are in agreement with MHD simulations of a strongly magnetized medium, suggesting that magnetic fields play an important role in shaping the DR21 main filament and sub-filaments., Comment: 26 pages, 13 figures, ApJ accepted

Magnetic resonance imaging (MRI) is an essential diagnostic tool that suffers from prolonged scan time. To alleviate this limitation, advanced fast MRI technology attracts extensive research interests. Recent deep learning has shown its great potential in improving image quality and reconstruction speed. Faithful coil sensitivity estimation is vital for MRI reconstruction. However, most deep learning methods still rely on pre-estimated sensitivity maps and ignore their inaccuracy, resulting in the significant quality degradation of reconstructed images. In this work, we propose a Joint Deep Sensitivity estimation and Image reconstruction network, called JDSI. During the image artifacts removal, it gradually provides more faithful sensitivity maps with high-frequency information, leading to improved image reconstructions. To understand the behavior of the network, the mutual promotion of sensitivity estimation and image reconstruction is revealed through the visualization of network intermediate results. Results on in vivo datasets and radiologist reader study demonstrate that, for both calibration-based and calibrationless reconstruction, the proposed JDSI achieves the state-of-the-art performance visually and quantitatively, especially when the acceleration factor is high. Additionally, JDSI owns nice robustness to patients and autocalibration signals., Comment: 12 pages, 13 figures, 7 tables

Diffusion magnetic resonance imaging (MRI) is the only imaging modality for non-invasive movement detection of in vivo water molecules, with significant clinical and research applications. Diffusion MRI (DWI) acquired by multi-shot techniques can achieve higher resolution, better signal-to-noise ratio, and lower geometric distortion than single-shot, but suffers from inter-shot motion-induced artifacts. These artifacts cannot be removed prospectively, leading to the absence of artifact-free training labels. Thus, the potential of deep learning in multi-shot DWI reconstruction remains largely untapped. To break the training data bottleneck, here, we propose a Physics-Informed Deep DWI reconstruction method (PIDD) to synthesize high-quality paired training data by leveraging the physical diffusion model (magnitude synthesis) and inter-shot motion-induced phase model (motion phase synthesis). The network is trained only once with 100,000 synthetic samples, achieving encouraging results on multiple realistic in vivo data reconstructions. Advantages over conventional methods include: (a) Better motion artifact suppression and reconstruction stability; (b) Outstanding generalization to multi-scenario reconstructions, including multi-resolution, multi-b-value, multi-undersampling, multi-vendor, and multi-center; (c) Excellent clinical adaptability to patients with verifications by seven experienced doctors (p<0.001). In conclusion, PIDD presents a novel deep learning framework by exploiting the power of MRI physics, providing a cost-effective and explainable way to break the data bottleneck in deep learning medical imaging., Comment: 23 pages, 16 figures

We present and analyze observations of polarized dust emission at 850 $\mu$m towards the central 1 pc $\times$ 1 pc hub-filament structure of Monoceros R2 (Mon R2). The data are obtained with SCUBA-2/POL-2 on the James Clerk Maxwell Telescope (JCMT) as part of the BISTRO (B-fields in Star-forming Region Observations) survey. The orientations of the magnetic field follow the spiral structure of Mon R2, which are well-described by an axisymmetric magnetic field model. We estimate the turbulent component of the magnetic field using the angle difference between our observations and the best-fit model of the underlying large-scale mean magnetic field. This estimate is used to calculate the magnetic field strength using the Davis-Chandrasekhar-Fermi method, for which we also obtain the distribution of volume density and velocity dispersion using a column density map derived from $Herschel$ data and the C$^{18}$O ($J$ = 3-2) data taken with HARP on the JCMT, respectively. We make maps of magnetic field strengths and mass-to-flux ratios, finding that magnetic field strengths vary from 0.02 to 3.64 mG with a mean value of 1.0 $\pm$ 0.06 mG, and the mean critical mass-to-flux ratio is 0.47 $\pm$ 0.02. Additionally, the mean Alfv\'en Mach number is 0.35 $\pm$ 0.01. This suggests that in Mon R2, magnetic fields provide resistance against large-scale gravitational collapse, and magnetic pressure exceeds turbulent pressure. We also investigate the properties of each filament in Mon R2. Most of the filaments are aligned along the magnetic field direction and are magnetically sub-critical., Comment: This paper is accepted to the ApJ

Magnetic fields play an important role in the evolution of molecular clouds and star formation. Using the Velocity Gradient Technique (VGT) model, we measured the magnetic field in Orion A using the 12CO, 13CO, and C18O (1-0) emission lines at a scale of 0.07 pc. The measured B-field shows an east-west orientation that is perpendicular to the integral shaped filament of Orion A at large scale. The VGT magnetic fields obtained from 13CO and C18O are in agreement with the B-field that is measured from the Planck 353 GHz dust polarization at a scale of 0.55 pc. Removal of density effects by using a Velocity Decomposition Algorithm can significantly improve the accuracy of the VGT in tracing magnetic fields with the 12CO (1-0) line. The magnetic field strength of seven sub-clouds, OMC-1, OMC-2, OMC-3, OMC-4, OMC-5, L 1641-N, and NGC 1999 has also been estimated with the Davis-Chandrasekhar-Fermi (DCF) and MM2 technique, and these are found to be in agreement with previous results obtained from dust polarization at far-infrared and sub-millimeter wavelengths. At smaller scales, the VGT proves a good method to measure magnetic fields., Comment: 15 pages, 6 figures, accepted to ApJ

We studied the cloud-cloud collision candidate G323.18+0.15 based on signatures of induced filaments, clumps, and star formation. We used archival molecular spectrum line data from the SEDIGISM $^{13}$CO($J$\,=\,2--1) survey, from the Mopra southern Galactic plane CO survey, and infrared to radio data from the GLIMPSE, MIPS, Hi-GAL, and SGPS surveys. Our new result shows that the G323.18+0.15 complex is 3.55kpc away from us and consists of three cloud components, G323.18a, G323.18b, and G323.18c. G323.18b shows a perfect U-shape structure, which can be fully complemented by G323.18a, suggesting a collision between G323.18a and the combined G323.18bc filamentary structure. One dense compressed layer (filament) is formed at the bottom of G323.18b, where we detect a greatly increased velocity dispersion. The bridge with an intermediate velocity in a position-velocity diagram appears between G323.18a and G323.18b, which corresponds to the compressed layer. G323.18a plus G323.18b as a whole are probably not gravitationally bound. This indicates that high-mass star formation in the compressed layer may have been caused by an accidental event. The column density in the compressed layer of about $1.36 \times 10^{22}$cm$^{-2}$ and most of the dense clumps and high-mass stars are located there. The average surface density of classI and classII young stellar objects (YSOs) inside the G323.18+0.15 complex is much higher than the density in the surroundings. The timescale of the collision between G323.18a and G323.18b is $1.59$Myr. This is longer than the typical lifetime of classI YSOs and is comparable to the lifetime of classII YSOs.

We present 850 $\mu$m polarimetric observations toward the Serpens Main molecular cloud obtained using the POL-2 polarimeter on the James Clerk Maxwell Telescope (JCMT) as part of the B-fields In STar-forming Region Observations (BISTRO) survey. These observations probe the magnetic field morphology of the Serpens Main molecular cloud on about 6000 au scales, which consists of cores and six filaments with different physical properties such as density and star formation activity. Using the histogram of relative orientation (HRO) technique, we find that magnetic fields are parallel to filaments in less dense filamentary structures where $N_{H_2} < 0.93\times 10^{22}$ cm$^{-2}$ (magnetic fields perpendicular to density gradients), while being perpendicular to filaments (magnetic fields parallel to density gradients) in dense filamentary structures with star formation activity. Moreover, applying the HRO technique to denser core regions, we find that magnetic field orientations change to become perpendicular to density gradients again at $N_{H_2} \approx 4.6 \times 10^{22}$ cm$^{-2}$. This can be interpreted as a signature of core formation. At $N_{H_2} \approx 16 \times 10^{22}$ cm$^{-2}$ magnetic fields change back to being parallel to density gradients once again, which can be understood to be due to magnetic fields being dragged in by infalling material. In addition, we estimate the magnetic field strengths of the filaments ($B_{POS} = 60-300~\mu$G)) using the Davis-Chandrasekhar-Fermi method and discuss whether the filaments are gravitationally unstable based on magnetic field and turbulence energy densities., Comment: 18 pages, accepted for publication in ApJ

The presence of complex organic molecules (COMs) in the interstellar medium (ISM) is of great interest since it may link to the origin and prevalence of life in the universe. Aiming to investigate the occurrence of COMs and their possible origins, we conducted a chemical census toward a sample of protostellar cores as part of the ALMA Survey of Orion Planck Galactic Cold Clumps (ALMASOP) project. We report the detection of 11 hot corino sources, which exhibit compact emissions from warm and abundant COMs, among 56 Class 0/I protostellar cores. All the hot corino sources discovered are likely Class 0 and their sizes of the warm region ($>$ 100 K) are comparable to 100 au. The luminosity of the hot corino sources exhibits positive correlations with the total number of methanol and the extent of its emissions. Such correlations are consistent with the thermal desorption picture for the presence of hot corino and suggest that the lower luminosity (Class 0) sources likely have a smaller region with COMs emissions. With the same sample selection method and detection criteria being applied, the detection rates of the warm methanol in the Orion cloud (15/37) and the Perseus cloud (28/50) are statistically similar when the cloud distances and the limited sample size are considered. Observing the same set of COM transitions will bring a more informative comparison between the cloud properties., Comment: 34 pages. 14 figures. 1 figure set. 1 machine-readable table. Accepted for publication in ApJ

This paper introduces a notion of viscosity solutions for second order elliptic Hamilton-Jacobi-Bellman (HJB) equations with infinite delay associated with infinite-horizon optimal control problems for stochastic differential equations with infinite delay. We identify the value functional of optimal control problems as unique viscosity solution to associated second order elliptic HJB equation with infinite delay. We also show that our notion of viscosity solutions is consistent with the corresponding notion of classical solutions, and satisfies a stability property., Comment: 39 pages. arXiv admin note: text overlap with arXiv:2009.05367, arXiv:2005.05309

We present the results of simultaneous 450 $\mu$m and 850 $\mu$m polarization observations toward the massive star forming region NGC 2071IR, a target of the BISTRO (B-fields in Star-Forming Region Observations) Survey, using the POL-2 polarimeter and SCUBA-2 camera mounted on the James Clerk Maxwell Telescope. We find a pinched magnetic field morphology in the central dense core region, which could be due to a rotating toroidal disk-like structure and a bipolar outflow originating from the central young stellar object, IRS 3. Using the modified Davis-Chandrasekhar-Fermi method, we obtain a plane-of-sky magnetic field strength of 563$\pm$421 $\mu$G in the central $\sim$0.12 pc region from 850 $\mu$m polarization data. The corresponding magnetic energy density of 2.04$\times$10$^{-8}$ erg cm$^{-3}$ is comparable to the turbulent and gravitational energy densities in the region. We find that the magnetic field direction is very well aligned with the whole of the IRS 3 bipolar outflow structure. We find that the median value of polarization fractions, 3.0 \%, at 450 $\mu$m in the central 3 arcminute region, which is larger than the median value of 1.2 \% at 850 $\mu$m. The trend could be due to the better alignment of warmer dust in the strong radiation environment. We also find that polarization fractions decrease with intensity at both wavelengths, with slopes, determined by fitting a Rician noise model, of $0.59 \pm 0.03$ at 450 $\mu$m and $0.36 \pm 0.04$ at 850 $\mu$m, respectively. We think that the shallow slope at 850 $\mu$m is due to grain alignment at the center being assisted by strong radiation from the central young stellar objects., Comment: 17 pages, 11 figures, 4 tables