arXiv subjects

Peng Jiang

Publications and source records attributed to Peng Jiang.

At least 145 records · Page 8Linked to original sources

arXiv2025

The HI Mass Function of the Local Universe: Combining Measurements from HIPASS, ALFALFA and FASHI

We present the first HI mass function (HIMF) measurement for the recent FAST All Sky HI (FASHI) survey and the most complete measurements of HIMF in the local universe thus far. We obtained these results by combining the HI catalogues from HI Parkes All Sky Survey (HIPASS), Arecibo Legacy Fast ALFA (ALFALFA) and FASHI surveys at redshift 0 < z < 0.05, covering 76% of the entire sky. We adopted the same methods to estimate the distances, calculate the sample completeness, and determine the HIMF for all three surveys. The best-fit Schechter function for the total HIMF shows a low-mass slope parameter of alpha = -1.30 and a knee mass log(Ms) = 9.86, along with a normalisation of phi_s = 0.00658. This gives us the cosmic HI abundance: omega_HI= 0.000454. We find that a double Schechter function with the same slope alpha better describes our HIMF, where the two different knee masses are log(Ms1) = 9.96 and log(Ms2) = 9.65. We verify that the measured HIMF is marginally affected by the choice of distance estimates. The effect of cosmic variance is significantly suppressed by combining the three surveys and this provides a unique opportunity to obtain an unbiased estimate of the HIMF in the Local Universe.

astro-ph.GA↗

arXiv2025

Effects of appendages on the turbulence and flow noise of a submarine model using high-order scheme

This study employs high-fidelity numerical simulations to investigate the influence of appendages on the turbulent flow dynamics and far-field acoustic radiation of the SUBOFF submarine model at a Reynolds number of Re = 1.2*10^7. Utilizing a third-order numerical scheme combined with wall-modeled large eddy simulation (WMLES) and the Ffowcs Williams-Hawkings (FW-H) acoustic analogy, the hydrodynamic and acoustic behaviors of an appended SUBOFF configuration are compared to those of a bare hull. A computational grid of 103 million cells resolves the intricate flow interactions, while 648 hydrophones positioned 500 diameters from the model capture far-field acoustic signatures. Key results reveal that appendages significantly amplify hydrodynamic and acoustic disturbances. Flow separations and vortex shedding at appendage junctions elevate pressure-induced drag contributions, contrasting the viscous-dominated drag of the bare hull. The sail-hull interaction intensifies local surface pressure fluctuations, increasing power spectral density (PSD) amplitudes by up to an order of magnitude. In the far field, the appended SUBOFF generates sound pressure levels approximately 20 dB higher than the bare hull, with distinct dipole directivity patterns and peak noise levels (85.10 dB) observed on the central plane. Appendages also disrupt wake symmetry, introducing complex vortical structures such as horseshoe and necklace vortices. These findings demonstrate the critical influence of appendages on hydrodynamic and acoustic behavior, filling a gap in turbulence noise research for complex underwater geometries and providing a vital foundation for the noise reduction optimization of advanced underwater vehicles.

physics.flu-dyn↗

arXiv2025

Lossy Compression of Scientific Data: Applications Constrains and Requirements

Increasing data volumes from scientific simulations and instruments (supercomputers, accelerators, telescopes) often exceed network, storage, and analysis capabilities. The scientific community's response to this challenge is scientific data reduction. Reduction can take many forms, such as triggering, sampling, filtering, quantization, and dimensionality reduction. This report focuses on a specific technique: lossy compression. Lossy compression retains all data points, leveraging correlations and controlled reduced accuracy. Quality constraints, especially for quantities of interest, are crucial for preserving scientific discoveries. User requirements also include compression ratio and speed. While many papers have been published on lossy compression techniques and reference datasets are shared by the community, there is a lack of detailed specifications of application needs that can guide lossy compression researchers and developers. This report fills this gap by reporting on the requirements and constraints of nine scientific applications covering a large spectrum of domains (climate, combustion, cosmology, fusion, light sources, molecular dynamics, quantum circuit simulation, seismology, and system logs). The report also details key lossy compression technologies (SZ, ZFP, MGARD, LC, SPERR, DCTZ, TEZip, LibPressio), discussing their history, principles, error control, hardware support, features, and impact. By presenting both application needs and compression technologies, the report aims to inspire new research to fill existing gaps.

astro-ph.IM↗

arXiv2025

D&M: Enriching E-commerce Videos with Sound Effects by Key Moment Detection and SFX Matching

Videos showcasing specific products are increasingly important for E-commerce. Key moments naturally exist as the first appearance of a specific product, presentation of its distinctive features, the presence of a buying link, etc. Adding proper sound effects (SFX) to these key moments, or video decoration with SFX (VDSFX), is crucial for enhancing the user engaging experience. Previous studies about adding SFX to videos perform video to SFX matching at a holistic level, lacking the ability of adding SFX to a specific moment. Meanwhile, previous studies on video highlight detection or video moment retrieval consider only moment localization, leaving moment to SFX matching untouched. By contrast, we propose in this paper D&M, a unified method that accomplishes key moment detection and moment to SFX matching simultaneously. Moreover, for the new VDSFX task we build a large-scale dataset SFX-Moment from an E-commerce platform. For a fair comparison, we build competitive baselines by extending a number of current video moment detection methods to the new task. Extensive experiments on SFX-Moment show the superior performance of the proposed method over the baselines.

cs.CV↗

arXiv2025

Adaptive$^2$: Adaptive Domain Mining for Fine-grained Domain Adaptation Modeling

Advertising systems often face the multi-domain challenge, where data distributions vary significantly across scenarios. Existing domain adaptation methods primarily focus on building domain-adaptive neural networks but often rely on hand-crafted domain information, e.g., advertising placement, which may be sub-optimal. We think that fine-grained "domain" patterns exist that are difficult to hand-craft in online advertisement. Thus, we propose Adaptive$^2$, a novel framework that first learns domains adaptively using a domain mining module by self-supervision and then employs a shared&specific network to model shared and conflicting information. As a practice, we use VQ-VAE as the domain mining module and conduct extensive experiments on public benchmarks. Results show that traditional domain adaptation methods with hand-crafted domains perform no better than single-domain models under fair FLOPS conditions, highlighting the importance of domain definition. In contrast, Adaptive$^2$ outperforms existing approaches, emphasizing the effectiveness of our method and the significance of domain mining. We also deployed Adaptive$^2$ in the live streaming scenario of Kuaishou Advertising System, demonstrating its commercial value and potential for automatic domain identification. To the best of our knowledge, Adaptive$^2$ is the first approach to automatically learn both domain identification and adaptation in online advertising, opening new research directions for this area.

cs.LG↗

arXiv2025

FAST Discovery of A Gas-rich and Ultra-faint Dwarf Galaxy: KK153

Based on a high-sensitivity HI survey using the Five-hundred-meter Aperture Spherical radio Telescope (FAST), we identified an isolated HI cloud with a system velocity of ~127.0 km/s, which is associated with an optical galaxy KK153 in space. The HI gas of KK153 shows a typical disk-galaxy structure. Using the Baryonic Tully-Fisher relation, we obtained that the distance to KK153 is 2.0_{-0.8}^{+1.7} Mpc. Adopting such distance, we derived a stellar mass of 4.1_{-2.6}^{+10.0}*10^{5} Msun and a neutral gas fraction of 0.63, implying that KK153 is a gas-rich ultra-faint dwarf (UFD) galaxy in the Local Group or its outskirts. KK153 shows a cool (~200 K) and warm (~7400 K) two-phase neutral medium. The g-r color distribution of KK153 suggests that new stars are mostly forming in its inner disk. The dynamical mass of KK153 is 6.9_{-3.0}^{+5.5}*10^{7} Msun, which is about 60 times larger than its baryonic matter. Detection of such a low-mass and gas-rich halo poses a challenge to the theory of cosmic reionization.

astro-ph.GA↗

arXiv2025

Magnetic field properties of the SNR HB 9

We aim to study the polarization and magnetic field properties of the SNR HB 9 using new 21-cm continuum cube data from the Five-hundred-meter Aperture Spherical radio telescope (FAST). We computed the Faraday depth at 21 cm, and re-analyzed the rotation measures (RMs) of HB 9 using in addition Effelsberg 2695-MHz and Urumqi 4800-MHz polarization data. FAST total-intensity images of two subbands are decomposed into components of multiple angular scales to check spectral-index variation via temperature versus temperature plots (TT-plots). The filamentary emission has a spectral index ($S\simν^α$) of $α=-$0.52, corresponding to freshly accelerated relativistic electrons. The diffuse emission has a steeper spectrum of $α=-$0.63, corresponding to confined electrons that are no longer accelerated. The FAST detected 1385-MHz polarized emission might come from a thin layer in the outer envelope of the shells, with a Faraday depth of 4-28 rad m$^{-2}$ from the Faraday rotation synthesis result. The RMs derived from the Effelsberg 2695-MHz and Urumqi 4800-MHz polarization data show about 70 rad m$^{-2}$ in the eastern and northern shell, and 124 rad m$^{-2}$ in the inner and southern patches. The regular magnetic field is about 5$-$8 $μ$G over the remnant. The northern shell shows depolarization at 2695 MHz relative to the 4800-MHz polarization data, indicating an additional random magnetic field of 12 $μ$G on the scale of 0.6 pc. The shock wave might have entered the dense gas environment in the northern-shell region and has driven turbulence to cause depolarization at 2695 MHz.

astro-ph.GA↗

arXiv2025

SweetTok: Semantic-Aware Spatial-Temporal Tokenizer for Compact Video Discretization

This paper presents the \textbf{S}emantic-a\textbf{W}ar\textbf{E} spatial-t\textbf{E}mporal \textbf{T}okenizer (SweetTok), a novel video tokenizer to overcome the limitations in current video tokenization methods for compacted yet effective discretization. Unlike previous approaches that process flattened local visual patches via direct discretization or adaptive query tokenization, SweetTok proposes a decoupling framework, compressing visual inputs through distinct spatial and temporal queries via \textbf{D}ecoupled \textbf{Q}uery \textbf{A}uto\textbf{E}ncoder (DQAE). This design allows SweetTok to efficiently compress video token count while achieving superior fidelity by capturing essential information across spatial and temporal dimensions. Furthermore, we design a \textbf{M}otion-enhanced \textbf{L}anguage \textbf{C}odebook (MLC) tailored for spatial and temporal compression to address the differences in semantic representation between appearance and motion information. SweetTok significantly improves video reconstruction results by \textbf{42.8\%} w.r.t rFVD on UCF-101 dataset. With a better token compression strategy, it also boosts downstream video generation results by \textbf{15.1\%} w.r.t gFVD. Additionally, the compressed decoupled tokens are imbued with semantic information, enabling few-shot recognition capabilities powered by LLMs in downstream applications.

cs.CV↗

arXiv2025

Formation of the dark-matter deficient S0 galaxy NGC 4111 under the tidal interactions

We present the high-sensitivity and large-scale atomic hydrogen (HI) observations towards lenticular (S0) galaxy NGC 4111 using the Five-hundred-meter Aperture Spherical Radio Telescope (FAST). The column density map shows that NGC4111 and seven other different types of galaxies share a huge HI gas complex. The data also suggest that NGC 4111 is interacting with seven galaxies. Moreover, we identified a rotating gas disk associated with NGC 4111 from the HI complex. Still, the HI disk rotation direction has deviated from its stellar disk about 34.2$^{\circ}$, indicating that the NGC 4111 galaxy is undergoing a transition from a spiral galaxy to an S0 galaxy by the tidal interactions. The obtained dark matter-to-stellar mass ratio of NGC4111 is 3.1$\pm$0.7, which is lower than the average value of the Local Universe, implying that the interactions may strip its dark matter. Our results suggest that in a galaxy group environment, tidal interactions have a significant effect on galaxy features.

astro-ph.GA↗

arXiv2025

AURO: Reinforcement Learning for Adaptive User Retention Optimization in Recommender Systems

The field of Reinforcement Learning (RL) has garnered increasing attention for its ability of optimizing user retention in recommender systems. A primary obstacle in this optimization process is the environment non-stationarity stemming from the continual and complex evolution of user behavior patterns over time, such as variations in interaction rates and retention propensities. These changes pose significant challenges to existing RL algorithms for recommendations, leading to issues with dynamics and reward distribution shifts. This paper introduces a novel approach called \textbf{A}daptive \textbf{U}ser \textbf{R}etention \textbf{O}ptimization (AURO) to address this challenge. To navigate the recommendation policy in non-stationary environments, AURO introduces an state abstraction module in the policy network. The module is trained with a new value-based loss function, aligning its output with the estimated performance of the current policy. As the policy performance of RL is sensitive to environment drifts, the loss function enables the state abstraction to be reflective of environment changes and notify the recommendation policy to adapt accordingly. Additionally, the non-stationarity of the environment introduces the problem of implicit cold start, where the recommendation policy continuously interacts with users displaying novel behavior patterns. AURO encourages exploration guarded by performance-based rejection sampling to maintain a stable recommendation quality in the cost-sensitive online environment. Extensive empirical analysis are conducted in a user retention simulator, the MovieLens dataset, and a live short-video recommendation platform, demonstrating AURO's superior performance against all evaluated baseline algorithms.

cs.IR↗

arXiv2025

FEASTS Combined with Interferometry (IV): Mapping HI Emission to a limit of $N_{\text{HI}}=10^{17.7} \text{cm}^{-2}$ in Seven Edge-on Galaxies

We present a statistical study of the neutral atomic hydrogen (HI) gas extending into the circumgalactic medium perpendicular to the disk for 7 edge-on galaxies with inclinations above $85^{\circ}$ from the FEASTS program with a $3σ$ ($20\,\text{km}\,\text{s}^{-1}$) column density ($N_{\text{HI}}$) depth of $5\times10^{17} \text{cm}^{-2}$. We develop two photometric methods to separate the extraplanar HI from the disk component, based on existing interferometric data and parametric modeling of the disk flux distribution respectively. With both methods, the FEASTS data exhibit clear extended wings beyond the disk along the minor axis. The extraplanar HI accounts for 5% to 20% of the total HI mass and extends to $20\text{-}50$ kpc at $N_{\text{HI}}=10^{18} \text{cm}^{-2}$. We find a tight positive correlation between vertical extensions of the extraplanar HI and total HI mass $M_\text{HI}$. The iso-density shape of HI at $N_{\text{HI}}=10^{18} \text{cm}^{-2}$ has an average axis ratio of $0.56\pm0.11$. The off-disk $N_{\text{HI}}$ profiles of these edge-on galaxies well represent the lower envelop of previous Lyman-$α$ absorption measurements at low-redshift. Our results suggest that at $N_{\text{HI}}=5\times10^{17} \text{cm}^{-2}$, the HI extends considerably further than the known thin and thick disks in the vertical direction, but still remains much flattener than a spherical distribution, consistent with theoretical expectations that outflow, circulation, and accretion should have different impacts in these two directions. We show the tension of our results with Illustris and TNG predictions, highlighting the constraining power of our results for future simulations.

astro-ph.GA↗

arXiv2025

Joint Waveform and Beamforming Design in RIS-ISAC Systems: A Model-Driven Learning Approach

Integrated Sensing and Communication (ISAC) has emerged as a key enabler for future wireless systems. The recently developed symbol-level precoding (SLP) technique holds significant potential for ISAC waveform design, as it leverages both temporal and spatial degrees of freedom (DoFs) to enhance multi-user communication and radar sensing capabilities. Concurrently, reconfigurable intelligent surfaces (RIS) offer additional controllable propagation paths, further amplifying interest in their application. However, previous studies have encountered substantial computational challenges due to the complexity of jointly designing SLP-based waveforms and RIS passive beamforming. In this paper, we propose a novel model-driven learning approach that jointly optimizes waveform and beamforming by unfolding the iterative alternative direction method of multipliers (ADMM) algorithm. Two joint design algorithms are developed for radar target detection and direction-of-arrival (DoA) estimation tasks in a cluttered RIS-ISAC system. While ensuring the communication quality-of-service (QoS) requirements, our objectives are: 1) to maximize the radar output signal-to-interference-plus-noise ratio (SINR) for target detection, and 2) to minimize the Cramér-Rao bound (CRB) for DoA estimation. Simulation results verify that our proposed model-driven learning algorithms achieve satisfactory communication and sensing performance, while also offering a substantial reduction in computational complexity, as reflected by the average execution time.

eess.SP↗

arXiv2025

From Principles to Applications: A Comprehensive Survey of Discrete Tokenizers in Generation, Comprehension, Recommendation, and Information Retrieval

Discrete tokenizers have emerged as indispensable components in modern machine learning systems, particularly within the context of autoregressive modeling and large language models (LLMs). These tokenizers serve as the critical interface that transforms raw, unstructured data from diverse modalities into discrete tokens, enabling LLMs to operate effectively across a wide range of tasks. Despite their central role in generation, comprehension, and recommendation systems, a comprehensive survey dedicated to discrete tokenizers remains conspicuously absent in the literature. This paper addresses this gap by providing a systematic review of the design principles, applications, and challenges of discrete tokenizers. We begin by dissecting the sub-modules of tokenizers and systematically demonstrate their internal mechanisms to provide a comprehensive understanding of their functionality and design. Building on this foundation, we synthesize state-of-the-art methods, categorizing them into multimodal generation and comprehension tasks, and semantic tokens for personalized recommendations. Furthermore, we critically analyze the limitations of existing tokenizers and outline promising directions for future research. By presenting a unified framework for understanding discrete tokenizers, this survey aims to guide researchers and practitioners in addressing open challenges and advancing the field, ultimately contributing to the development of more robust and versatile AI systems.

cs.IR↗

arXiv2025

Beam Measurements of Full Stokes Parameters for the FAST L-band 19-beam Receiver

The Five-hundred-meter Aperture Spherical radio Telescope (FAST) has been fully operational since 11 January 2020. We present a comprehensive analysis of the beam structure for each of the 19 feed horns on FAST's L-band receiver across the Stokes I, Q, U, and V parameters. Using an on-the-fly mapping pattern, we conducted simultaneous sky mapping using all 19 beams directed towards polarization calibrators J1407+2827 and J0854+2006 from 2020 to 2022. Electromagnetic simulations were also performed to model the telescope's beam patterns in all Stokes parameters. Our findings reveal a symmetrical Gaussian pattern in the Stokes I parameter of the central beam without strong sidelobes, while the off-center beams exhibit significant asymmetrical shapes that can be fitted using a combination of log-normal and Gaussian distributions. The inner beams have higher relative beam efficiencies and smaller beam sizes compared to those of the outer beams. The sidelobes of the inner beams contribute approximately 2% of the total flux in the main lobe, increasing to 5% for outer beams, with a peak at 6.8%. In Stokes U, a distinct four-lobed cloverleaf beam squash structure is observed, with similar intensity levels in both inner and outer beams. In Stokes V, a two-lobed beam squint structure is observed in the central beam, along with a secondary eight-lobed structure. The highest squint peak in Stokes V is about 0.3% of the Stokes I in the outer beams. These results align closely with the simulations, providing valuable insights for the design of radio multi-beam observations.

astro-ph.IM↗

arXiv2025

HCMRM: A High-Consistency Multimodal Relevance Model for Search Ads

Search advertising is essential for merchants to reach the target users on short video platforms. Short video ads aligned with user search intents are displayed through relevance matching and bid ranking mechanisms. This paper focuses on improving query-to-video relevance matching to enhance the effectiveness of ranking in ad systems. Recent vision-language pre-training models have demonstrated promise in various multimodal tasks. However, their contribution to downstream query-video relevance tasks is limited, as the alignment between the pair of visual signals and text differs from the modeling of the triplet of the query, visual signals, and video text. In addition, our previous relevance model provides limited ranking capabilities, largely due to the discrepancy between the binary cross-entropy fine-tuning objective and the ranking objective. To address these limitations, we design a high-consistency multimodal relevance model (HCMRM). It utilizes a simple yet effective method to enhance the consistency between pre-training and relevance tasks. Specifically, during the pre-training phase, along with aligning visual signals and video text, several keywords are extracted from the video text as pseudo-queries to perform the triplet relevance modeling. For the fine-tuning phase, we introduce a hierarchical softmax loss, which enables the model to learn the order within labels while maximizing the distinction between positive and negative samples. This promotes the fusion ranking of relevance and bidding in the subsequent ranking stage. The proposed method has been deployed in the Kuaishou search advertising system for over a year, contributing to a 6.1% reduction in the proportion of irrelevant ads and a 1.4% increase in ad revenue.

cs.IR↗

arXiv2025

Future-Conditioned Recommendations with Multi-Objective Controllable Decision Transformer

Securing long-term success is the ultimate aim of recommender systems, demanding strategies capable of foreseeing and shaping the impact of decisions on future user satisfaction. Current recommendation strategies grapple with two significant hurdles. Firstly, the future impacts of recommendation decisions remain obscured, rendering it impractical to evaluate them through direct optimization of immediate metrics. Secondly, conflicts often emerge between multiple objectives, like enhancing accuracy versus exploring diverse recommendations. Existing strategies, trapped in a "training, evaluation, and retraining" loop, grow more labor-intensive as objectives evolve. To address these challenges, we introduce a future-conditioned strategy for multi-objective controllable recommendations, allowing for the direct specification of future objectives and empowering the model to generate item sequences that align with these goals autoregressively. We present the Multi-Objective Controllable Decision Transformer (MocDT), an offline Reinforcement Learning (RL) model capable of autonomously learning the mapping from multiple objectives to item sequences, leveraging extensive offline data. Consequently, it can produce recommendations tailored to any specified objectives during the inference stage. Our empirical findings emphasize the controllable recommendation strategy's ability to produce item sequences according to different objectives while maintaining performance that is competitive with current recommendation strategies across various objectives.

cs.IR↗

arXiv2025

DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender Systems

The integration of Large Language Models (LLMs) into recommender systems has led to substantial performance improvements. However, this often comes at the cost of diminished recommendation diversity, which can negatively impact user satisfaction. To address this issue, controllable recommendation has emerged as a promising approach, allowing users to specify their preferences and receive recommendations that meet their diverse needs. Despite its potential, existing controllable recommender systems frequently rely on simplistic mechanisms, such as a single prompt, to regulate diversity-an approach that falls short of capturing the full complexity of user preferences. In response to these limitations, we propose DLCRec, a novel framework designed to enable fine-grained control over diversity in LLM-based recommendations. Unlike traditional methods, DLCRec adopts a fine-grained task decomposition strategy, breaking down the recommendation process into three sequential sub-tasks: genre prediction, genre filling, and item prediction. These sub-tasks are trained independently and inferred sequentially according to user-defined control numbers, ensuring more precise control over diversity. Furthermore, the scarcity and uneven distribution of diversity-related user behavior data pose significant challenges for fine-tuning. To overcome these obstacles, we introduce two data augmentation techniques that enhance the model's robustness to noisy and out-of-distribution data. These techniques expose the model to a broader range of patterns, improving its adaptability in generating recommendations with varying levels of diversity. Our extensive empirical evaluation demonstrates that DLCRec not only provides precise control over diversity but also outperforms state-of-the-art baselines across multiple recommendation scenarios.

cs.IR↗

arXiv2025

FEASTS: Radial Distribution of HI surface densities down to 0.01 M$_{\odot}$ pc$^{-2}$ of 35 Nearby Galaxies

We present the HI surface density ($Σ_{\rm HI}$) radial distributions based on total-power HI images obtained by FAST in the FEASTS program, for 35 galaxies with inclinations lower than 72 degree. We derive the HI radius $R_{001}$, which is the radius for the 0.01 $\,M_{\odot}\,{\rm pc}^{-2}$ ($\sim10^{18.1}\,{\rm cm}^{-2}$) iso-density level, 100 times deeper than the 1 $\,M_{\odot}\,{\rm pc}^{-2}$ level previously commonly used to measure $R_1$. The profile shapes show a large diversity at a given radius in units of kpc, group virial radius, and $R_1$, but align more tightly with radius normalized by $R_{001}$. The universal HI profile has a scatter of $\sim0.2$ dex, and a scale-length of $\sim0.11R_{001}$ in the outer region. We derive a new $R_{001}$-$M_{\rm HI}$ relation, which has a scatter of 0.02 dex, and similar slope of $\sim$0.5 as the previously known $R_1$-$M_{\rm HI}$ relation. Excluding strongly tidal-interacting galaxies, the ratio $R_{001}/R_1$ (anti-)correlate strongly and significantly with the HI-to-stellar mass ratio and sSFR, but not with the stellar mass, $M_{\rm HI}$, dark matter mass, or SFR. The strongly tidal-interacting galaxies tend to show deviations from these trends, and have the most flattened profiles. These results imply that in absence of major tidal interactions, physical processes must cooperate so that $Σ_{\rm HI}$ distributes in a self-similar way in the outer region down to the 0.01$\,M_{\odot}\,{\rm pc}^{-2}$ level. Moreover, they may drive gas flows in such a way, that HI-richer galaxies have HI disks not only extend further, but also transport HI inward more efficiently from $R_{001}$ to $R_1$.

astro-ph.GA↗