Searcharxiv⌕ Search

arXiv subjects

Rong Liu

Publications and source records attributed to Rong Liu.

At least 37 records · Page 2Linked to original sources

Retrieved dropout imputation considering administrative study withdrawal

The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) E9 (R1) Addendum provides a framework for defining estimands in clinical trials. Treatment policy strategy is the mostly used approach to handle intercurrent events in defining estimands. Imputing missing values for potential outcomes under the treatment policy strategy has been discussed in the literature. Missing values as a result of administrative study withdrawals (such as site closures due to business reasons, COVID-19 control measures, and geopolitical conflicts, etc.) are often imputed in the same way as other missing values occurring after intercurrent events related to safety or efficacy. Some research suggests using a hypothetical strategy to handle the treatment discontinuations due to administrative study withdrawal in defining the estimands and imputing the missing values based on completer data assuming missing at random, but this approach ignores the fact that subjects might experience other intercurrent events had they not had the administrative study withdrawal. In this article, we consider the administrative study withdrawal censors the normal real-world like intercurrent events and propose two methods for handling the corresponding missing values under the retrieved dropout imputation framework. Simulation shows the two methods perform well. We also applied the methods to actual clinical trial data evaluating an anti-diabetes treatment.

stat.AP↗

FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design

Recent advancements in Large Language Models (LLMs) have exhibited notable efficacy in question-answering (QA) tasks across diverse domains. Their prowess in integrating extensive web knowledge has fueled interest in developing LLM-based autonomous agents. While LLMs are efficient in decoding human instructions and deriving solutions by holistically processing historical inputs, transitioning to purpose-driven agents requires a supplementary rational architecture to process multi-source information, establish reasoning chains, and prioritize critical tasks. Addressing this, we introduce \textsc{FinMem}, a novel LLM-based agent framework devised for financial decision-making. It encompasses three core modules: Profiling, to customize the agent's characteristics; Memory, with layered message processing, to aid the agent in assimilating hierarchical financial data; and Decision-making, to convert insights gained from memories into investment decisions. Notably, \textsc{FinMem}'s memory module aligns closely with the cognitive structure of human traders, offering robust interpretability and real-time tuning. Its adjustable cognitive span allows for the retention of critical information beyond human perceptual limits, thereby enhancing trading outcomes. This framework enables the agent to self-evolve its professional knowledge, react agilely to new investment cues, and continuously refine trading decisions in the volatile financial environment. We first compare \textsc{FinMem} with various algorithmic agents on a scalable real-world financial dataset, underscoring its leading trading performance in stocks. We then fine-tuned the agent's perceptual span and character setting to achieve a significantly enhanced trading performance. Collectively, \textsc{FinMem} presents a cutting-edge LLM agent framework for automated trading, boosting cumulative investment returns.

q-fin.CP↗

Stand for Something or Fall for Everything: Predict Misinformation Spread with Stance-Aware Graph Neural Networks

Although pervasive spread of misinformation on social media platforms has become a pressing challenge, existing platform interventions have shown limited success in curbing its dissemination. In this study, we propose a stance-aware graph neural network (stance-aware GNN) that leverages users' stances to proactively predict misinformation spread. As different user stances can form unique echo chambers, we customize four information passing paths in stance-aware GNN, while the trainable attention weights provide explainability by highlighting each structure's importance. Evaluated on a real-world dataset, stance-aware GNN outperforms benchmarks by 32.65% and exceeds advanced GNNs without user stance by over 4.69%. Furthermore, the attention weights indicate that users' opposition stances have a higher impact on their neighbors' behaviors than supportive ones, which function as social correction to halt misinformation propagation. Overall, our study provides an effective predictive model for platforms to combat misinformation, and highlights the impact of user stances in the misinformation propagation.

cs.SI↗

Orbits of charged particles with an azimuthal initial velocity in a dipole magnetic field

Nonintegrable dynamical systems have complex structures in their phase space. Motion of a test charged particle in a dipole magnetic field can be reduced to a 2 degree-of-freedom (2 d.o.f.) nonintegrable Hamiltonian system. We carried out a systematic study of orbits of charged particles with an azimuthal initial velocity in a dipole field via calculation of their Lyapunov characteristic exponents (LCEs) and escape times for a dimensionless energy less and greater than 1/32, respectively. Meridian plane periodic orbits symmetric with respect to the equatorial plane are then identified. We found that 1) symmetric periodic orbits can be classified into several classes based on their number of crossing points on the equatorial plane; 2) the initial conditions of these classes locate on closed loops or closed curves going through the origin; 3) most isolated regions of stable quasi-periodic orbits are associated asymmetric stable periodic orbits; 4) classes of asymmetric periodic orbits either go through the origin or terminate at flat equatorial plane orbits with the other end approaching centers of spiral structures; 5) there are apparent self-similarities in the above features with the decrease of energy.

math.DS↗

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- XV. Steady Accretion from Global Collapse to Core Feeding in Massive Hub-filament System SDC335

We present ALMA Band-3/7 observations towards "the Heart" of a massive hub-filament system (HFS) SDC335, to investigate its fragmentation and accretion. At a resolution of $\sim0.03$ pc, 3 mm continuum emission resolves two massive dense cores MM1 and MM2, with $383(^{+234}_{-120})$ $M_\odot$ (10-24% mass of "the Heart") and $74(^{+47}_{-24})$ $M_\odot$, respectively. With a resolution down to 0.01 pc, 0.87 mm continuum emission shows MM1 further fragments into six condensations and multi-transition lines of H$_2$CS provide temperature estimation. The relation between separation and mass of condensations at a scale of 0.01 pc favors turbulent Jeans fragmentation where the turbulence seems to be scale-free rather than scale-dependent. We use the H$^{13}$CO$^+$ (1-0) emission line to resolve the complex gas motion inside "the Heart" in position-position-velocity space. We identify four major gas streams connected to large-scale filaments, inheriting the anti-clockwise spiral pattern. Along these streams, gas feeds the central massive core MM1. Assuming an inclination angle of $45(\pm15)^{\circ}$ and a H$^{13}$CO$^+$ abundance of $5(\pm3)\times10^{-11}$, the total mass infall rate is estimated to be $2.40(\pm0.78)\times10^{-3}$ $M_\odot$ yr$^{-1}$, numerically consistent with the accretion rates derived from the clump-scale spherical infall model and the core-scale outflows. The consistency suggests a continuous, near steady-state, and efficient accretion from global collapse, therefore ensuring core feeding. Our comprehensive study of SDC335 showcases the detailed gas kinematics in a prototypical massive infalling clump and calls for further systematic and statistical analyses in a large sample.

astro-ph.GA↗

MURPHY: Relations Matter in Surgical Workflow Analysis

Autonomous robotic surgery has advanced significantly based on analysis of visual and temporal cues in surgical workflow, but relational cues from domain knowledge remain under investigation. Complex relations in surgical annotations can be divided into intra- and inter-relations, both valuable to autonomous systems to comprehend surgical workflows. Intra- and inter-relations describe the relevance of various categories within a particular annotation type and the relevance of different annotation types, respectively. This paper aims to systematically investigate the importance of relational cues in surgery. First, we contribute the RLLS12M dataset, a large-scale collection of robotic left lateral sectionectomy (RLLS), by curating 50 videos of 50 patients operated by 5 surgeons and annotating a hierarchical workflow, which consists of 3 inter- and 6 intra-relations, 6 steps, 15 tasks, and 38 activities represented as the triplet of 11 instruments, 8 actions, and 16 objects, totaling 2,113,510 video frames and 12,681,060 annotation entities. Correspondingly, we propose a multi-relation purification hybrid network (MURPHY), which aptly incorporates novel relation modules to augment the feature representation by purifying relational features using the intra- and inter-relations embodied in annotations. The intra-relation module leverages a R-GCN to implant visual features in different graph relations, which are aggregated using a targeted relation purification with affinity information measuring label consistency and feature similarity. The inter-relation module is motivated by attention mechanisms to regularize the influence of relational features based on the hierarchy of annotation types from the domain knowledge. Extensive experimental results on the curated RLLS dataset confirm the effectiveness of our approach, demonstrating that relations matter in surgical workflow analysis.

cs.CV↗

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- XI. From inflow to infall in hub-filament systems

We investigate the presence of hub-filament systems in a large sample of 146 active proto-clusters, using H$^{13}$CO$^{+}$ J=1-0 molecular line data obtained from the ATOMS survey. We find that filaments are ubiquitous in proto-clusters, and hub-filament systems are very common from dense core scales ($\sim$0.1 pc) to clump/cloud scales ($\sim$1-10 pc). The proportion of proto-clusters containing hub-filament systems decreases with increasing dust temperature ($T_d$) and luminosity-to-mass ratios ($L/M$) of clumps, indicating that stellar feedback from H{\sc ii} regions gradually destroys the hub-filament systems as proto-clusters evolve. Clear velocity gradients are seen along the longest filaments with a mean velocity gradient of 8.71 km s$^{-1}$pc$^{-1}$ and a median velocity gradient of 5.54 km s$^{-1}$pc$^{-1}$. We find that velocity gradients are small for filament lengths larger than $\sim$1~pc, probably hinting at the existence of inertial inflows, although we cannot determine whether the latter are driven by large-scale turbulence or large-scale gravitational contraction. In contrast, velocity gradients below $\sim$1~pc dramatically increase as filament lengths decrease, indicating that the gravity of the hubs or cores starts to dominate gas infall at small scales. We suggest that self-similar hub-filament systems and filamentary accretion at all scales may play a key role in high-mass star formation.

astro-ph.GA↗

ALMA Survey of Orion Planck Galactic Cold Clumps (ALMASOP): How do dense core properties affect the multiplicity of protostars?

During the transition phase from a prestellar to a protostellar cloud core, one or several protostars can form within a single gas core. The detailed physical processes of this transition, however, still remain unclear. We present 1.3 mm dust continuum and molecular line observations with the Atacama Large Millimeter/submillimeter Array (ALMA) toward 43 protostellar cores in the Orion Molecular Cloud Complex ($λ$ Orionis, Orion B, and Orion A) with an angular resolution of $\sim$ 0.35" ($\sim$ 140 au). In total, we detect 13 binary/multiple systems. We derive an overall multiplicity frequency (MF) of 28$\%$ $\pm$ 4$\%$ and a companion star fraction (CSF) of 51$\%$ $\pm$ 6$\%$, over a separation range of 300-8900 au. The median separation of companions is about 2100 au. The occurrence of stellar multiplicity may depend on the physical characteristics of the dense cores. Notably, those containing binary/multiple systems tend to show higher gas density and Mach number than cores forming single stars. The integral-shaped filament (ISF) of Orion A giant molecular cloud (GMC), which has the highest gas density and hosts high-mass star formation in its central region (the Orion Nebula cluster), shows the highest MF and CSF among the Orion GMCs. In contrast, the $λ$ Orionis Giant Molecular Cloud (GMC) has a lower MF and CSF than the Orion B and Orion A GMCs, indicating that feedback from HII regions may suppress the formation of multiple systems. We also find that the protostars comprising a binary/multiple system are usually at different evolutionary stages.

astro-ph.GA↗

A Comprehensive Toolbox to Facilitate Quantitative Decision Science in Drug Development: A web-based R shiny application GOahead

Decision-making is critical at each stage of drug development and making informed and transparent Go/No-Go decisions require a sound quantitative decision framework. We designed and implemented GOahead, a comprehensive web-based tool to improve how statisticians and collaborators could prospectively plan and implement the selected Go/No-Go decision approach in real-time. In the paper, we conducted a comprehensive overview of dual-criterion and confidence interval-based approaches to enable quantitative decision-making. illustrative examples are demonstrated for single and two arms designs in both Bayesian and frequentist frameworks, multiple arms design with MCP-MOD is also demonstrated. GOahead can be found on shinyapps server.

stat.AP↗

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- VII. A catalogue of SiO clumps from ACA observations

To understand the nature of SiO emission, we conducted ACA observations of the SiO (2-1) lines toward 146 massive star-forming regions, as part of the ALMA Three-millimeter Observations of Massive Star-forming regions (ATOMS) survey. We detected SiO emission in 128 (87.7$\%$) sources and identified 171 SiO clumps, 105 of which are spatially separated from 3 mm continuum emission. A large amount of the SiO line profiles (60$\%$) are non-Gaussian. The velocity dispersion of the SiO lines ranges from 0.3 to 5.43 km s$^{-1}$. In 63 sources the SiO clumps are associated with H$_\rm{II}$ regions characterized by H40$α$ emission. We find that 68$\%$ (116) of the SiO clumps are associated with strong outflows. The median velocity dispersion of the SiO line for outflow sources and non-outflow sources is 1.91 km s$^{-1}$ and 0.99 km s$^{-1}$, respectively. These results indicate that outflow activities could be connected to strongly shocked gas. The velocity dispersion and [SiO]/[H$^{13}$CO$^+$] intensity ratio do not show any correlation with the dust temperature and particle number density of clumps. We find a positive correlation between the SiO line luminosity and the bolometric luminosity, implying stronger shock activities are associated with more luminous proto-clusters. The SiO clumps in associations with H$_\rm{II}$ regions were found to show a steeper feature in $L_\rm{sio}$/$L_\rm{bol}$. The SiO line luminosity and the fraction of shocked gas have no apparent evidence of correlation with the evolutionary stages traced by luminosity to mass ratio ($L_\rm{bol}/M$).

astro-ph.GA↗

BOP2-DC: Bayesian optimal phase II designs with dual-criterion decision making

The conventional phase II trial design paradigm is to make the go/no-go decision based on the hypothesis testing framework. Statistical significance itself alone, however, may not be sufficient to establish that the drug is clinically effective enough to warrant confirmatory phase III trials. We propose the Bayesian optimal phase II trial design with dual-criterion decision making (BOP2-DC), which incorporates both statistical significance and clinical relevance into decision making. Based on the posterior probability that the treatment effect reaches the lower reference value (statistical significance) and the clinically meaningful value (clinical significance), BOP2-DC allows for go/consider/no-go decisions, rather than a binary go/no-go decision, and it is optimized to maximize the probability of a go decision when the treatment is effective or minimize the sample size when the treatment is futile. BOP2-DC is highly flexible and accommodates various types of endpoints, including binary, continuous, time-to-event, multiple, and co-primary endpoints, in single-arm and randomized trials. Simulation studies show that the BOP2-DC design yields desirable operating characteristics. The software to implement BOP2-DC is freely available at \url{www.trialdesign.org}.

stat.ME↗

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- V. Hierarchical fragmentation and gas dynamics in IRDC G034.43+00.24

We present new 3-mm continuum and molecular lines observations from the ATOMS survey towards the massive protostellar clump, MM1, located in the filamentary infrared dark cloud (IRDC), G034.43+00.24 (G34). The lines observed are the tracers of either dense gas (e.g. HCO+/H13CO+ J = 1-0) or outflows (e.g. CS J = 2-1). The most complete picture to date of seven cores in MM1 is revealed by dust continuum emission. These cores are found to be gravitationally bound, with virial parameter, $α_{vir}<2$. At least four outflows are identified in MM1 with a total outflowing mass of $\sim 45 M_\odot$, and a total energy of $\sim 1\times 10^{47}$ erg, typical of outflows from a B0-type star. Evidence of hierarchical fragmentation, where turbulence dominates over thermal pressure, is observed at both the cloud and the clump scales. This could be linked to the scale-dependent, dynamical mass inflow/accretion on clump and core scales. We therefore suggest that the G34 cloud could be undergoing a dynamical mass inflow/accretion process linked to the multiscale fragmentation, which leads to the sequential formation of fragments of the initial cloud, clumps, and ultimately dense cores, the sites of star formation.

astro-ph.GA↗

ATOMS: ALMA Three-millimeter Observations of Massive Star-forming regions -- VI. On the formation of the "L" type filament in G286.21+0.17

Filaments play an important role in star formation, but the formation process of filaments themselves is still unclear. The high-mass star forming clump G286.21+0.17 (G286 for short) that contains an "L" type filament was thought to undergo global collapse. Our high resolution ALMA band 3 observations resolve the gas kinematics of G286 and reveal two sub-clumps with very different velocities inside it. We find that the "blue profile" (an indicator of gas infall) of HCO+ lines in single dish observations of G286 is actually caused by gas emission from the two sub-clumps rather than gas infall. We advise great caution in interpreting gas kinematics (e.g., infall) from line profiles toward distant massive clumps in single dish observations. Energetic outflows are identified in G286 but the outflows are not strong enough to drive expansion of the two sub-clumps. The two parts of the "L" type filament ("NW-SE" and "NE-SW" filaments) show prominent velocity gradients perpendicular to their major axes, indicating that they are likely formed due to large-scale compression flows. We argue that the large-scale compression flows could be induced by the expansion of nearby giant HII regions. The "NW-SE" and "NE-SW" filaments seem to be in collision, and a large amount of gas has been accumulated in the junction region where the most massive core G286c1 forms.

astro-ph.GA↗

Improving Global Forest Mapping by Semi-automatic Sample Labeling with Deep Learning on Google Earth Images

Global forest cover is critical to the provision of certain ecosystem services. With the advent of the google earth engine cloud platform, fine resolution global land cover mapping task could be accomplished in a matter of days instead of years. The amount of global forest cover (GFC) products has been steadily increasing in the last decades. However, it's hard for users to select suitable one due to great differences between these products, and the accuracy of these GFC products has not been verified on global scale. To provide guidelines for users and producers, it is urgent to produce a validation sample set at the global level. However, this labeling task is time and labor consuming, which has been the main obstacle to the progress of global land cover mapping. In this research, a labor-efficient semi-automatic framework is introduced to build a biggest ever Forest Sample Set (FSS) contained 395280 scattered samples categorized as forest, shrubland, grassland, impervious surface, etc. On the other hand, to provide guidelines for the users, we comprehensively validated the local and global mapping accuracy of all existing 30m GFC products, and analyzed and mapped the agreement of them. Moreover, to provide guidelines for the producers, optimal sampling strategy was proposed to improve the global forest classification. Furthermore, a new global forest cover named GlobeForest2020 has been generated, which proved to improve the previous highest state-of-the-art accuracies (obtained by Gong et al., 2017) by 2.77% in uncertain grids and by 1.11% in certain grids.

cs.CV↗

ATOMS:ALMA Three-millimeter Observations of Massive Star-forming regions -- III :Catalogues of candidate hot molecular cores and Hyper/Ultra compact HII regions

We have identified 453 compact dense cores in 3 mm continuum emission maps in the ATOMS (ALMA Three-millimeter Observations of Massive Star-forming regions) survey, and compiled three catalogues of high-mass star forming cores. One catalogue, referred to as H/UC-HII catalogue, includes 89 cores that enshroud hyper/ultra compact (H/UC) HII regions as characterized by associated compact H40alpha emission. A second catalogue, referred to as pure s-cHMC, includes 32 candidate Hot Molecular Cores (HMCs) showing rich spectra (N>20lines) of complex organic molecules (COMs) but not associated with H/UC-HII regions. The third catalogue, referred to as pure w-cHMC, includes 58 candidate HMCs with relatively low levels of COM richness and not associated with H/UC-HII regions. These three catalogues of dense cores provide an important foundation for future studies of the early stages of high-mass star formation across the Milky Way. We also find that nearly half of H/UC-HII cores are candidate HMCs. From the number counts of COM-containing and H/UC-HII cores, we suggest that the duration of high-mass protostellar cores showing chemically rich features is at least comparable to the lifetime of H/UC-HII regions. For cores in the H/UC-HII catalogue, the width of the H40alpha line increases as the core size decreases, suggesting that the non-thermal dynamical and/or pressure line-broadening mechanisms dominate on the smaller scales of the H/UC-HII cores.

astro-ph.GA↗

Back-n White Neutron Source at CSNS and its Applications

Back-streaming neutrons from the spallation target of the China Spallation Neutron Source (CSNS) that emit through the incoming proton channel were exploited to build a white neutron beam facility (the so-called Back-n white neutron source), which was completed in March 2018. The Back-n neutron beam is very intense, at approximately 2*10^7 n/cm^2/s at 55 m from the target, and has a nominal proton beam with a power of 100 kW in the CSNS-I phase and a kinetic energy of 1.6 GeV and a thick tungsten target in multiple slices with modest moderation from the cooling water through the slices. In addition, the excellent energy spectrum spanning from 0.5 eV to 200 MeV, and a good time resolution related to the time-of-flight measurements make it a typical white neutron source for nuclear data measurements; its overall performance is among that of the best white neutron sources in the world. Equipped with advanced spectrometers, detectors, and application utilities, the Back-n facility can serve wide applications, with a focus on neutron-induced cross-section measurements. This article presents an overview of the neutron beam characteristics, the experimental setups, and the ongoing applications at Back-n.

physics.acc-ph↗

Statistical Inference for Generalized Additive Partially Linear Model

The Generalized Additive Model (GAM) is a powerful tool and has been well studied. This model class helps to identify additive regression structure. Via available test procedures one may identify the regression structure even sharper if some component functions have parametric form. The Generalized Additive Partially Linear Models (GAPLM) enjoy the simplicity of the GLM and the flexibility of the GAM because they combine both parametric and nonparametric components. We use the hybrid spline-backfitted kernel estimation method, which combines the best features of both spline and kernel methods for making fast, efficient and reliable estimation under alpha-mixing condition. In addition, simultaneous confidence corridors (SCCs) for testing overall trends and empirical likelihood confidence region for parameters are provided under independent condition. The asymptotic properties are obtained and simulation results support the theoretical properties. For the application, we use the GAPLM to improve the accuracy ratio of the default predictions for $19610$ German companies. The quantlets for this paper are available on https://github.com.

stat.ME↗

Outstanding Thermal Conductivity of Single Atomic Layer Isotope-Modified Boron Nitride

Materials with high thermal conductivities (k) is valuable to solve the challenge of waste heat dissipation in highly integrated and miniaturized modern devices. Herein, we report the first synthesis of atomically thin isotopically pure hexagonal boron nitride (BN) and its one of the highest k among all semiconductors and electric insulators. Single atomic layer (1L) BN enriched with 11B has a k up to 1009 W/mK at room temperature. We find that the isotope engineering mainly suppresses the out-of-plane optical (ZO) phonon scatterings in BN, which subsequently reduces acoustic-optical scatterings between ZO and transverse acoustic (TA) and longitudinal acoustic (LA) phonons. On the other hand, reducing the thickness to single atomic layer diminishes the interlayer interactions and hence Umklapp scatterings of the out-of-plane acoustic (ZA) phonons, though this thickness-induced k enhancement is not as dramatic as that in naturally occurring BN. With many of its unique properties, atomically thin monoisotopic BN is promising on heat management in van der Waals (vdW) devices and future flexible electronics. The isotope engineering of atomically thin BN may also open up other appealing applications and opportunities in 2D materials yet to be explored.

cond-mat.mtrl-sci↗