51 research outputs found
Controllable Text Generation with Residual Memory Transformer
Large-scale Causal Language Models (CLMs), e.g., GPT3 and ChatGPT, have
brought great success in text generation. However, it is still an open
challenge to control the generation process of CLM while balancing flexibility,
control granularity, and generation efficiency. In this paper, we provide a new
alternative for controllable text generation (CTG), by designing a
non-intrusive, lightweight control plugin to accompany the generation of CLM at
arbitrary time steps. The proposed control plugin, namely Residual Memory
Transformer (RMT), has an encoder-decoder setup, which can accept any types of
control conditions and cooperate with CLM through a residual learning paradigm,
to achieve a more flexible, general, and efficient CTG. Extensive experiments
are carried out on various control tasks, in the form of both automatic and
human evaluations. The results show the superiority of RMT over a range of
state-of-the-art approaches, proving the effectiveness and versatility of our
approach.Comment: github:https://github.com/littlehacker26/Residual_Memory_Transforme
Measurement of the high energy -rays from heavy ion reactions using \v{C}erenkov detector
The energetic bremsstrahlung photons up to 100 MeV produced in heavy ion
collisions can be used as a sensitive probe to the short range correlation in
atomic nuclei. The energy of the -rays can be measured by collecting
the \v{C}erenkov light in medium induced by the fast electrons generated in
Compton scattering or electromagnetic shower of the incident ray. Two
types of detectors, based on pure water and lead glass as the sensitive
material respectively, are designed for the above purpose. The
response and optical photon propagation in detectors have been simulated based
on the electromagnetic and optical processes in Geant4. The inherent energy
resolution of for water and
for lead glass are obtained. The geometry size of
lead glass and water are optimized at cm and
cm, respectively, for detecting high energy
-rays at 160 MeV. Hough transform method has been applied to
reconstruct the direction of the incident -rays, giving the ability to
distinguish experimentally the high-energy rays produced in the
reactions on the target from the random background cosmic ray muons
Dynamic Transfer Learning across Graphs
Transferring knowledge across graphs plays a pivotal role in many high-stake
domains, ranging from transportation networks to e-commerce networks, from
neuroscience to finance. To date, the vast majority of existing works assume
both source and target domains are sampled from a universal and stationary
distribution. However, many real-world systems are intrinsically dynamic, where
the underlying domains are evolving over time. To bridge the gap, we propose to
shift the problem to the dynamic setting and ask: given the label-rich source
graphs and the label-scarce target graphs observed in previous T timestamps,
how can we effectively characterize the evolving domain discrepancy and
optimize the generalization performance of the target domain at the incoming
T+1 timestamp? To answer the question, for the first time, we propose a
generalization bound under the setting of dynamic transfer learning across
graphs, which implies the generalization performance is dominated by domain
evolution and domain discrepancy between source and target domains. Inspired by
the theoretical results, we propose a novel generic framework DyTrans to
improve knowledge transferability across dynamic graphs. In particular, we
start with a transformer-based temporal encoding module to model temporal
information of the evolving domains; then, we further design a dynamic domain
unification module to efficiently learn domain-invariant representations across
the source and target domains. Finally, extensive experiments on various
real-world datasets demonstrate the effectiveness of DyTrans in transferring
knowledge from dynamic source domains to dynamic target domains
A tough and mechanically stable adhesive hydrogel for non-invasive wound repair
Wound healing has been a great challenge throughout human history. Improper treatment for wounds is so easy to lead to infection and a series of serious symptoms, even death. Because of the ability of absorbing fluid and keeping a moist environment, the hydrogel with 3D networks is ideal candidate for wound dressing. More important, it has good biocompatibility. However, most of the hydrogel dressings reported have weak mechanical properties and adhesion properties, which greatly limit their clinical application. Herein, a tough adhesive hydrogel with good mechanical stability for non-invasive wound repair is reported. The hydrogel is composed of polyethylene glycol dimethacrylate (PEGDA), chitosan (CS) and chitin nano-whisker (CW). PEGDA and CS form interpenetrating network hydrogel through free radical polymerization reaction under the UV light. The introduction of CW further enhances the toughness of the hydrogel. The pH-sensitive CS can form adhesion to various materials through topological adhesion. As a wound closure repair material, PEGDA/CS/CW hydrogel not only has the characteristic of effectively closing the wound, defending against invading bacteria, and keeping the wound clean, but also has good tensile and mechanical stability, which is expected to realize the closure and repair of joints and other moving parts of the wound. This adhesive hydrogel is proven a promising material for wound closure repair
A CsI hodoscope on CSHINE for Bremsstrahlung {\gamma}-rays in Heavy Ion Reactions
Bremsstrahlung production in heavy ion reactions at Fermi energies
carries important physical information including the nuclear symmetry energy at
supra-saturation densities. In order to detect the high energy Bremsstrahlung
rays, a hodoscope consisting of 15 CsI(Tl) crystal read out by photo
multiplier tubes has been built, tested and operated in experiment. The
resolution, efficiency and linear response of the units to rays have
been studied using radioactive source and reactions. The
inherent energy resolution of is obtained.
Reconstruction method has been established through Geant 4 simulations,
reproducing the experimental results where comparison can be made. Using the
reconstruction method developed, the whole efficiency of the hodoscope is about
against the emissions at the target position,
exhibiting insignificant dependence on the energy of incident rays
above 20 MeV. The hodoscope is operated in the experiment of Kr +
Sn at 25 MeV/u, and a full energy spectrum up to 80 MeV has
been obtained.Comment: 9 pages, 19 figure
Probing high-momentum component in nucleon momentum distribution by neutron-proton bremsstrahlung {\gamma}-rays in heavy ion reactions
The high momentum tail (HMT) of nucleons, as a signature of the short-range
correlations in nuclei, has been investigated by the high-energy bremsstrahlung
rays produced in Kr + Sn at 25 MeV/u. The energetic
photons are measured by a CsI(Tl) hodoscope mounted on the spectrometer CSHINE.
The energy spectrum above 30 MeV can be reproduced by the IBUU model
calculations incorporating the photon production channel from process in
which the HMTs of nucleons is considered. A non-zero HMT ratio of about
is favored by the data. The effect of the capture channel is
demonstrated
Revisit to the yield ratio of triton and He as an indicator of neutron-rich neck emission
The neutron rich neck zone created in heavy ion reaction is experimentally
probed by the production of the isobars. The energy spectra and angular
distributions of triton and He are measured with the CSHINE detector in
Kr +Pb reactions at 25 MeV/u. While the energy spectrum of
He is harder than that of triton, known as "He-puzzle", the yield
ratio presents a robust rising trend with the polar angle in
laboratory. Using the fission fragments to reconstruct the fission plane, the
enhancement of out-plane is confirmed in comparison to the
in-plane ratios. Transport model simulations reproduce qualitatively the
experimental trends, but the quantitative agreement is not achieved. The
results demonstrate that a neutron rich neck zone is formed in the reactions.
Further studies are called for to understand the clustering and the isospin
dynamics related to neck formation
Domain decomposition approach for parallel improvement of tetrahedral meshes
Presently, a tetrahedral mesher based on the Delaunay triangulation approach may outperform a tetrahedral improver based on local smoothing and flip operations by nearly one order in terms of computing time. Parallelization is a feasible way to speed up the improver and enable it to handle large-scale meshes. In this study, a novel domain decomposition approach is proposed for parallel mesh improvement. It analyses the dual graph of the input mesh to build an inter-domain boundary that avoids small dihedral angles and poorly shaped faces. Consequently, the parallel improver can fit this boundary without compromising the mesh quality. Meanwhile, the new method does not involve any inter-processor communications and therefore runs very efficiently. A parallel pre-processing pipeline that combines the proposed improver and existing parallel surface and volume meshers can prepare a quality mesh containing hundreds of millions of elements in minutes. Experiments are presented to show that the developed system is robust and applicable to models of a complication level experienced in industry
Transcriptome Profiling of Citrus Fruit Response to Huanglongbing Disease
Huanglongbing (HLB) or “citrus greening” is the most destructive citrus disease worldwide. In this work, we studied host responses of citrus to infection with Candidatus Liberibacter asiaticus (CaLas) using next-generation sequencing technologies. A deep mRNA profile was obtained from peel of healthy and HLB-affected fruit. It was followed by pathway and protein-protein network analysis and quantitative real time PCR analysis of highly regulated genes. We identified differentially regulated pathways and constructed networks that provide a deep insight into the metabolism of affected fruit. Data mining revealed that HLB enhanced transcription of genes involved in the light reactions of photosynthesis and in ATP synthesis. Activation of protein degradation and misfolding processes were observed at the transcriptomic level. Transcripts for heat shock proteins were down-regulated at all disease stages, resulting in further protein misfolding. HLB strongly affected pathways involved in source-sink communication, including sucrose and starch metabolism and hormone synthesis and signaling. Transcription of several genes involved in the synthesis and signal transduction of cytokinins and gibberellins was repressed while that of genes involved in ethylene pathways was induced. CaLas infection triggered a response via both the salicylic acid and jasmonic acid pathways and increased the transcript abundance of several members of the WRKY family of transcription factors. Findings focused on the fruit provide valuable insight to understanding the mechanisms of the HLB-induced fruit disorder and eventually developing methods based on small molecule applications to mitigate its devastating effects on fruit production
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