1,178 research outputs found
The ionization rates of galactic nuclei and disks from Herschel/HIFI observations of water and its associated ions
(Abridged) We present Herschel/HIFI spectra of the H2O 1113 GHz and H2O+ 1115
GHz lines toward five nearby prototypical starburst/AGN systems, and OH+ 971
GHz spectra toward three of these. The beam size of 20" corresponds to
resolutions between 0.35 and 7 kpc. The observed line profiles range from pure
absorption (NGC 4945, M82) to P-Cygni indicating outflow (NGC 253, Arp 220) and
inverse P-Cygni indicating infall (Cen A). The similarity of the H2O, OH+, and
H2O+ profiles to each other and to HI indicates that diffuse and dense gas
phases are well mixed. We estimate column densities assuming negligible
excitation (for absorption features) and using a non-LTE model (for emission
features), adopting calculated collision data for H2O and OH+, and rough
estimates for H2O+. Column densities range from ~10^13 to ~10^15 cm^-2 for each
species, and are similar between absorption and emission components, indicating
that the nuclear region does not contribute much to the emission in these
ground-state lines. The N(H2O)/N(H2O+) ratios of 1.4-5.6 indicate an origin of
the lines in diffuse gas, and the N(OH+)/N(H2O+) ratios of 1.6-3.1 indicate a
low H2 fraction (~11%) in the gas.
Adopting recent Galactic values for the average gas density and the
ionization efficiency, we find ionization rates for our sample galaxies of
~3x10^-16 s^-1 which are similar to the value for the Galactic disk, but ~10x
below that of the Galactic Center and ~100x below estimates for AGN from
excited-state H3O+ lines. We conclude that the ground-state lines of water and
its associated ions probe primarily non-nuclear gas in the disks of these
centrally active galaxies. Our data thus provide evidence for a decrease in
ionization rate by a factor of ~10 from the nuclei to the disks of galaxies, as
found before for the Milky Way.Comment: Accepted for publication in Astronomy & Astrophysics; 8 pages, 8
figure
Research of Coordinated Control Strategy for Multi-UHVDC in AC/DC Hybrid Power Grid
AbstractThe control strategy and modulation scheme of DC system have great effect on transient stability and dynamical stability in AC/DC hybrid power grid. In order to decrease the effect of UHVDC blocks and AC lines faults, a coordinated control strategy of emergency power modulation and small signal modulation is put forward by making use of the fast controllability and the overload capability of HVDC system. Simulation results show that the coordinated control strategy may decrease power loss and improve the dynamical stability of the AC/DC hybrid system
Simulation of coastal resource and environmental carrying capacity in the Yangtze River delta coastal zone based on shared socioeconomic pathways
Study of resource and environmental carrying capacity is an important research content of sustainable development science and the theoretical support for land space optimization. Existing research theories need to be deepened, and spatial simulation studies are relatively lacking. This study aimed to assess the current and future resource and environmental carrying capacity in the Yangtze River Delta region’s coastal zone and enhance sustainable development by exploring the application of shared socioeconomic pathway (SSPs) scenarios at the spatial pattern scale in regional resource and environmental carrying capacity simulation studies. Based on the FLUS and InVEST models, this study introduced the Coastal Resource and Environmental Carrying Capacity Index (CRECC) from the dimensions of “pressure” and “support” using land use remote sensing monitoring data and SSPs scenario data. A CRECC evaluation index system and quantitative evaluation method for the Yangtze River Delta were constructed. The results showed that from 2000 to 2020, the CRECC of the Yangtze River Delta coastal zone increased, the carrying capacity decreased, and the spatial distribution was low in the north and high in the south. The carrying capacity under the five SSP scenarios did not improve. The mismatch between natural ecological conditions and the intensity of human activities in the shoreline area was more prominent than in the study area, with the SSP1 and SSP5 scenarios being the most obvious. The supporting indicators have a more significant influence on improving CRECC than the pressure indicators, among which the supply capacity of water resources, land resources, and atmospheric environmental quality are the main limiting factors in the process of future sustainable economic-ecological development. This study provides ideas and examples for exploring spatial and temporal predictions of resources and environmental carrying capacity in coastal zones
SEAT: Stable and Explainable Attention
Currently, attention mechanism becomes a standard fixture in most
state-of-the-art natural language processing (NLP) models, not only due to
outstanding performance it could gain, but also due to plausible innate
explanation for the behaviors of neural architectures it provides, which is
notoriously difficult to analyze. However, recent studies show that attention
is unstable against randomness and perturbations during training or testing,
such as random seeds and slight perturbation of embedding vectors, which
impedes it from becoming a faithful explanation tool. Thus, a natural question
is whether we can find some substitute of the current attention which is more
stable and could keep the most important characteristics on explanation and
prediction of attention. In this paper, to resolve the problem, we provide a
first rigorous definition of such alternate namely SEAT (Stable and Explainable
Attention). Specifically, a SEAT should has the following three properties: (1)
Its prediction distribution is enforced to be close to the distribution based
on the vanilla attention; (2) Its top-k indices have large overlaps with those
of the vanilla attention; (3) It is robust w.r.t perturbations, i.e., any
slight perturbation on SEAT will not change the prediction distribution too
much, which implicitly indicates that it is stable to randomness and
perturbations. Finally, through intensive experiments on various datasets, we
compare our SEAT with other baseline methods using RNN, BiLSTM and BERT
architectures via six different evaluation metrics for model interpretation,
stability and accuracy. Results show that SEAT is more stable against different
perturbations and randomness while also keeps the explainability of attention,
which indicates it is a more faithful explanation. Moreover, compared with
vanilla attention, there is almost no utility (accuracy) degradation for SEAT.Comment: To be appeared in AAAI 202
A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capability
This paper presents the first comprehensive analysis of ChatGPT's Text-to-SQL
ability. Given the recent emergence of large-scale conversational language
model ChatGPT and its impressive capabilities in both conversational abilities
and code generation, we sought to evaluate its Text-to-SQL performance. We
conducted experiments on 12 benchmark datasets with different languages,
settings, or scenarios, and the results demonstrate that ChatGPT has strong
text-to-SQL abilities. Although there is still a gap from the current
state-of-the-art (SOTA) model performance, considering that the experiment was
conducted in a zero-shot scenario, ChatGPT's performance is still impressive.
Notably, in the ADVETA (RPL) scenario, the zero-shot ChatGPT even outperforms
the SOTA model that requires fine-tuning on the Spider dataset by 4.1\%,
demonstrating its potential for use in practical applications. To support
further research in related fields, we have made the data generated by ChatGPT
publicly available at https://github.com/THU-BPM/chatgpt-sql.Comment: 6 pages, 1 figure
Improving Interpretation Faithfulness for Vision Transformers
Vision Transformers (ViTs) have achieved state-of-the-art performance for
various vision tasks. One reason behind the success lies in their ability to
provide plausible innate explanations for the behavior of neural architectures.
However, ViTs suffer from issues with explanation faithfulness, as their focal
points are fragile to adversarial attacks and can be easily changed with even
slight perturbations on the input image. In this paper, we propose a rigorous
approach to mitigate these issues by introducing Faithful ViTs (FViTs). Briefly
speaking, an FViT should have the following two properties: (1) The top-
indices of its self-attention vector should remain mostly unchanged under input
perturbation, indicating stable explanations; (2) The prediction distribution
should be robust to perturbations. To achieve this, we propose a new method
called Denoised Diffusion Smoothing (DDS), which adopts randomized smoothing
and diffusion-based denoising. We theoretically prove that processing ViTs
directly with DDS can turn them into FViTs. We also show that Gaussian noise is
nearly optimal for both and -norm cases. Finally, we
demonstrate the effectiveness of our approach through comprehensive experiments
and evaluations. Results show that FViTs are more robust against adversarial
attacks while maintaining the explainability of attention, indicating higher
faithfulness.Comment: Accepted by ICML 202
Multiple domains are involved in the targeting of the mouse DNA methyltransferase to the DNA replication foci
It has been shown that, during the S-phase of the cell cycle, the mouse DNA methyltransferase (DNA MTase) is targeted to sites of DNA replication by an amino acid sequence (aa 207-455) lying in the N-terminal domain of the enzyme [Leonhardt, H., Page, A. W., Weier, H. U. and Bestor, T. H. (1992) Cell, 71, 865-873]. In this paper it is shown, by using enhanced green fluorescent protein (EGFP) fusions, that other peptide sequences of DNA MTase are also involved in this targeting. The work focuses on a sequence, downstream of the reported targeting sequence (TS), which is homologous to the Polybromo-1 protein. This motif (designated as PBHD) is separated from the reported targeting sequence by a zinc-binding motif [Bestor, T. H. (1992) EMBO J, 11, 2611-2617]. Primed in situ extension using centromeric-specific primers was used to show that both the host DNA MTase and EGFP fusion proteins containing the targeting sequences were localized to centromeric, but not telomeric, regions during late S-phase and mitosis. Also found was that, in ∼10% of the S-phase cells, the EGFP fusions did not co-localize with the centromeric regions. Mutants containing either, or both, of these targeting sequences could act as dominant negative mutants against the host DNA MTase. EGFP fusion proteins, containing the reported TS (aa 207-455), were targeted to centromeric regions throughout the mitotic stage which lead to the discovery of a similar behavior of the endogenous DNA MTase although the host MTase showed much less intense staining than in S-phase cells. The biological role of the centromeric localization of DNA MTase during mitosis is currently unknow
Making the Invisible Visible: Action Recognition Through Walls and Occlusions
Understanding people's actions and interactions typically depends on seeing
them. Automating the process of action recognition from visual data has been
the topic of much research in the computer vision community. But what if it is
too dark, or if the person is occluded or behind a wall? In this paper, we
introduce a neural network model that can detect human actions through walls
and occlusions, and in poor lighting conditions. Our model takes radio
frequency (RF) signals as input, generates 3D human skeletons as an
intermediate representation, and recognizes actions and interactions of
multiple people over time. By translating the input to an intermediate
skeleton-based representation, our model can learn from both vision-based and
RF-based datasets, and allow the two tasks to help each other. We show that our
model achieves comparable accuracy to vision-based action recognition systems
in visible scenarios, yet continues to work accurately when people are not
visible, hence addressing scenarios that are beyond the limit of today's
vision-based action recognition.Comment: ICCV 2019. The first two authors contributed equally to this pape
A Semantic Invariant Robust Watermark for Large Language Models
Watermark algorithms for large language models (LLMs) have achieved extremely
high accuracy in detecting text generated by LLMs. Such algorithms typically
involve adding extra watermark logits to the LLM's logits at each generation
step. However, prior algorithms face a trade-off between attack robustness and
security robustness. This is because the watermark logits for a token are
determined by a certain number of preceding tokens; a small number leads to low
security robustness, while a large number results in insufficient attack
robustness. In this work, we propose a semantic invariant watermarking method
for LLMs that provides both attack robustness and security robustness. The
watermark logits in our work are determined by the semantics of all preceding
tokens. Specifically, we utilize another embedding LLM to generate semantic
embeddings for all preceding tokens, and then these semantic embeddings are
transformed into the watermark logits through our trained watermark model.
Subsequent analyses and experiments demonstrated the attack robustness of our
method in semantically invariant settings: synonym substitution and text
paraphrasing settings. Finally, we also show that our watermark possesses
adequate security robustness. Our code and data are available at
https://github.com/THU-BPM/Robust_Watermark.Comment: 16 pages, 9 figures, 2 table
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