120 research outputs found
An Unsupervised Sampling Approach for Image-Sentence Matching Using Document-Level Structural Information
In this paper, we focus on the problem of unsupervised image-sentence
matching. Existing research explores to utilize document-level structural
information to sample positive and negative instances for model training.
Although the approach achieves positive results, it introduces a sampling bias
and fails to distinguish instances with high semantic similarity. To alleviate
the bias, we propose a new sampling strategy to select additional
intra-document image-sentence pairs as positive or negative samples.
Furthermore, to recognize the complex pattern in intra-document samples, we
propose a Transformer based model to capture fine-grained features and
implicitly construct a graph for each document, where concepts in a document
are introduced to bridge the representation learning of images and sentences in
the context of a document. Experimental results show the effectiveness of our
approach to alleviate the bias and learn well-aligned multimodal
representations.Comment: To be published in AAAI202
Efficacy of Zhifei Kangfu Decoction in the Treatment of Infantile Pneumonia in the Recovery Period
The objective of this article is to explore the effect of applying Zhifei Kangfu Decoction on the treatment effect of patients during the recovery period of children with pneumonia. The method of this research is to take patients who were treated in our hospital from December 2019 to December 2020 as an example to carry out the research work. The researchers selected all patients in the recovery period of pediatric pneumonia, and the number was selected as 100 cases, who were divided into two groups, and the treatment methods used are conventional western medicine and Zhifei Kangfu Decoction treatment, who were named the control group and the experimental group, and the clinical treatment effects of the two groups of patients are compared and analyzed. The effective rate and adverse reaction rate of children in the experimental group were 96.00% and 4.00%, respectively. The effective rate and adverse reaction rate of children in the control group were 82.00% and 30.00%, respectively. Asthma, cough relieving, and treatment time were shorter than those of the control group, and the difference in the data was P<0.05, which was statistically significant. The experimental group had better results. The treatment of children in the recovery period of pneumonia and the application of Zhifei Kangfu Decoction can promote the improvement of clinical efficacy, reduce the incidence of adverse reactions in children, and have a positive significance in promoting the recovery of children
On the Inertia Term of Projectile's Penetration Resistance
The effect of the target inertia term of rigid kinetic energy projectiles (KEP’s) penetration resistance is investigated using nonlinear dynamic code LS-DYNA and four constitutive models. It is found that the damage number of target can be used to measure the influence of the inertia term. The smaller the damage number is, the less influence the inertia term has. The less dependent the resistance has on projectile velocity, the more accurate it is to treat the resistance as a constant. For the ogive-nose projectile with CRH of 3, when the target is aluminum, steel, or other metals, the threshold velocity for the constant resistance is at least 1258 m/s; when the target is concrete, rock, or other brittle materials, if the velocity of the projectile is greater than 400 m/s or so, the damage number would be very large, and the penetration resistance would clearly depend on the projectile’s velocity. The higher the elastic wave velocity is, the more penetration process is affected by the impact face
iBall: Augmenting Basketball Videos with Gaze-moderated Embedded Visualizations
We present iBall, a basketball video-watching system that leverages
gaze-moderated embedded visualizations to facilitate game understanding and
engagement of casual fans. Video broadcasting and online video platforms make
watching basketball games increasingly accessible. Yet, for new or casual fans,
watching basketball videos is often confusing due to their limited basketball
knowledge and the lack of accessible, on-demand information to resolve their
confusion. To assist casual fans in watching basketball videos, we compared the
game-watching behaviors of casual and die-hard fans in a formative study and
developed iBall based on the fndings. iBall embeds visualizations into
basketball videos using a computer vision pipeline, and automatically adapts
the visualizations based on the game context and users' gaze, helping casual
fans appreciate basketball games without being overwhelmed. We confrmed the
usefulness, usability, and engagement of iBall in a study with 16 casual fans,
and further collected feedback from 8 die-hard fans.Comment: ACM CHI2
Keep it Consistent: Topic-Aware Storytelling from an Image Stream via Iterative Multi-agent Communication
Visual storytelling aims to generate a narrative paragraph from a sequence of
images automatically. Existing approaches construct text description
independently for each image and roughly concatenate them as a story, which
leads to the problem of generating semantically incoherent content. In this
paper, we propose a new way for visual storytelling by introducing a topic
description task to detect the global semantic context of an image stream. A
story is then constructed with the guidance of the topic description. In order
to combine the two generation tasks, we propose a multi-agent communication
framework that regards the topic description generator and the story generator
as two agents and learn them simultaneously via iterative updating mechanism.
We validate our approach on VIST dataset, where quantitative results,
ablations, and human evaluation demonstrate our method's good ability in
generating stories with higher quality compared to state-of-the-art methods.Comment: Accepted to COLING 202
Probing the Galactic halo with RR Lyrae stars -- IV. On the Oosterhoff dichotomy of RR Lyrae stars
We use 3653 (2661 RRab, 992 RRc) RR Lyrae stars (RRLs) with 7D (3D position,
3D velocity, and metallicity) information selected from SDSS, LAMOST, and Gaia
EDR3, and divide the sample into two Oosterhoff groups (Oo I and Oo II)
according to their amplitude-period behaviour in the Bailey Diagram. We present
a comparative study of these two groups based on chemistry, kinematics, and
dynamics. We find that Oo I RRLs are relatively more metal rich, with
predominately radially dominated orbits and large eccentricities, while Oo II
RRLs are relatively more metal poor, and have mildly radially dominated orbits.
The Oosterhoff dichotomy of the Milky Way's halo is more apparent for the
inner-halo region than for the outer-halo region. Additionally, we also search
for this phenomenon in the halos of the two largest satellite galaxies, the
Large and Small Magellanic clouds (LMC, SMC), and compare over different bins
in metallicity. We find that the Oosterhoff dichotomy is not immutable, and
varies based on position in the Galaxy and from galaxy-to-galaxy. We conclude
that the Oosterhoff dichotomy is the result of a combination of stellar and
galactic evolution, and that it is much more complex than the dichotomy
originally identified in Galactic globular clusters
Climate change : strategies for mitigation and adaptation
The sustainability of life on Earth is under increasing threat due to humaninduced climate change. This perilous change in the Earth's climate is caused by increases in carbon dioxide and other greenhouse gases in the atmosphere, primarily due to emissions associated with burning fossil fuels. Over the next two to three decades, the effects of climate change, such as heatwaves, wildfires, droughts, storms, and floods, are expected to worsen, posing greater risks to human health and global stability. These trends call for the implementation of mitigation and adaptation strategies. Pollution and environmental degradation exacerbate existing problems and make people and nature more susceptible to the effects of climate change. In this review, we examine the current state of global climate change from different perspectives. We summarize evidence of climate change in Earth’s spheres, discuss emission pathways and drivers of climate change, and analyze the impact of climate change on environmental and human health. We also explore strategies for climate change mitigation and adaptation and highlight key challenges for reversing and adapting to global climate change
Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector
A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements
Precision Higgs physics at the CEPC
The discovery of the Higgs boson with its mass around 125 GeV by the ATLAS
and CMS Collaborations marked the beginning of a new era in high energy
physics. The Higgs boson will be the subject of extensive studies of the
ongoing LHC program. At the same time, lepton collider based Higgs factories
have been proposed as a possible next step beyond the LHC, with its main goal
to precisely measure the properties of the Higgs boson and probe potential new
physics associated with the Higgs boson. The Circular Electron Positron
Collider~(CEPC) is one of such proposed Higgs factories. The CEPC is an
circular collider proposed by and to be hosted in China. Located in a
tunnel of approximately 100~km in circumference, it will operate at a
center-of-mass energy of 240~GeV as the Higgs factory. In this paper, we
present the first estimates on the precision of the Higgs boson property
measurements achievable at the CEPC and discuss implications of these
measurements.Comment: 46 pages, 37 figure
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
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