2,840 research outputs found
Risk of cardiovascular disease in Chinese patients with rheumatoid arthritis: a cross sectional study based on hospital medical records in 10 years
Objective: Though the risk of cardiovascular disease (CVD) in rheumatoid arthritis (RA) has been established in Western population, little is known about the risk in Chinese people with RA. Our objective was to estimate the risk of CVD in Chinese people with RA using hospital medical records data.
Methods
The inpatients medical record database 2005‐2015 of Sichuan provincial people’s hospital was examined. All individuals with a primary diagnosis of RA were included as cases, and those of osteoarthritis (OA) were included as controls, which consisted of the unmatched dataset. Then, RA cases and OA controls were matched by sex and age at 1:1 ratio, forming the matched dataset. The morbidity of CVD (including ischemia heart disease (IHD), congestive heart failure (CHF), et al), stroke and arthrosclerosis were extracted from the database, so as the demographic data and comorbidities related to CVD. Multiple logistic regression analysis was used to estimate the risk of CVD in RA adjusted for demographics and comorbidities using the unmatched dataset. Sensitivity analysis was conducted 1) considering interaction terms between RA and comorbidities, and 2) using multivariable conditional logistic regression for the matched dataset.
Results: The unmatched data set comprised of 1824RA cases and 1995 OA controls and the matched dataset comprised of 1022 pairs of sex and age matched RA and OA patients. RA exhibited increased odds of prevalent CVD compared with OA, and the adjusted ORs (95%CIs) for CVD, stroke, IHD, CHF, and atherosclerosis were1.86(1.42‐2.43), 1.11(0.71‐1.74), 1.47(0.97‐2.24), 2.09(1.03‐4.22), and 2.49 (1.97‐3.13), respectively, and was 2.26 (1.29‐3.96) for IHD further adjusted for interaction term. The matched dataset analysis found similar results.
Conclusions: Chinese people with RA were approximated 2 times more 1 likely to have CVD, IHD, CHF and atherosclerosis compared with those with OA. The findings justified the need of further longitudinal study to establish the causal‐relationship between RA and CVD and to estimate the precise risk in this population
Interdisciplinary Fairness in Imbalanced Research Proposal Topic Inference: A Hierarchical Transformer-based Method with Selective Interpolation
The objective of topic inference in research proposals aims to obtain the
most suitable disciplinary division from the discipline system defined by a
funding agency. The agency will subsequently find appropriate peer review
experts from their database based on this division. Automated topic inference
can reduce human errors caused by manual topic filling, bridge the knowledge
gap between funding agencies and project applicants, and improve system
efficiency. Existing methods focus on modeling this as a hierarchical
multi-label classification problem, using generative models to iteratively
infer the most appropriate topic information. However, these methods overlook
the gap in scale between interdisciplinary research proposals and
non-interdisciplinary ones, leading to an unjust phenomenon where the automated
inference system categorizes interdisciplinary proposals as
non-interdisciplinary, causing unfairness during the expert assignment. How can
we address this data imbalance issue under a complex discipline system and
hence resolve this unfairness? In this paper, we implement a topic label
inference system based on a Transformer encoder-decoder architecture.
Furthermore, we utilize interpolation techniques to create a series of
pseudo-interdisciplinary proposals from non-interdisciplinary ones during
training based on non-parametric indicators such as cross-topic probabilities
and topic occurrence probabilities. This approach aims to reduce the bias of
the system during model training. Finally, we conduct extensive experiments on
a real-world dataset to verify the effectiveness of the proposed method. The
experimental results demonstrate that our training strategy can significantly
mitigate the unfairness generated in the topic inference task.Comment: 19 pages, Under review. arXiv admin note: text overlap with
arXiv:2209.1391
Drive Like a Human: Rethinking Autonomous Driving with Large Language Models
In this paper, we explore the potential of using a large language model (LLM)
to understand the driving environment in a human-like manner and analyze its
ability to reason, interpret, and memorize when facing complex scenarios. We
argue that traditional optimization-based and modular autonomous driving (AD)
systems face inherent performance limitations when dealing with long-tail
corner cases. To address this problem, we propose that an ideal AD system
should drive like a human, accumulating experience through continuous driving
and using common sense to solve problems. To achieve this goal, we identify
three key abilities necessary for an AD system: reasoning, interpretation, and
memorization. We demonstrate the feasibility of employing an LLM in driving
scenarios by building a closed-loop system to showcase its comprehension and
environment-interaction abilities. Our extensive experiments show that the LLM
exhibits the impressive ability to reason and solve long-tailed cases,
providing valuable insights for the development of human-like autonomous
driving. The related code are available at
https://github.com/PJLab-ADG/DriveLikeAHuman
Generation of Kerr soliton microcomb in a normally dispersed lithium niobate microdisk resonator by mode trimming
Anomalous microresonator dispersion is mandatory for Kerr soliton microcomb
formation, which depends critically on the geometry of the microresonator and
can hardly be tuned after the structure is made. To date, cavity-based
microcombs have only been generated with fundamental whispering gallery modes
(WGMs) of anomalous dispersion in microresonators. Moreover, microcomb
generation in highly Raman-active platforms such as lithium niobate (LN)
microresonators frequently suffers from stimulated Raman scattering and mode
crossing due to the existence of multiple families of high-order WGMs. Here, we
reveal a unique Kerr soliton microcomb generation mechanism through mode
trimming in a weakly perturbed LN microdisk resonator. Remarkably, the soliton
comb is generated with fundamental WGMs of normal dispersion and free from the
mode crossing and Raman scattering effects. A robust soliton with a spectrum
spanning from 1450 nm to 1620 nm at an on-chip pump power of 35 mW. Our
discovery offers a powerful solution to circumvent the stringent requirements
on high-precision dispersion engineering and termination of Raman excitation
for soliton generation in the high-Q microdisk.Comment: 16 pages,and 5 figure
Search for the Lepton Flavor Violation Process at BESIII
We search for the lepton-flavor-violating decay of the into an
electron and a muon using events
collected with the BESIII detector at the BEPCII collider. Four candidate
events are found in the signal region, consistent with background expectations.
An upper limit on the branching fraction of (90% C.L.) is obtained
First observation of the M1 transition
Using a sample of 106 million \psi(3686) events collected with the BESIII
detector at the BEPCII storage ring, we have made the first measurement of the
M1 transition between the radially excited charmonium S-wave spin-triplet and
the radially excited S-wave spin-singlet states: \psi(3686)\to\gamma\eta_c(2S).
Analyses of the processes \psi(2S)\to \gamma\eta_c(2S) with \eta_c(2S)\to
\K_S^0 K\pi and K^+K^-\pi^0 gave an \eta_c(2S) signal with a statistical
significance of greater than 10 standard deviations under a wide range of
assumptions about the signal and background properties. The data are used to
obtain measurements of the \eta_c(2S) mass (M(\eta_c(2S))=3637.6\pm
2.9_\mathrm{stat}\pm 1.6_\mathrm{sys} MeV/c^2), width
(\Gamma(\eta_c(2S))=16.9\pm 6.4_\mathrm{stat}\pm 4.8_\mathrm{sys} MeV), and the
product branching fraction (\BR(\psi(3686)\to \gamma\eta_c(2S))\times
\BR(\eta_c(2S)\to K\bar K\pi) = (1.30\pm 0.20_\mathrm{stat}\pm
0.30_\mathrm{sys})\times 10^{-5}). Combining our result with a BaBar
measurement of \BR(\eta_c(2S)\to K\bar K \pi), we find the branching fraction
of the M1 transition to be \BR(\psi(3686)\to\gamma\eta_c(2S)) = (6.8\pm
1.1_\mathrm{stat}\pm 4.5_\mathrm{sys})\times 10^{-4}.Comment: 7 pages, 1 figure, 1 tabl
Study of and
The decays and have been
investigated with a sample of 225.2 million events collected with the
BESIII detector at the BEPCII collider. The branching fractions are
determined to be and . Distributions of the angle
between the proton or anti-neutron and the beam direction are well
described by the form , and we find
for and
for . Our branching-fraction
results suggest a large phase angle between the strong and electromagnetic
amplitudes describing the decay.Comment: 16 pages, 13 figures, the 2nd version, submitted to PR
First Observation of the Decays chi_{cJ} -> pi^0 pi^0 pi^0 pi^0
We present a study of the P-wave spin -triplet charmonium chi_{cJ} decays
(J=0,1,2) into pi^0 pi^0 pi^0 pi^0. The analysis is based on 106 million
\psiprime decays recorded with the BESIII detector at the BEPCII electron
positron collider. The decay into the pi^0 pi^0 pi^0 pi^0 hadronic final state
is observed for the first time. We measure the branching fractions B(chi_{c0}
-> pi^0 pi^0 pi^0 pi^0)=(3.34 +- 0.06 +- 0.44)*10^{-3}, B(chi_{c1} -> pi^0 pi^0
pi^0 pi^0)=(0.57 +- 0.03 +- 0.08)*10^{-3}, and B(chi_{c2} -> pi^0 pi^0 pi^0
pi^0)=(1.21 +- 0.05 +- 0.16)*10^{-3}, where the uncertainties are statistical
and systematical, respectively.Comment: 7 pages, 3 figure
Observation of the -Annihilation Decay and Evidence for
We report on the observation of the -annihilation decay and the evidence for with a data sample corresponding to an integrated luminosity of 3.19
fb collected with the BESIII detector at the center-of-mass energy
GeV. We obtain the branching fractions
and , respectively
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