104 research outputs found
Protective effect of salvianolic acid B against intestinal ischemia reperfusion-induced injury in a rat model
Purpose: To evaluate the gastro-protective efficacy of salvianolic acid B (SAB) against intestinal ischemic-reperfusion injury (IIRI) in a rat model.Methods: Forty-eight healthy male rats were randomly choosen and divided into 4 groups of 12 rats each. Control group rats underwent laparotomy without occlusion; IIRI group rats underwent laparotomy with occlusion for 60 min, followed by 24 h of reperfusion; SAB + IIRI group received 7 days of pretreatment with 40 mg/kg of SAB + IIRI; while the fourth group received only SAB. The antioxidant, inflammatory markers, intestinal permeability marker, as well as intestinal histopathological changes were assessed.Results: The activities of antioxidants including reduced glutathione (GSH), catalase (CAT) and superoxide dismutase (SOD) were significantly ameliorated (p < 0.01) in SAB-supplemented group (SAB + IIRI). The concentration of inflammatory markers, including interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α) and nuclear factor p65 (NF-p65) as well as small intestinal permeability marker (FITC-Dextran), were significantly reduced (p < 0.01) following administration of SAB for 7 days. In addition, pretreatment with SAB reverted intestinal (ileum) histopathological changes to almost normal architecture with significant reduction in Chiu score.Conclusion: The results of this study demonstrate that SAB may protect the intestine by attenuating oxidative stress and inflammatory response and hence, may be potentially for treating IIRI.Keywords: Salvianolic acid B, Intestinal Ischemia-reperfusion, Antioxidants, Inflammation, Intestinal permeabilit
Fast Exact NPN Classification with Influence-aided Canonical Form
NPN classification has many applications in the synthesis and verification of
digital circuits. The canonical-form-based method is the most common approach,
designing a canonical form as representative for the NPN equivalence class
first and then computing the transformation function according to the canonical
form. Most works use variable symmetries and several signatures, mainly based
on the cofactor, to simplify the canonical form construction and computation.
This paper describes a novel canonical form and its computation algorithm by
introducing Boolean influence to NPN classification, which is a basic concept
in analysis of Boolean functions. We show that influence is
input-negation-independent, input-permutation-dependent, and has other
structural information than previous signatures for NPN classification.
Therefore, it is a significant ingredient in speeding up NPN classification.
Experimental results prove that influence plays an important role in reducing
the transformation enumeration in computing the canonical form. Compared with
the state-of-the-art algorithm implemented in ABC, our influence-aided
canonical form for exact NPN classification gains up to 5.5x speedup.Comment: To be appeared in ICCAD'2
Model-Free Large-Scale Cloth Spreading With Mobile Manipulation: Initial Feasibility Study
Cloth manipulation is common in domestic and service tasks, and most studies
use fixed-base manipulators to manipulate objects whose sizes are relatively
small with respect to the manipulators' workspace, such as towels, shirts, and
rags. In contrast, manipulation of large-scale cloth, such as bed making and
tablecloth spreading, poses additional challenges of reachability and
manipulation control. To address them, this paper presents a novel framework to
spread large-scale cloth, with a single-arm mobile manipulator that can solve
the reachability issue, for an initial feasibility study. On the manipulation
control side, without modeling highly deformable cloth, a vision-based
manipulation control scheme is applied and based on an online-update Jacobian
matrix mapping from selected feature points to the end-effector motion. To
coordinate the control of the manipulator and mobile platform, Behavior Trees
(BTs) are used because of their modularity. Finally, experiments are conducted,
including validation of the model-free manipulation control for cloth spreading
in different conditions and the large-scale cloth spreading framework. The
experimental results demonstrate the large-scale cloth spreading task
feasibility with a single-arm mobile manipulator and the model-free deformation
controller.Comment: 6 pages, 6 figures, submit to CASE202
Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning
Advances in deep learning have greatly improved structure prediction of
molecules. However, many macroscopic observations that are important for
real-world applications are not functions of a single molecular structure, but
rather determined from the equilibrium distribution of structures. Traditional
methods for obtaining these distributions, such as molecular dynamics
simulation, are computationally expensive and often intractable. In this paper,
we introduce a novel deep learning framework, called Distributional Graphormer
(DiG), in an attempt to predict the equilibrium distribution of molecular
systems. Inspired by the annealing process in thermodynamics, DiG employs deep
neural networks to transform a simple distribution towards the equilibrium
distribution, conditioned on a descriptor of a molecular system, such as a
chemical graph or a protein sequence. This framework enables efficient
generation of diverse conformations and provides estimations of state
densities. We demonstrate the performance of DiG on several molecular tasks,
including protein conformation sampling, ligand structure sampling,
catalyst-adsorbate sampling, and property-guided structure generation. DiG
presents a significant advancement in methodology for statistically
understanding molecular systems, opening up new research opportunities in
molecular science.Comment: 80 pages, 11 figure
Impact of Examined Lymph Node Count on Precise Staging and Long-Term Survival of Resected Non-Small-Cell Lung Cancer:A Population Study of the US SEER Database and a Chinese Multi-Institutional Registry
The north–south shift of the ridge location of the western Pacific subtropical high and its influence on the July precipitation in the Jianghuai region from 1978 to 2021
The Jianghuai region is the area between the Yangtze River and the Huai River in China and is a densely populated agriculture region therefore, the economics and human activity there are significantly affected by the precipitation changes, particularly during the summer when extreme storms and droughts normally occur. It will be helpful if the summer precipitation changes can be predicted. The monthly ERA5 atmospheric reanalysis data from 1978 to 2021 are used in this study to investigate the relationship between the ridge latitudinal location of the western Pacific subtropical high (WPSH) and the precipitation in July over the Jianghuai region. The results show that the WPSH ridge location has an important impact on the amount and spatial distribution of the precipitation in this region. When the ridge was northward, an anomalous anticyclonic circulation will appear over the western Pacific, leading to the weakening of the summer monsoon and the reduction of moisture transport from the Indian Ocean, therefore decreasing precipitation in the Jianghuai region, while the situation is opposite when the ridge was southward. The Niño 3.4 index in March and the India–Burma trough intensity index in June have significant correlations with the July WPSH ridge location, and both can be used as precursors to predict the WPSH ridge location and, therefore, the precipitation in this region
The DESI One-Percent Survey: Exploring the Halo Occupation Distribution of Luminous Red Galaxies and Quasi-Stellar Objects with AbacusSummit
We present the first comprehensive Halo Occupation Distribution (HOD)
analysis of the DESI One-Percent survey Luminous Red Galaxy (LRG) and
Quasi-Stellar Object (QSO) samples. We constrain the HOD of each sample and
test possible HOD extensions by fitting the redshift-space galaxy 2-point
correlation functions in 0.15 < r < 32 Mpc/h in a set of fiducial redshift
bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model
templates and forward model galaxy clustering with the AbacusHOD package. We
achieve good fits with a standard HOD model with velocity bias, and we find no
evidence for galaxy assembly bias or satellite profile modulation at the
current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a
satellite fraction of fsat = 11+-1%, a mean halo mass of log10 Mh =
13.40+0.02-0.02, and a linear bias of blin = 1.93+0.06-0.04. For LRGs in 0.6 <
z < 0.8, we find fsat = 14+-1%, log10 Mh = 13.24+0.02-0.02, and blin =
2.08+0.03-0.03. For QSOs, we infer fsat = 3+8-2%, log10 Mh = 12.65+0.09-0.04,
and blin = 2.63+0.37-0.26 in redshift range 0.8 < z < 2.1. Using these fits, we
generate a large suite of high-fidelity galaxy mocks. We also study the
redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealing
significant and interesting trends in mean halo mass, linear bias, and
satellite fraction.Comment: Submitted to MNRAS, comments welcom
The DESI One-Percent survey: constructing galaxy-halo connections for ELGs and LRGs using auto and cross correlations
In the current Dark Energy Spectroscopic Instrument (DESI) survey, emission
line galaxies (ELGs) and luminous red galaxies (LRGs) are essential for mapping
the dark matter distribution at . We measure the auto and cross
correlation functions of ELGs and LRGs at from the DESI
One-Percent survey. Following Gao et al. (2022), we construct the galaxy-halo
connections for ELGs and LRGs simultaneously. With the stellar-halo mass
relation (SHMR) for the whole galaxy population (i.e. normal galaxies), LRGs
can be selected directly by stellar mass, while ELGs can also be selected
randomly based on the observed number density of each stellar mass, once the
probability of a satellite galaxy becoming an ELG is
determined. We demonstrate that the observed small scale clustering prefers a
halo mass-dependent model rather than a constant. With this
model, we can well reproduce the auto correlations of LRGs and the cross
correlations between LRGs and ELGs at
. We can also reproduce the auto correlations of ELGs at
( ) in
real (redshift) space. Although our model has only seven parameters, we show
that it can be extended to higher redshifts and reproduces the observed auto
correlations of ELGs in the whole range of , which enables us to
generate a lightcone ELG mock for DESI. With the above model, we further derive
halo occupation distributions (HODs) for ELGs which can be used to produce ELG
mocks in coarse simulations without resolving subhalos.Comment: 27 pages, 16 figures, accepted by Ap
Persistent sulfate formation from London Fog to Chinese haze
Sulfate aerosols exert profound impacts on human and ecosystem health, weather, and climate, but their formation mechanism remains uncertain. Atmospheric models consistently underpredict sulfate levels under diverse environmental conditions. From atmospheric measurements in two Chinese megacities and complementary laboratory experiments, we show that the aqueous oxidation of SO2 by NO2 is key to efficient sulfate formation but is only feasible under two atmospheric conditions: on fine aerosols with high relative humidity and NH3 neutralization or under cloud conditions. Under polluted environments, this SO2 oxidation process leads to large sulfate production rates and promotes formation of nitrate and organic matter on aqueous particles, exacerbating severe haze development. Effective haze mitigation is achievable by intervening in the sulfate formation process with enforced NH3 and NO2 control measures. In addition to explaining the polluted episodes currently occurring in China and during the 1952 London Fog, this sulfate production mechanism is widespread, and our results suggest a way to tackle this growing problem in China and much of the developing world
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