128 research outputs found
Assessing the effect of lens mass model in cosmological application with updated galaxy-scale strong gravitational lensing sample
By comparing the dynamical and lensing masses of early-type lens galaxies,
one can constrain both the cosmological parameters and the density profiles of
galaxies. We explore the constraining power on cosmological parameters and the
effect of the lens mass model in this method with 161 galaxy-scale strong
lensing systems, which is currently the largest sample with both high
resolution imaging and stellar dynamical data. We assume a power-law mass model
for the lenses, and consider three different parameterizations for
(i.e., the slope of the total mass density profile) to include the effect of
the dependence of on redshift and surface mass density. When treating
(i.e., the slope of the luminosity density profile) as a universal
parameter for all lens galaxies, we find the limits on the cosmological
parameter are quite weak and biased, and also heavily dependent on
the lens mass model in the scenarios of parameterizing with three
different forms. When treating as an observable for each lens, the
unbiased estimate of can be obtained only in the scenario of
including the dependence of on both the redshift and the surface mass
density, that is at 68\% confidence level
in the framework of a flat CDM model. We conclude that the significant
dependencies of on both the redshift and the surface mass density, as
well as the intrinsic scatter of among the lenses, need to be properly
taken into account in this method.Comment: Accepted for publication in MNRAS; 17 pages, 5 figures, 2 table
Trajectories of Dietary Patterns, Sleep Duration, and Body Mass Index in China: A Population-Based Longitudinal Study from China Nutrition and Health Survey, 1991-2009.
No study has used trajectories of dietary patterns to examine their effects on sleep duration and body mass index over time in the Chinese population. We analyzed data from adults participating in the China Health and Nutrition Survey between 1991 and 2009. Dietary intake was measured by a 24-h recall method over three consecutive days. Height and body weight were measured, and sleep duration was self-reported. Multivariable mixed linear models were applied to examine the association between trajectories of dietary patterns (using a latent class model) and sleep duration as well as BMI. Four trajectories of a traditional pattern (characterized by rice, meat, and vegetables) and three trajectories of a modern pattern (characterized by fast food, milk, and deep-fried food) were identified. Participants with a high and rapid increase trajectory of the modern dietary pattern had the shortest sleep duration (β = -0.26; 95% CI: -0.40, -0.13). Participants with a high and stable intake of the traditional dietary pattern had the lowest BMI (β = -1.14; 95% CI: -1.41, -0.87), while the participants with a high and rapid increase trajectory of the modern dietary pattern had the highest BMI (β = 0.74; 95% CI: 0.34, 1,15). A rapid increase in the modern dietary pattern is associated with shorter sleep duration and higher BMI
A Dynamic Additive and Multiplicative Effects Model with Application to the United Nations Voting Behaviors
We introduce a regression model for a series of networks that are correlated
over time. Our model is a dynamic extension of the additive and multiplicative
effects network model (AMEN) of Hoff (2019) In addition to incorporating a
temporal structure, the model accommodates two types of missing data thus
allows the size of the network to vary over time. We demonstrate via
simulations the necessity of various components of the model. We apply the
model to the United Nations General Assembly voting data from 1983 to 2014
(Voeten (2013)) to answer interesting research questions regarding to
international voting behaviors. In addition to finding important factors that
could explain the voting behaviors, the model-estimated additive effects,
multiplicative effects, and their movements reveal meaningful foreign policy
positions and alliances of various countries
Improving immunogenicity and safety of flagellin as vaccine carrier by high-density display on virus-like particle surface
Flagellin is a protein-based adjuvant that activates toll-like receptor (TLR) 5. Flagellin has been actively explored as vaccine adjuvants and carriers. Preclinical and clinical studies find flagellin-based vaccines have a risk to induce systemic adverse reactions potentially due to its overt activation of TLR5. To improve safety and immunogenicity of flagellin as vaccine carriers, FljB was displayed at high densities on hepatitis b core (HBc) virus-like particle (VLP) surface upon c/e1 loop insertion. FljB-HBc (FH) VLPs showed significantly reduced ability to activate TLR5 or induce systemic interleukin-6 release as compared to FljB. FH VLPs also failed to significantly increase rectal temperature of mice, while FljB could significantly increase rectal temperature of mice. These data indicated systemic safety of FljB could be significantly improved by high-density display on HBc VLP surface. Besides improved safety, FH VLPs and FljB similarly boosted co-administered ovalbumin immunization and FH VLPs were found to induce two-fold higher anti-FljB antibody titer than FljB. These data indicated preserved adjuvant potency and improved immunogenicity after high-density display of FljB on HBc VLP surface. Consistent with the high immunogenicity, FH VLPs were found to be more efficiently taken up by bone marrow-derived dendritic cells and stimulate more potent dendritic cell maturation than FljB. Lastly, FH VLPs were found to be a more immunogenic carrier than FljB, HBc VLPs, or the widely used keyhole limpet hemocyanin for nicotine vaccine development with a good local and systemic safety. Our data support FH VLPs to be a potentially safer and more immunogenic carrier than FljB for vaccine development
Velocity Dispersion Aperture Corrections as a Function of Galaxy Properties from Integral-field Stellar Kinematics of 10,000 MaNGA Galaxies
The second moment of the stellar velocity within the effective radius,
denoted by , is a crucial quantity in galaxy studies as it
provides insight into galaxy properties and their mass distributions. However,
large spectroscopic surveys typically do not measure directly,
instead providing , the second moment of the stellar
velocity within a fixed fiber aperture. In this paper, we derive an empirical
aperture correction formula, given by , using spatially resolved stellar kinematics
extracted from approximately 10,000 Sloan Digital Sky Survey-Mapping Nearby
Galaxies at Apache Point Observatory (SDSS-MaNGA) integral field unit
observations. Our analysis reveals a strong dependence of on the
-band absolute magnitude , color, and Sersic index , where values are lower for brighter, redder galaxies with
higher Sersic indices. Our results demonstrate that the aperture correction
derived from previous literature on early-type galaxies cannot be applied to
predict the aperture corrections for galaxies with intermediate Sersic indices.
We provide a lookup table of values for different galaxy types, with
parameters in the ranges of , , and . A Python script is provided to obtain the correction factors from the
lookup table.Comment: 12 pages, 10 figures, 1 table, published in Research in Astronomy and
Astrophysic
Discovering strongly lensed quasar candidates with catalogue-based methods from DESI Legacy Surveys
The Hubble tension, revealed by a discrepancy between
measurements of the Hubble-Lemaitre constant from early- and local-Universe
observations, is one of the most significant problems in modern cosmology. In
order to better understand the origin of this mismatch, independent techniques
to measure , such as strong lensing time delays, are required. Notably,
the sample size of such systems is key to minimising statistical uncertainties
and cosmic variance, which can be improved by exploring the datasets of
large-scale sky surveys like DESI (Dark Energy Spectroscopic Instrument). We
identify possible strong lensing time-delay systems within DESI by selecting
candidate multiply imaged lensed quasars from a catalogue of 24,440,816
candidate QSOs contained in the 9th data release of the DESI Legacy Imaging
Surveys (DESI-LS). Using a friend-of-friends-like algorithm on spatial
co-ordinates, our method generates an initial list of compact quasar groups.
This list is subsequently filtered using a measure of the similarity of colours
of a group's members and the likelihood that they are quasars. A visual
inspection finally selects candidate strong lensing systems based on the
spatial configuration of the group members. We identify 620 new candidate
multiply imaged lensed quasars (101 Grade-A, 214 Grade-B, 305 Grade-C). This
number excludes 53 known spectroscopically confirmed systems and existing
candidate systems identified in other similar catalogues. When available, these
new candidates will be further checked by combining the spectroscopic and
photometric data from DESI. The catalogues and images of the candidates in this
work are available online
(https://github.com/EigenHermit/lensed_qso_cand_catalogue_He-22/).Comment: Accepted by A&A. 14 pages, 11 figures. Comments are welcom
Adversarial Robust Memory-Based Continual Learner
Despite the remarkable advances that have been made in continual learning,
the adversarial vulnerability of such methods has not been fully discussed. We
delve into the adversarial robustness of memory-based continual learning
algorithms and observe limited robustness improvement by directly applying
adversarial training techniques. Preliminary studies reveal the twin challenges
for building adversarial robust continual learners: accelerated forgetting in
continual learning and gradient obfuscation in adversarial robustness. In this
study, we put forward a novel adversarial robust memory-based continual learner
that adjusts data logits to mitigate the forgetting of pasts caused by
adversarial samples. Furthermore, we devise a gradient-based data selection
mechanism to overcome the gradient obfuscation caused by limited stored data.
The proposed approach can widely integrate with existing memory-based continual
learning as well as adversarial training algorithms in a plug-and-play way.
Extensive experiments on Split-CIFAR10/100 and Split-Tiny-ImageNet demonstrate
the effectiveness of our approach, achieving up to 8.13% higher accuracy for
adversarial data
Topology-Preserving Adversarial Training
Despite the effectiveness in improving the robustness of neural networks,
adversarial training has suffered from the natural accuracy degradation
problem, i.e., accuracy on natural samples has reduced significantly. In this
study, we reveal that natural accuracy degradation is highly related to the
disruption of the natural sample topology in the representation space by
quantitative and qualitative experiments. Based on this observation, we propose
Topology-pReserving Adversarial traINing (TRAIN) to alleviate the problem by
preserving the topology structure of natural samples from a standard model
trained only on natural samples during adversarial training. As an additional
regularization, our method can easily be combined with various popular
adversarial training algorithms in a plug-and-play manner, taking advantage of
both sides. Extensive experiments on CIFAR-10, CIFAR-100, and Tiny ImageNet
show that our proposed method achieves consistent and significant improvements
over various strong baselines in most cases. Specifically, without additional
data, our proposed method achieves up to 8.78% improvement in natural accuracy
and 4.50% improvement in robust accuracy
Both Short and Long Sleep Durations Are Associated with Poor Cognition and Memory in Chinese Adults Aged 55+ Years-Results from China Health and Nutrition Survey.
We aimed to examine the associations between sleep duration and cognitive functions and memory in older Chinese adults attending the China Health and Nutrition Survey. A total of 7924 participants 55 years and older who reported their sleep duration and had a cognitive screen test in 2004, 2006, and 2015 were included in the analysis. Mixed-effects logistic regression models were used to assess the associations. A short sleep duration (≤6 h/day) and long sleep duration (≥10 h/day) were positively associated with a low global cognitive score (odds ratio-OR: 1.23, 95% CI: 1.01-1.50; OR: 1.47, 95% CI: 1.17-1.79, respectively). Both short sleepers and long sleepers had an increased risk of self-reported poor memory (OR: 1.63, 95% CI: 1.39-1.91; OR: 1.48, 95% CI: 1.25-1.74, respectively). No differences in the above associations were found for income, education, and urbanity. In conclusion, both the short and long sleep duration were associated with declined cognition and memory. Maintaining a normal sleep duration may aid in the prevention of cognitive function decline in older adults
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