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 $\gamma$ (i.e., the slope of the total mass density profile) to include the effect of the dependence of $\gamma$ on redshift and surface mass density. When treating $\delta$ (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 $\Omega_m$ are quite weak and biased, and also heavily dependent on the lens mass model in the scenarios of parameterizing $\gamma$ with three different forms. When treating $\delta$ as an observable for each lens, the unbiased estimate of $\Omega_m$ can be obtained only in the scenario of including the dependence of $\gamma$ on both the redshift and the surface mass density, that is $\Omega_m = 0.381^{+0.185}_{-0.154}$ at 68\% confidence level in the framework of a flat $\Lambda$CDM model. We conclude that the significant dependencies of $\gamma$ on both the redshift and the surface mass density, as well as the intrinsic scatter of $\delta$ 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 σaper\sigma_{\rm aper} 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 $\sigma_{\rm e}^2$, 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 $\sigma_{\rm e}$ directly, instead providing $\sigma_{\rm aper}$, the second moment of the stellar velocity within a fixed fiber aperture. In this paper, we derive an empirical aperture correction formula, given by $\sigma_{\rm aper}/\sigma_{\rm e}=(R_{\rm aper}/R_{\rm e})^{\alpha}$, 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 $\alpha$ on the $r$-band absolute magnitude $M_{\rm r}$, $g-i$ color, and Sersic index $n_{\rm Ser}$, where $\alpha$ 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 $\alpha$ values for different galaxy types, with parameters in the ranges of $-18>M_{\rm r}>-24$, $0.4<g-i<1.6$, and $0<n_{\rm Ser}<8$. 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 $\sim 5\sigma$ 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 $H_0$, 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