I3DOL: Incremental 3D Object Learning without Catastrophic Forgetting

3D object classification has attracted appealing attentions in academic researches and industrial applications. However, most existing methods need to access the training data of past 3D object classes when facing the common real-world scenario: new classes of 3D objects arrive in a sequence. Moreover, the performance of advanced approaches degrades dramatically for past learned classes (i.e., catastrophic forgetting), due to the irregular and redundant geometric structures of 3D point cloud data. To address these challenges, we propose a new Incremental 3D Object Learning (i.e., I3DOL) model, which is the first exploration to learn new classes of 3D object continually. Specifically, an adaptive-geometric centroid module is designed to construct discriminative local geometric structures, which can better characterize the irregular point cloud representation for 3D object. Afterwards, to prevent the catastrophic forgetting brought by redundant geometric information, a geometric-aware attention mechanism is developed to quantify the contributions of local geometric structures, and explore unique 3D geometric characteristics with high contributions for classes incremental learning. Meanwhile, a score fairness compensation strategy is proposed to further alleviate the catastrophic forgetting caused by unbalanced data between past and new classes of 3D object, by compensating biased prediction for new classes in the validation phase. Experiments on 3D representative datasets validate the superiority of our I3DOL framework.Comment: Accepted by Association for the Advancement of Artificial Intelligence 2021 (AAAI 2021

Resonant Inelastic X-ray Scattering from Electronic Excitations in α\alpha-RuCl3_3 Nanolayers

We present Ru $L_3$-edge resonant inelastic x-ray scattering (RIXS) measurements of spin-orbit and d-d excitations in exfoliated nanolayers of the Kitaev spin-liquid candidate RuCl$_3$. Whereas the spin-orbit excitations are independent of thickness, we observe a pronounced red-shift and broadening of the d-d excitations in layers with thickness below $\sim$7 nm. Aided by model calculations, we attribute these effects to distortions of the RuCl$_6$ octahedra near the surface. Our study paves the way towards RIXS investigations of electronic excitations in various other 2D materials and heterostructures

Reduced Energy Metabolism Impairs T Cell-Dependent B Cell Responses in Patients With Advanced HBV-Related Cirrhosis

Background and AimsPatients with decompensated HBV-related liver cirrhosis (HBV D-LC) showed compromised immune responses, which manifested as a proneness to develop infections and hyporesponsiveness to vaccines, resulting in accelerated disease progression. The alterations in T cell-dependent B cell responses in this pathophysiological process were not well understood. This study aimed to investigate T cell-dependent B cell responses in this process and discuss the mechanism from the perspective of metabolism.MethodsChanges in phenotypes and subsets of peripheral B cells between HBV D-LC patients and healthy controls (HCs) were compared by flow cytometry. Isolated B cells were activated by coculture with circulating T follicular (cTfh) cells. After coculture, the frequencies of plasmablasts and plasma cells and immunoglobin levels were analyzed. Oxidative phosphorylation (OXPHOS) and glycolysis were analyzed by a Seahorse analyzer. Mitochondrial function and the AKT/mTOR pathway were analyzed by flow cytometry.ResultsThe proliferation and differentiation capacities of B cells after T cell stimulation were impaired in D-LC. Furthermore, we found that B cells from D-LC patients showed reductions in OXPHOS and glycolysis after activation, which may result from reduced glucose uptake, mitochondrial dysfunction and attenuated activation of the AKT/mTOR pathway.ConclusionsB cells from HBV D-LC patients showed dysfunctional energy metabolism after T cell-dependent activation. Understanding the regulations of B cell metabolic pathway and their changes may provide a new direction to rescue B cell hyporesponsiveness in patients with HBV D-LC, preventing these patients be infected and improving sensitivity to vaccines

Xcr1+ type 1 conventional dendritic cells are essential mediators for atherosclerosis progression

Atherosclerosis is characterized by lipid accumulation within plaques, leading to foam cell formation and an inflammatory response within the aortic lesions. Lipid disorders have been extensively investigated, however, the cellular and molecular mechanisms that trigger the inflammatory response in atherosclerotic plaques remain far from being fully understood. Xcr1+ cDC1 cells are newly identified antigen-presenting cells in activating immune cells. However, the role of cDC1 cells in atherosclerosis development remains highly controversial. We first confirmed the presence of cDC1 within human atherosclerotic plaques and discovered a significant association between the increasing cDC1 numbers and atherosclerosis progression in mice. Subsequently, we established Xcr1Cre-Gfp Rosa26LSL-DTA Apoe–/– mice, a novel and complex genetic model, in which cDC1 was constitutively depleted in vivo during atherosclerosis development. Intriguingly, we observed a notable reduction in atherosclerotic lesions in hyperlipidemic mice, alongside suppressed T cell activation of both CD4+ and CD8+ subsets in the aortic plaques. Notably, aortic macrophages and serum lipid levels were not significantly changed in the cDC1-depleted mice. Single-cell RNA sequencing revealed heterogeneity of Xcr1+ cDC1 cells across the aorta and lymphoid organs under hyperlipidemic conditions. As Xcr1 is the sole receptor for Xcl1, we next explored to target Xcr1+ cDC1 cells via Xcl1 by establishing Xcl1–/–Apoe–/– mice. Xcl1–/–Apoe–/– mice exhibited decreased atherosclerotic plaque formation and reduced aortic cDC1 accumulation, indicating that Xcl1 contributes to cDC1-mediated atherosclerotic lesion development. Our results reveal crucial roles of cDC1 in atherosclerosis progression and provide insights into the development of immunotherapies by targeting cDC1 through Xcl1

A study on the strategies of Park City construction of Chengdu from the perspective of urban heat island mitigation

In the process of urbanization, various urban problems have become increasingly prominent, and the heat island effect is one of them. The expansion of urban land, the increase in construction intensity and the increase in population make the urban heat island effect even worse. The construction of park cities improves the ecological environment of the city and is considered to have a positive effect on alleviating the heat island effect, but it is not clear whether it has such an effect or not. This article explores whether the construction of Park City can help to improve the urban thermal environment effectively, and also, seek solutions for how to improve the construction of park cities so that the heat island effect can be better mitigated. Landsat8 remote sensing images in 2014 and 2019 were used to estimate the fractional vegetation cover (FVC) and land surface temperature (LST) in the Third Ring Road of Chengdu. Land use data were also introduced into the study to analyze LST changes in different surfaces and FVC.The results indicate that: (1) the area of the heat island zone in the Third Ring Road of Chengdu decreased by 0.91% from 2014 to 2019, and the area of the cold island zone increased by 17.89% ; (2) the urban blue-green space is conductive to mitigating the urban heat island effect, in which the water provides the best mitigation, while impervious surface and bare land may aggravate the urban heat island effect; (3) the FVC in the area of the Third Ring Road in Chengdu is on the rise as a whole, and there is a significant negative correlation between FVC and LST (p < 0.01). Based on the above results, this paper shows that Park City construction is beneficial to alleviate the urban heat island effect, and more attention should be paid to blue-green space layout and quality, along with urban ventilation and FVC control. Our results provide useful input for green space planning and the construction of Park City in the future

Gene-Environment Interplay Beyond Interactions: Psychosocial Environments Mediate Genetic Effects Underlying Externalizing Behavior Trajectories

This repository stores supplemental materials associated with the preprint under the same name

Gene-Environment Interplay Beyond Interactions: Psychosocial Environments Mediate Genetic Effects Underlying Externalizing Behavior Trajectories

This repository stores supplemental materials associated with the preprint under the same name

Polygenic Risk-Environment Interactions Underlying Developmental Trajectories of Externalizing Behaviors Across the Lifespan

From a recent genome-wide association study conducted on externalizing behaviors (EXT), polygenic scores (PGSEXT) were found to explain up to 10% of the variance in EXT across various populations (Karlsson-Linnér et al 2021). However, it is unclear how polygenic influences vary across family, school, or peer environments. Additionally, EXT are not static, as their expression may vary over the course of development. As heritability is relatively higher for chronic and early-onset EXT (Isen et al 2022), we test the possibility that polygenic-environment interactions may specifically underlie development of these persistent forms of EXT, rather than forms that are more developmentally time-limited. Using five-wave data from the National Longitudinal Study of Adolescent to Adult Health (n=9,974), the current study explores the association between PGSEXT and developmental trajectories of EXT from age 13 to 41 using growth mixture modeling. EXT will reflect substance use (e.g., alcohol, tobacco, and marijuana use) and antisocial behaviors (e.g., theft, aggression, property destruction). We will examine whether PGSEXT associations on latent class trajectories of EXT will be moderated by aspects of early-adolescent environment (i.e., parental warmth, deviant peer affiliation, and school connectedness)

A Longitudinal Analysis of Gene x Environment Interaction on Verbal Intelligence Across Adolescence and Early Adulthood

The goal of our study is to replicate the Scarr-Rowe effect in the Wave III Add Health data and to investigate whether additional socioeconomic status indicators like school quality and annual income also moderate the heritability of intelligence. We will apply the Behavioral Genetic Model and the Modified Twin Correlation Model to Add Health sibling data through the Mplus software

Gene-Environment Correlations: A Within-Family Analysis Using Polygenic Scores

Polygenic scores (PGS) for externalizing (EXT) behaviors have been shown to associate with not only EXT outcomes but also various environmental variables, such as parental relationship and peer affiliation. The current study aims to investigate this phenomenon, commonly referred to as gene-environment correlation (rGE), using a genetically-informed quasi-causal design. Leveraging a sample of adolescent twins and siblings living in the same household in the National Longitudinal Study of Adolescent to Adult, we will fit multilevel structural equation models to control for confounds (e.g., population stratification, parental genotype, etc.) and estimate the effect of PGS on adolescent social environments within-family as they pertain to the development of EXT behaviors. Furthermore, we assess the support for a gene-environment cascade model, where PGS indirectly influences the social environments via EXT behaviors in adolescence, thereby indirectly influencing the development of EXT into adulthood via those social environments. Results from this study will potentially facilitate our understanding of how genes and the environment interact and also inform targets of psychosocial intervention