On Azadkia-Chatterjee's conditional dependence coefficient

In recent work, Azadkia and Chatterjee (2021) laid out an ingenious approach to defining consistent measures of conditional dependence. Their fully nonparametric approach forms statistics based on ranks and nearest neighbor graphs. The appealing nonparametric consistency of the resulting conditional dependence measure and the associated empirical conditional dependence coefficient has quickly prompted follow-up work that seeks to study its statistical efficiency. In this paper, we take up the framework of conditional randomization tests (CRT) for conditional independence and conduct a power analysis that considers two types of local alternatives, namely, parametric quadratic mean differentiable alternatives and nonparametric H\"older smooth alternatives. Our local power analysis shows that conditional independence tests using the Azadkia--Chatterjee coefficient remain inefficient even when aided with the CRT framework, and serves as motivation to develop variants of the approach; cf. Lin and Han (2022b). As a byproduct, we resolve a conjecture of Azadkia and Chatterjee by proving central limit theorems for the considered conditional dependence coefficients, with explicit formulas for the asymptotic variances.Comment: to appear in Bernoull

SMatStack to enhance noisy teleseismic seismic phases: validation and application to resolving depths of oceanic transform earthquakes

The depths of most moderate‐sized oceanic earthquakes are poorly constrained because of the lack of local recording stations and noisy teleseismic recordings. This hampers our understanding of slip behaviors along oceanic faults and the mechanical properties of the oceanic lithosphere. In this study, we develop a new method to enhance the weak body‐wave signals, particularly the depth phases, associated with earthquakes on oceanic transform faults using large‐aperture arrays in the teleseismic range. We simulate the enhanced teleseismic signals to refine the centroid depths of moderate‐sized earthquakes. We validate the new approach using synthetic waveforms and show it outperforms conventional methods when dealing with noisy signals. We obtain the depth estimates for three moderate‐sized earthquakes on the Chain transform fault in the equatorial Atlantic Ocean and find two of them are consistent with a local catalog derived using oceanic bottom seismometers. Application of the new method to the past decades of teleseismic recordings of moderate‐sized earthquakes on the large and slow‐slipping transform faults will provide significantly improved constraints on the width of the seismogenic zone, thus advancing our understanding of the rheology of oceanic lithosphere and earthquake processes in oceanic settings and, by comparison, their more dangerous continental counterparts. The new method is not limited to oceanic transform earthquakes, but can be easily adapted to other seismological studies in which noisy but coherent signals could be revisited for better usage.https://doi.org/10.1029/2023GC011109Published versio

Comparative phylogeography of the plateau zokor (Eospalax baileyi) and its host-associated flea (Neopsylla paranoma) in the Qinghai-Tibet Plateau

Background: Specific host-parasite systems often embody a particular co-distribution phenomenon, in which the parasite’s phylogeographic pattern is dependent on its host. In practice, however, both congruent and incongruent phylogeographic patterns between the host and the parasite have been reported. Here, we compared the population genetics of the plateau zokor (Eospalax baileyi), a subterranean rodent, and its host-associated flea species, Neopsylla paranoma, with an aim to determine whether the two animals share a similar phylogeographic pattern. Results: We sampled 130 host-parasite pairs from 17 localities in the Qinghai-Tibet Plateau (QTP), China, and sequenced a mitochondrial DNA (mtDNA) segment (~2,500 bp), including the complete COI and COII genes. We also detected 55 zokor and 75 flea haplotypes. AMOVA showed that the percentage of variation among the populations of zokors constituted 97.10%, while the within population variation was only 2.90%; for fleas, the values were 85.68% and 14.32%, respectively. Moreover, the flea Fst (fixation index) values were significantly smaller than in zokor. Although the Fst values between zokors and fleas were significantly and positively correlated (N =105, R =0.439, p =0.000), only a small amount (R2= 0.19) of the flea Fst variations could be explained by the zokor Fst variations. The two animals showed very distinct haplotype network structures from each other while co-phylogenetic analyses were unable to reject the hypothesis of an independence of speciation events. Conclusions: Zokors and fleas have very distinct population genetic patterns from each other, likely due to the influence of other sympatrically-distributed vertebrates on the transmission of fleas

Brain-inspired Graph Spiking Neural Networks for Commonsense Knowledge Representation and Reasoning

How neural networks in the human brain represent commonsense knowledge, and complete related reasoning tasks is an important research topic in neuroscience, cognitive science, psychology, and artificial intelligence. Although the traditional artificial neural network using fixed-length vectors to represent symbols has gained good performance in some specific tasks, it is still a black box that lacks interpretability, far from how humans perceive the world. Inspired by the grandmother-cell hypothesis in neuroscience, this work investigates how population encoding and spiking timing-dependent plasticity (STDP) mechanisms can be integrated into the learning of spiking neural networks, and how a population of neurons can represent a symbol via guiding the completion of sequential firing between different neuron populations. The neuron populations of different communities together constitute the entire commonsense knowledge graph, forming a giant graph spiking neural network. Moreover, we introduced the Reward-modulated spiking timing-dependent plasticity (R-STDP) mechanism to simulate the biological reinforcement learning process and completed the related reasoning tasks accordingly, achieving comparable accuracy and faster convergence speed than the graph convolutional artificial neural networks. For the fields of neuroscience and cognitive science, the work in this paper provided the foundation of computational modeling for further exploration of the way the human brain represents commonsense knowledge. For the field of artificial intelligence, this paper indicated the exploration direction for realizing a more robust and interpretable neural network by constructing a commonsense knowledge representation and reasoning spiking neural networks with solid biological plausibility

DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph

Unsupervised representation learning for dynamic graphs has attracted a lot of research attention in recent years. Compared with static graph, the dynamic graph is a comprehensive embodiment of both the intrinsic stable characteristics of nodes and the time-related dynamic preference. However, existing methods generally mix these two types of information into a single representation space, which may lead to poor explanation, less robustness, and a limited ability when applied to different downstream tasks. To solve the above problems, in this paper, we propose a novel disenTangled representation learning framework for discrete-time Dynamic graphs, namely DyTed. We specially design a temporal-clips contrastive learning task together with a structure contrastive learning to effectively identify the time-invariant and time-varying representations respectively. To further enhance the disentanglement of these two types of representation, we propose a disentanglement-aware discriminator under an adversarial learning framework from the perspective of information theory. Extensive experiments on Tencent and five commonly used public datasets demonstrate that DyTed, as a general framework that can be applied to existing methods, achieves state-of-the-art performance on various downstream tasks, as well as be more robust against noise

Career-Specific Parenting Practices and Career Decision-Making Self-Efficacy Among Chinese Adolescents: The Interactive Effects of Parenting Practices and the Mediating Role of Autonomy

This study examined the unique and interactive effects of various career-specific parenting practices (i.e., parental career support, interference, and lack of engagement) on Chinese high school students’ career decision-making self-efficacy (CDSE) as well as the mediating role of autonomy in such associations. Based on data from 641 Chinese high school students (47.6% male; mean age = 15.28 years old, SD = 0.49) in 2016, two moderated mediating effects were identified. Higher level of parental career engagement strengthened the positive association between parental career support and adolescents’ autonomy, which in turn, was associated positively with adolescents’ CDSE. Parental career interference related negatively with adolescents’ CDSE via autonomy when lack of parental career engagement was low, but related positively with adolescents’ CDSE via autonomy when lack of parental career engagement was high. These findings advance our understanding of the underlying processes between career-specific parenting practices and adolescents’ CDSE. Implications for practices were discussed

Fine-tuning of microglia polarization prevents diabetes-associated cerebral atherosclerosis

Diabetes increases the occurrence and severity of atherosclerosis. When plaques form in brain vessels, cerebral atherosclerosis causes thickness, rigidity, and unstableness of cerebral artery walls, leading to severe complications like stroke and contributing to cognitive impairment. So far, the molecular mechanism underlying cerebral atherosclerosis is not determined. Moreover, effective intervention strategies are lacking. In this study, we showed that polarization of microglia, the resident macrophage in the central nervous system, appeared to play a critical role in the pathological progression of cerebral atherosclerosis. Microglia likely underwent an M2c-like polarization in an environment long exposed to high glucose. Experimental suppression of microglia M2c polarization was achieved through transduction of microglia with an adeno-associated virus (serotype AAV-PHP.B) carrying siRNA for interleukin-10 (IL-10) under the control of a microglia-specific TMEM119 promoter, which significantly attenuated diabetes-associated cerebral atherosclerosis in a mouse model. Thus, our study suggests a novel translational strategy to prevent diabetes-associated cerebral atherosclerosis through in vivo control of microglia polarization