Tackling Over-Smoothing for General Graph Convolutional Networks

Increasing the depth of GCN, which is expected to permit more expressivity, is shown to incur performance detriment especially on node classification. The main cause of this lies in over-smoothing. The over-smoothing issue drives the output of GCN towards a space that contains limited distinguished information among nodes, leading to poor expressivity. Several works on refining the architecture of deep GCN have been proposed, but it is still unknown in theory whether or not these refinements are able to relieve over-smoothing. In this paper, we first theoretically analyze how general GCNs act with the increase in depth, including generic GCN, GCN with bias, ResGCN, and APPNP. We find that all these models are characterized by a universal process: all nodes converging to a cuboid. Upon this theorem, we propose DropEdge to alleviate over-smoothing by randomly removing a certain number of edges at each training epoch. Theoretically, DropEdge either reduces the convergence speed of over-smoothing or relieves the information loss caused by dimension collapse. Experimental evaluations on simulated dataset have visualized the difference in over-smoothing between different GCNs. Moreover, extensive experiments on several real benchmarks support that DropEdge consistently improves the performance on a variety of both shallow and deep GCNs.Comment: Submitted to TPAMI, 15 page

Tranquilizing and Allaying Excitement Needling Method Affects BDNF and SYP Expression in Hippocampus

Sleep disorder is a state of sleep loss caused by various reasons, which leads to a series of changes, such as emotion, learning and memory, and immune function. “Tranquilizing and allaying excitement” was widely used in clinical treatment of insomnia; however, the mechanism was still not very clear. We randomly divided rats into three groups: control group, sleep deprivation group, and acupuncture treatment group. We observed BDNF and SYP expression in hippocampus in these three groups. Both protein contents and mRNA contents of BDNF and SYP were measured by western blot, immunohistochemistry, and RT-PCR analysis. The sleep deprivation model was established using modified multiple platform sleep deprivation method (MMPM). Our study explored the BDNF and SYP abnormality in hippocampus caused by sleep deprivation and “tranquilizing and allaying excitement” intervention regulated the abnormal expression of BDNF and SYP caused by sleep deprivation on the short run and the long run. Our study provided a molecular evidence that “tranquilizing and allaying excitement” treatment in rats with sleep disorder affects learning and memory ability

Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic

Learning high-quality Q-value functions plays a key role in the success of many modern off-policy deep reinforcement learning (RL) algorithms. Previous works focus on addressing the value overestimation issue, an outcome of adopting function approximators and off-policy learning. Deviating from the common viewpoint, we observe that Q-values are indeed underestimated in the latter stage of the RL training process, primarily related to the use of inferior actions from the current policy in Bellman updates as compared to the more optimal action samples in the replay buffer. We hypothesize that this long-neglected phenomenon potentially hinders policy learning and reduces sample efficiency. Our insight to address this issue is to incorporate sufficient exploitation of past successes while maintaining exploration optimism. We propose the Blended Exploitation and Exploration (BEE) operator, a simple yet effective approach that updates Q-value using both historical best-performing actions and the current policy. The instantiations of our method in both model-free and model-based settings outperform state-of-the-art methods in various continuous control tasks and achieve strong performance in failure-prone scenarios and real-world robot tasks

Aberrant corticostriatal functional circuits in adolescents with Internet addiction disorder

Abnormal structure and function in the striatum and prefrontal cortex have been revealed in Internet addiction disorder (IAD). However, little is known about alterations of corticostriatal functional circuits in IAD. The aim of this study was to investigate the integrity of corticostriatal functional circuits and their relations to neuropsychological measures in IAD by resting-state functional connectivity. Fourteen IAD adolescents and 15 healthy controls underwent resting-state fMRI scans. Using 6 predefined bilateral striatal regions-of-interest, voxelwise correlation maps were computed and compared between groups. Relationships between alterations of corticostriatal connectivity and clinical measurements were examined in the IAD group. Compared to controls, IAD subjects exhibited reduced connectivity between the inferior ventral striatum and bilateral caudate head, subgenual anterior cingulate cortex (ACC), and posterior cingulate cortex, and between the superior ventral striatum and bilateral dorsal/rostral ACC, ventral anterior thalamus, and putamen/pallidum/insula/inferior frontal gyrus (IFG), and between the dorsal caudate and dorsal/rostral ACC, thalamus, and IFG, and between the left ventral rostral putamen and right IFG. IAD subjects also showed increased connectivity between the left dorsal caudal putamen and bilateral caudal cigulate motor area. Moreover, altered cotricostriatal functional circuits were significantly correlated with neuropsychological measures. This study directly provides evidence that IAD is associated with alterations of corticostriatal functional circuits involved in the affective and motivation processing, and cognitive control. These findings emphasize that functional connections in the corticostriatal circuits are modulated by affective/motivational/cognitive states and further suggest that IAD may have abnormalities of such modulation in this network

A Dimensional Structure based Knowledge Distillation Method for Cross-Modal Learning

Due to limitations in data quality, some essential visual tasks are difficult to perform independently. Introducing previously unavailable information to transfer informative dark knowledge has been a common way to solve such hard tasks. However, research on why transferred knowledge works has not been extensively explored. To address this issue, in this paper, we discover the correlation between feature discriminability and dimensional structure (DS) by analyzing and observing features extracted from simple and hard tasks. On this basis, we express DS using deep channel-wise correlation and intermediate spatial distribution, and propose a novel cross-modal knowledge distillation (CMKD) method for better supervised cross-modal learning (CML) performance. The proposed method enforces output features to be channel-wise independent and intermediate ones to be uniformly distributed, thereby learning semantically irrelevant features from the hard task to boost its accuracy. This is especially useful in specific applications where the performance gap between dual modalities is relatively large. Furthermore, we collect a real-world CML dataset to promote community development. The dataset contains more than 10,000 paired optical and radar images and is continuously being updated. Experimental results on real-world and benchmark datasets validate the effectiveness of the proposed method

Self doping effect and successive magnetic transitions in superconducting Sr2_2VFeAsO3_3

We have studied a quinary Fe-based superconductor Sr$_2$VFeAsO$_3$ by the measurements of x-ray diffraction, x-ray absorption, M\"{o}ssbauer spectrum, resistivity, magnetization and specific heat. This apparently undoped oxyarsenide is shown to be self doped via electron transfer from the V$^{3+}$ ions. We observed successive magnetic transitions within the VO$_2$ layers: an antiferromagnetic transition at 150 K followed by a weak ferromagnetic transition at 55 K. The spin orderings within the VO$_2$ planes are discussed based on mixed valence of V$^{3+}$ and V$^{4+}$.Comment: One Table and more references are adde

Long-term psychological intervention for parents of children with prolonged disorders of consciousness: a pilot study

BackgroundChildren with prolonged disorders of consciousness experience severe intellectual and behavioral disabilities that will last for decades or even a lifetime. Parents generally experience severe anxiety, stress, sadness, or family conflicts, which can lead to abnormal parenting behavior and can, in turn, adversely affect the cognitive, emotional, and behavioral well-being of the children. This causes a serious burden on children, families, and society. Psychological interventions targeting parents using online conversations provide an opportunity to improve the overall well-being of the parents, their children, and the family as a whole.MethodsA total of 13 patients completed the protocol. Six were girls (46.2%), the mean age was 4.5 ± 3.0 years, and the length of time before emergent from minimally consciousness state was 244 ± 235 days. A staff member with psychological counseling qualifications implemented all psychological interventions. Regular online psychological interventions were performed annually before and after discharge. Evaluation data were collected before discharge and at 1 and 3–5 years post-discharge.ResultsWith the extension of intervention time, the Strengths and Difficulties Questionnaire, the Depression Anxiety and Stress Scale-21, and the Parenting Sense of Competence Scale scores showed significant improvement (p < 0.05), while the Revised Scale for Caregiving Self-Efficacy scores did not. With the extension of intervention time, the Strengths and Difficulties Questionnaire (Total Difficulties scores, TD) scores showed significant improvement (p < 0.05), while the scores did not after 1 year compared with before intervention. The Index of Child Care Environment evaluation scores declined significantly (p < 0.05).ConclusionPsychological interventions aimed at the parents of children with prolonged disorders of consciousness performed at least once per year resulted in significant improvements in negative parental emotions, parental self-efficacy, and emotional and behavioral problems in their children. However, the childcare environment continued to decline