Graph Matching in Correlated Stochastic Block Models for Improved Graph Clustering

We consider community detection from multiple correlated graphs sharing the same community structure. The correlated graphs are generated by independent subsampling of a parent graph sampled from the stochastic block model. The vertex correspondence between the correlated graphs is assumed to be unknown. We consider the two-step procedure where the vertex correspondence between the correlated graphs is first revealed, and the communities are recovered from the union of the correlated graphs, which becomes denser than each single graph. We derive the information-theoretic limits for exact graph matching in general density regimes and the number of communities, and then analyze the regime of graph parameters, where one can benefit from the matching of the correlated graphs in recovering the latent community structure of the graphs.Comment: Allerton Conference 202

Efficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation

We consider the problem of graph matching, or learning vertex correspondence, between two correlated stochastic block models (SBMs). The graph matching problem arises in various fields, including computer vision, natural language processing and bioinformatics, and in particular, matching graphs with inherent community structure has significance related to de-anonymization of correlated social networks. Compared to the correlated Erdos-Renyi (ER) model, where various efficient algorithms have been developed, among which a few algorithms have been proven to achieve the exact matching with constant edge correlation, no low-order polynomial algorithm has been known to achieve exact matching for the correlated SBMs with constant correlation. In this work, we propose an efficient algorithm for matching graphs with community structure, based on the comparison between partition trees rooted from each vertex, by extending the idea of Mao et al. (2021) to graphs with communities. The partition tree divides the large neighborhoods of each vertex into disjoint subsets using their edge statistics to different communities. Our algorithm is the first low-order polynomial-time algorithm achieving exact matching between two correlated SBMs with high probability in dense graphs.Comment: ICML 202

The role of inhibitory control in task switching

Previous research on task switching has been confounded by inhibitory control mechanism and there has been debate on the source of switch costs and how and when the inhibitory control occurs during task switching. In order to circumvent this problem, the thesis aimed to investigate the role of inhibition in task switching by examining switch costs, alternating switch costs and congruency effect in three tasks when two preparation intervals (short and long) are given. Task switching experiments in the present study captured both flexibility (changes in task) and anticipatory control (preparation interval between cue and target) and provided the measurement for inhibitory control, 'backward inhibition' by alternating switch cost. Backward inhibition was manifest in longer reaction times (and/or more errors) to alternating switch trials (ABA) than to double switch trials (CBA). Reaction time and error in the present study also reflected whether the task in the current trials were easy when it requires the same response as the task in the previous trials, i.e., whether the required response were congruent. The results in the thesis provided the strong evidence for switch costs as one of cognitive control mechanism and it was reduced by the long preparation interval through all the experiments. When the cues were arbitrarily matched for each task, switch costs were increased, suggesting that high working memory load and the effort for interpretation of the cues might cause more additional process during switching tasks. On the other hand, the change of the cue type was insensitive to backward inhibition since there were no significant differences on the size of alternating switch costs. The results imply that the occurrence of backward inhibition is more prone to the type of task you perform and level of congruency

The role of inhibitory control in task switching

Previous research on task switching has been confounded by inhibitory control mechanism and there has been debate on the source of switch costs and how and when the inhibitory control occurs during task switching. In order to circumvent this problem, the thesis aimed to investigate the role of inhibition in task switching by examining switch costs, alternating switch costs and congruency effect in three tasks when two preparation intervals (short and long) are given. Task switching experiments in the present study captured both flexibility (changes in task) and anticipatory control (preparation interval between cue and target) and provided the measurement for inhibitory control, 'backward inhibition' by alternating switch cost. Backward inhibition was manifest in longer reaction times (and/or more errors) to alternating switch trials (ABA) than to double switch trials (CBA). Reaction time and error in the present study also reflected whether the task in the current trials were easy when it requires the same response as the task in the previous trials, i.e., whether the required response were congruent. The results in the thesis provided the strong evidence for switch costs as one of cognitive control mechanism and it was reduced by the long preparation interval through all the experiments. When the cues were arbitrarily matched for each task, switch costs were increased, suggesting that high working memory load and the effort for interpretation of the cues might cause more additional process during switching tasks. On the other hand, the change of the cue type was insensitive to backward inhibition since there were no significant differences on the size of alternating switch costs. The results imply that the occurrence of backward inhibition is more prone to the type of task you perform and level of congruency

HRT, Herbal Formula, Induces G 2

We have demonstrated the anticancer effect of HRT in HCT116, human colon carcinoma cells. HRT inhibited cancer cell growth by causing cell cycle arrest at G2/M and inducing apoptosis as evidenced by DNA fragmentation assay. We found that HRT induces the activation of caspase-3, -8, and -9, whereas it reduces the level of Bcl-2 protein and results in the cleavage of PARP. Further, HRT decreased the level of phosphorylation of Akt and its downstream signals such as mTOR and GSK-3β. These results indicate that HRT stimulates the apoptotic signaling pathway and represses the survival and proliferation of colon cancer cells via inhibiting Akt activity. Hence, our results suggest that HRT has a potential to be developed as a therapeutic agent against colon cancer cells

Improved hematopoietic differentiation of human pluripotent stem cells via estrogen receptor signaling pathway

Additional file 2: Table S1. Temporal changes (%) of ER-Îą and hematopoietic phenotypes during hiPSC-derived hematopoietic differentiation