Pairwise Covariates-adjusted Block Model for Community Detection

One of the most fundamental problems in network study is community detection. The stochastic block model (SBM) is one widely used model for network data with different estimation methods developed with their community detection consistency results unveiled. However, the SBM is restricted by the strong assumption that all nodes in the same community are stochastically equivalent, which may not be suitable for practical applications. We introduce a pairwise covariates-adjusted stochastic block model (PCABM), a generalization of SBM that incorporates pairwise covariate information. We study the maximum likelihood estimates of the coefficients for the covariates as well as the community assignments. It is shown that both the coefficient estimates of the covariates and the community assignments are consistent under suitable sparsity conditions. Spectral clustering with adjustment (SCWA) is introduced to efficiently solve PCABM. Under certain conditions, we derive the error bound of community estimation under SCWA and show that it is community detection consistent. PCABM compares favorably with the SBM or degree-corrected stochastic block model (DCBM) under a wide range of simulated and real networks when covariate information is accessible.Comment: 41 pages, 6 figure

ELUCID IV: Galaxy Quenching and its Relation to Halo Mass, Environment, and Assembly Bias

We examine the quenched fraction of central and satellite galaxies as a function of galaxy stellar mass, halo mass, and the matter density of their large scale environment. Matter densities are inferred from our ELUCID simulation, a constrained simulation of local Universe sampled by SDSS, while halo masses and central/satellite classification are taken from the galaxy group catalog of Yang et al. The quenched fraction for the total population increases systematically with the three quantities. We find that the `environmental quenching efficiency', which quantifies the quenched fraction as function of halo mass, is independent of stellar mass. And this independence is the origin of the stellar mass-independence of density-based quenching efficiency, found in previous studies. Considering centrals and satellites separately, we find that the two populations follow similar correlations of quenching efficiency with halo mass and stellar mass, suggesting that they have experienced similar quenching processes in their host halo. We demonstrate that satellite quenching alone cannot account for the environmental quenching efficiency of the total galaxy population and the difference between the two populations found previously mainly arises from the fact that centrals and satellites of the same stellar mass reside, on average, in halos of different mass. After removing these halo-mass and stellar-mass effects, there remains a weak, but significant, residual dependence on environmental density, which is eliminated when halo assembly bias is taken into account. Our results therefore indicate that halo mass is the prime environmental parameter that regulates the quenching of both centrals and satellites.Comment: 21 pages, 16 figures, submitted to Ap

Connecting past and present.

A neural signature of serial dependence has been found, which mirrors the attractive bias of visual information seen in behavioral experiments

Spectral clustering via adaptive layer aggregation for multi-layer networks

One of the fundamental problems in network analysis is detecting community structure in multi-layer networks, of which each layer represents one type of edge information among the nodes. We propose integrative spectral clustering approaches based on effective convex layer aggregations. Our aggregation methods are strongly motivated by a delicate asymptotic analysis of the spectral embedding of weighted adjacency matrices and the downstream $k$-means clustering, in a challenging regime where community detection consistency is impossible. In fact, the methods are shown to estimate the optimal convex aggregation, which minimizes the mis-clustering error under some specialized multi-layer network models. Our analysis further suggests that clustering using Gaussian mixture models is generally superior to the commonly used $k$-means in spectral clustering. Extensive numerical studies demonstrate that our adaptive aggregation techniques, together with Gaussian mixture model clustering, make the new spectral clustering remarkably competitive compared to several popularly used methods.Comment: 71 page

Efficiency in Writing Systems: Testing Zipf's Law of Abbreviation Across Letters, N-Grams, and Words

This study investigates Zipf's Law of Abbreviation (ZLA) across 155 writing systems, analyzing how visual complexity optimizes with information content at three linguistic levels: letters, n-grams, and words. Using perimetric and skeleton-length complexity metrics, we demonstrate that letters exhibit the strongest correlation (� = 0.2–0.4 in most languages), confirming their role as primary units of efficiency optimization. Larger units (n-grams/words) show weaker effects due to structural constraints. While alphabetic scripts (e.g., Latin-based) align robustly with ZLA, logographic (e.g., Chinese) and abugida (e.g., Kannada) systems reveal exceptions—some with near-zero or negative correlations—highlighting script-specific pressures like distinctiveness or historical preservation. Our findings refine ZLA by emphasizing visual (not just length-based) effort minimization and underscore letters as the fundamental locus of abbreviation effects. Limitations in script diversity and complexity metrics suggest future directions, including phylogenetic controls and perceptual complexity measures. This work advances the cross-linguistic study of writing system evolution under efficiency pressures

Building a Cultural and Creative Industry Platform to Serve the Economic Development

With the rise of global integration of science, technology economy and cultural creative industries develop rapidly. Under the circumstance of rapid development, how to train the development of cultural creative industries talents has become a key factor problem of prosperity society. Institutions of higher learning undertake the four functions of talent training, scientific research, social service cultural inheritance and innovation. Therefore, it is necessary to build a research platform for cultural and creative industry of the college. This platform is not only help graduates find their future employment direction, but also effectively help them to obtain employment and start businesses. At the same time, the platform is used to enhance the integration with local industry development and promote the local economy development, which not only meets the development of college, but also meets the needs of local governments and enterprises. This mode of training talents for government-industry-university-research cooperation meets the interest demands of the government, industry and school, and serves the development of local economy together. Keywords: Cultural Creative Product; Talent Cultivation; Local Economic; Economic Development. eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open-access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under the responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians), and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7iSI7.377

Hemodynamics of Enhanced External Counterpulsation with Different Coronary Stenosis

Enhanced external counterpulsation (EECP) is able to treat myocardial ischemia, which is usually caused by coronary artery stenosis. However, the underlying mechanisms regarding why this technique is effective in treating myocardial ischemia remains unclear and there is no patient-specific counterpulsation mode for different rates of coronary artery stenosis in clinic. This study sought to investigate the hemodynamic effect of varied coronary artery stenosis rates when using EECP and the necessity of adopting targeted counterpulsation mode to consider different rates of coronary artery stenosis. Three 3-dimensional (3D) coronary models with different stenosis rates, including 55% (Model 1), 65% (Model 2), and 75% (Model 3), were generated, then coupled with a 0-dimensional (0D) lumped parametric model of the blood circulatory system. EECP was applied to the 0D/3D coupled models to study the hemodynamic response of the coronary artery. Under the same counterpulsation mode, the ratio of diastolic blood pressure to systolic blood pressure of 3 models during counterpulsation was 1.4, and the cardiac output and coronary artery flow rate increased significantly. The low wall shear stress (WSS) and high oscillatory shear index (OSI) areas were mainly located at the posterior end of the stenosis and coronary artery bifurcation. Moreover, with an increase in the rate of coronary artery stenosis, the increased percentage of flow rate through the coronary artery stenosis and area-averaged WSS decreased. The geometric multiscale model in this study can be used to effectively simulate the hemodynamic characteristics of cardiovascular system following the application of EECP. Local precise hemodynamic effect of the coronary artery stenosis can be observed. It was found from the hemodynamic factors that the coronary artery with lower stenosis rate more likely led to better vascular endothelial remodeling. Thus, it is necessary to adopt patient-specific counterpulsation mode accounting for different condition of coronary artery stenosis