H

With the help of a stochastic bounded real lemma, we deal with finite horizon H2/H∞ control problem for discrete-time MJLS, whose Markov chain takes values in an infinite set. Besides, a unified control design for H2, H∞, and H2/H∞ is given

Improving Sparsity and Modularity of High-Order Functional Connectivity Networks for MCI and ASD Identification

High-order correlation has recently been proposed to model brain functional connectivity network (FCN) for identifying neurological disorders, such as mild cognitive impairment (MCI) and autism spectrum disorder (ASD). In practice, the high-order FCN (HoFCN) can be derived from multiple low-order FCNs that are estimated separately in a series of sliding windows, and thus it in fact provides a way of integrating dynamic information encoded in a sequence of low-order FCNs. However, the estimation of low-order FCN may be unreliable due to the fact that the use of limited volumes/samples in a sliding window can significantly reduce the statistical power, which in turn affects the reliability of the resulted HoFCN. To address this issue, we propose to enhance HoFCN based on a regularized learning framework. More specifically, we first calculate an initial HoFCN using a recently developed method based on maximum likelihood estimation. Then, we learn an optimal neighborhood network of the initially estimated HoFCN with sparsity and modularity priors as regularizers. Finally, based on the improved HoFCNs, we conduct experiments to identify MCI and ASD patients from their corresponding normal controls. Experimental results show that the proposed methods outperform the baseline methods, and the improved HoFCNs with modularity prior consistently achieve the best performance

Statistics of Galactic-Scale Quasar Pairs at Cosmic Noon

The statistics of galactic-scale quasar pairs can elucidate our understanding of the dynamical evolution of supermassive black hole (SMBH) pairs, the duty cycles of quasar activity in mergers, or even the nature of dark matter, but have been challenging to measure at cosmic noon, the prime epoch of massive galaxy and SMBH formation. Here we measure a double quasar fraction of $\sim 6.2\pm0.5\times 10^{-4}$ integrated over $\sim 0.3-3$ arcsec separations (projected physical separations of $\sim 3-30\,{\rm kpc}$ at $z\sim 2$) in luminous ($L_{\rm bol}>10^{45.8}\,{\rm erg\,s^{-1}}$) unobscured quasars at $1.5<z<3.5$, using Gaia EDR3-resolved pairs around SDSS DR16 quasars. The measurement was based on a sample of 60 Gaia-resolved double quasars (out of 487 Gaia pairs dominated by quasar+star superpositions) at these separations, corrected for pair completeness in Gaia, which we quantify as functions of pair separation, magnitude of the primary, and magnitude contrast. The double quasar fraction increases towards smaller separations by a factor of $\sim 5$ over these scales. The division between physical quasar pairs and lensed quasars in our sample is currently unknown, requiring dedicated follow-up observations (in particular, deep, sub-arcsec-resolution IR imaging for the closest pairs). Intriguingly, at this point the observed pair statistics are in rough agreement with theoretical predictions both for the lensed quasar population in mock catalogs and for dual quasars in cosmological hydrodynamic simulations. Upcoming wide-field imaging/spectroscopic space missions such as Euclid, CSST and Roman, combined with targeted follow-up observations, will conclusively measure the abundances and host galaxy properties of galactic-scale quasar pairs, offset AGNs, and sub-arcsec lensed quasars across cosmic time.Comment: 19 pages, 9 figures; submitted to Ap

Electronic Structure of Superconducting Infinite-Layer Lanthanum Nickelates

Revealing the momentum-resolved electronic structure of infinite-layer nickelates is essential for understanding this new class of unconventional superconductors, but has been hindered by the formidable challenges in improving the sample quality. In this work, we report for the first time the angle-resolved photoemission spectroscopy of superconducting La$_{0.8}$Sr$_{0.2}$NiO$_{2}$ films prepared by molecular beam epitaxy and ${\mathrm{\textit{in situ}}}$ atomic-hydrogen reduction. The measured Fermi topology closely matches theoretical calculations, showing a large Ni-$d_{x^2-y^2}$ derived Fermi sheet that evolves from hole-like to electron-like along $k_{z}$, and a three-dimensional (3D) electron pocket centered at Brillouin zone corner. The Ni-$d_{x^2-y^2}$ derived bands show a mass enhancement ($m^*/m_{\rm{DFT}}$) of 2-3,while the 3D electron band shows negligible band renormalization. Moreover, the Ni-$d_{x^2-y^2}$ derived states also display a band dispersion anomaly at higher binding energy, reminiscent of the waterfall feature and kinks observed in cuprates.Comment: 29 pages,13 figure

Social Benefits Evaluation of Rural Micro-Landscapes in Southeastern Coastal Towns of China&mdash;The Case of Jinjiang, Fujian

Faced with the current situation of the decay and alienation of traditional public space and the broken and disorderly spatial structure caused by the rapid urbanization of the Chinese countryside, rural micro-landscape creation has become an effective way to improve human living environments. However, it is currently difficult for rural micro-landscape construction to achieve the sustainable development of social benefits due to the lack of scientific design guidelines. Evaluating the social benefits of completed projects and identifying the important influencing factors are key to realizing the evidence-based design of rural micro-landscapes. To this end, this study deduces the mechanism of social benefit generation based on the psychological process of spatial perception and establishes a structural equation model containing compound influence pathways to measure the social benefits of micro-landscapes. The evaluation model consists of four latent variables, &ldquo;physical element characteristics&rdquo;, &ldquo;perceptual quality&rdquo;, &ldquo;cognitive experience&rdquo;, and &ldquo;activity behavior&rdquo;, and 35 observed variables. The researchers selected 18 micro-landscape areas in Jinjiang City, Fujian Province, China, as the survey sample and analyzed the influence of the potential variables and the explanatory power of the observed variables through a quantitative analysis of objective environmental elements and perception data from 102 respondents. The results showed that &ldquo;perceptual quality&rdquo; and &ldquo;cognitive experience&rdquo; had the greatest direct effect on social benefits, and, based on the progressive influence relationships among the dimensions, &ldquo;physical element characteristics&rdquo; dominated the total social benefits through direct and indirect means. Compared with single-function green space, comfortable and diverse artificial facilities encourage residents to enter and use micro-landscapes and contribute to their social benefits. The purpose of this paper is to explore the ideal form of rural micro-landscape creation and provide a theoretical basis for the future practice of high-quality and sustainable rural micro-landscape construction

Social Benefits Evaluation of Rural Micro-Landscapes in Southeastern Coastal Towns of China—The Case of Jinjiang, Fujian

Faced with the current situation of the decay and alienation of traditional public space and the broken and disorderly spatial structure caused by the rapid urbanization of the Chinese countryside, rural micro-landscape creation has become an effective way to improve human living environments. However, it is currently difficult for rural micro-landscape construction to achieve the sustainable development of social benefits due to the lack of scientific design guidelines. Evaluating the social benefits of completed projects and identifying the important influencing factors are key to realizing the evidence-based design of rural micro-landscapes. To this end, this study deduces the mechanism of social benefit generation based on the psychological process of spatial perception and establishes a structural equation model containing compound influence pathways to measure the social benefits of micro-landscapes. The evaluation model consists of four latent variables, “physical element characteristics”, “perceptual quality”, “cognitive experience”, and “activity behavior”, and 35 observed variables. The researchers selected 18 micro-landscape areas in Jinjiang City, Fujian Province, China, as the survey sample and analyzed the influence of the potential variables and the explanatory power of the observed variables through a quantitative analysis of objective environmental elements and perception data from 102 respondents. The results showed that “perceptual quality” and “cognitive experience” had the greatest direct effect on social benefits, and, based on the progressive influence relationships among the dimensions, “physical element characteristics” dominated the total social benefits through direct and indirect means. Compared with single-function green space, comfortable and diverse artificial facilities encourage residents to enter and use micro-landscapes and contribute to their social benefits. The purpose of this paper is to explore the ideal form of rural micro-landscape creation and provide a theoretical basis for the future practice of high-quality and sustainable rural micro-landscape construction

Simultaneous Estimation of Low- and High-Order Functional Connectivity for Identifying Mild Cognitive Impairment

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