439 research outputs found

    Hub-Induced Synchronization in Scale-Free Networks with Cluster Structure

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    A recent research indicated that the corticocortical connectivity network of the cat possesses cluster structure and that each cluster in the network is scale-free and has a most connected hub. Motivated by that research, we slightly modify the network model and derive sufficient conditions for cluster synchronization of the modified network based on Lyapunov function method. The obtained results indicate that cluster synchronization can be induced by the hubs of the scale-free networks. In our opinion, the concept of hub-induced synchronization provides a better understanding of cluster synchronization in scale-free networks. Numerical examples are provided to demonstrate the effectiveness of the theoretical results

    The Differentiation Balance of Bone Marrow Mesenchymal Stem Cells Is Crucial to Hematopoiesis.

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    Bone marrow mesenchymal stem cells (BMSCs), the important component and regulator of bone marrow microenvironment, give rise to hematopoietic-supporting stromal cells and form hematopoietic niches for hematopoietic stem cells (HSCs). However, how BMSC differentiation affects hematopoiesis is poorly understood. In this review, we focus on the role of BMSC differentiation in hematopoiesis. We discussed the role of BMSCs and their progeny in hematopoiesis. We also examine the mechanisms that cause differentiation bias of BMSCs in stress conditions including aging, irradiation, and chemotherapy. Moreover, the differentiation balance of BMSCs is crucial to hematopoiesis. We highlight the negative effects of differentiation bias of BMSCs on hematopoietic recovery after bone marrow transplantation. Keeping the differentiation balance of BMSCs is critical for hematopoietic recovery. This review summarises current understanding about how BMSC differentiation affects hematopoiesis and its potential application in improving hematopoietic recovery after bone marrow transplantation

    Leveraging Deep Learning and Digital Twins to Improve Energy Performance of Buildings

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    Digital transformation in buildings accumulates massive operational data, which calls for smart solutions to utilize these data to improve energy performance. This study has proposed a solution, namely Deep Energy Twin, for integrating deep learning and digital twins to better understand building energy use and identify the potential for improving energy efficiency. Ontology was adopted to create parametric digital twins to provide consistency of data format across different systems in a building. Based on created digital twins and collected data, deep learning methods were used for performing data analytics to identify patterns and provide insights for energy optimization. As a demonstration, a case study was conducted in a public historic building in Norrk\"oping, Sweden, to compare the performance of state-of-the-art deep learning architectures in building energy forecasting.Comment: 6 pages, 5 figures, accepted in the 3rd IEEE International Conference on Industrial Electronics for Sustainable Energy System

    Design and development of infrastructure of the Dome A Kunlun Station (2005–2015)

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    To enable further advanced study of Antarctica, a new station called Kunlun Station has been built by China in the Dome A region of the inland East Antarctic ice sheet. This paper describes the Antarctic station building design system that was developed with consideration of factors that may affect Kunlun Station, such as environment and climate, construction work and transport, environmental protection and energy conservation, psychological requirements and functional requirements. The design system included site selection, station planning, external building form, construction work, function and indoor environment, energy conservation, environmental protection, and material strategy. We also describe the experience acquired during the transportation and construction phases of Kunlun Station

    Association of Lumican Gene with Susceptibility to Pathological Myopia in the Northern Han Ethnic Chinese

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    Pathological myopia is a severe hereditary ocular disease leading to blindness. It is urgent and very important to find the pathogenesis and therapy for this disease. The purpose of the study is to analyze sequences of lumican and decorin genes with pathological myopia(PM) and control subjects to verify the relationship between lumican, decorin genes and PM in Northern Han Chinese. We collected and analyzed the blood samples of 94 adults (including 12 pedigree cases and 82 sporadic cases) with PM and 90 controls in the northern Han ethnic Chinese. Genotyping was performed by direct sequencing after polymerase chain reaction(PCR) amplification and allele frequencies were tested for Hardy-Weinberg equilibrium. Univariate analysis revealed significant differences between two groups for three SNPs: rs3759223 (C → T) and rs17853500 (T → C) of the lumican gene and rs74419 (T → C) of decorin gene with (P < .05) for all their genotype distribution and allele frequency. There is no significant difference for incidence of these mutations between pedigree and sporadic group (P > .05). The results suggested that the sequence variants in 5′-regulatory region of lumican gene and 3'UTR of decorin gene were associated significantly with PM in Northern Han Chinese. Further studies are needed to confirm finally whether the two genes are the virulence genes of PM
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