Impacts of the introduced European honeybee on Australian bee‐flower network properties in urban bushland remnants and residential gardens

Abstract Background We aimed to identify sex differences in the network properties and to recognize the geometric alteration effects of long-term swim training in a rat model of exercise-induced left ventricular (LV) hypertrophy. Methods Thirty-eight Wistar rats were divided into four groups: male sedentary, female sedentary, male exercised and female exercised. After training sessions, LV morphology and function were checked by echocardiography. The geometry of the left coronary artery system was analysed on pressure-perfused, microsurgically prepared resistance artery networks using in situ video microscopy. All segments over > 80 μm in diameter were studied using divided 50-μm-long cylindrical ring units of the networks. Oxidative-nitrative (O-N) stress markers, adenosine A2A and estrogen receptor (ER) were investigated by immunohistochemistry. Results The LV mass index, ejection fraction and fractional shortening significantly increased in exercised animals. We found substantial sex differences in the coronary network in the control groups and in the swim-trained animals. Ring frequency spectra were significantly different between male and female animals in both the sedentary and trained groups. The thickness of the wall was higher in males as a result of training. There were elevations in the populations of 200- and 400-μm vessel units in males; the thinner ones developed farther and the thicker ones closer to the orifice. In females, a new population of 200- to 250-μm vessels appeared unusually close to the orifice. Conclusions Physical activity and LV hypertrophy were accompanied by a remodelling of coronary resistance artery network geometry that was different in both sexes.

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Network properties of decoys and CASP predicted models: a comparison with native protein structures

Molecular BioSystems ◽

10.1039/c3mb70157c ◽

2013 ◽

Vol 9 (7) ◽

pp. 1774 ◽

Cited By ~ 11

Author(s):

S. Chatterjee ◽

S. Ghosh ◽

S. Vishveshwara

Keyword(s):

Protein Structures ◽

Native Protein ◽

Network Properties

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Network Embedding on Hierarchical Community Structure Network

ACM Transactions on Knowledge Discovery from Data ◽

10.1145/3434747 ◽

2021 ◽

Vol 15 (4) ◽

pp. 1-23

Author(s):

Guojie Song ◽

Yun Wang ◽

Lun Du ◽

Yi Li ◽

Junshan Wang

Keyword(s):

Community Structure ◽

Structural Information ◽

Spherical Surface ◽

Network Embedding ◽

The Galaxy ◽

Community Information ◽

The Hierarchical Structure ◽

Network Properties ◽

Multi Class Classification ◽

Low Dimensional

Network embedding is a method of learning a low-dimensional vector representation of network vertices under the condition of preserving different types of network properties. Previous studies mainly focus on preserving structural information of vertices at a particular scale, like neighbor information or community information, but cannot preserve the hierarchical community structure, which would enable the network to be easily analyzed at various scales. Inspired by the hierarchical structure of galaxies, we propose the Galaxy Network Embedding (GNE) model, which formulates an optimization problem with spherical constraints to describe the hierarchical community structure preserving network embedding. More specifically, we present an approach of embedding communities into a low-dimensional spherical surface, the center of which represents the parent community they belong to. Our experiments reveal that the representations from GNE preserve the hierarchical community structure and show advantages in several applications such as vertex multi-class classification, network visualization, and link prediction. The source code of GNE is available online.

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Pathways to language: a naturalistic study of children with Williams syndrome and children with Down syndrome

Journal of Child Language ◽

10.1017/s0305000912000475 ◽

2012 ◽

Vol 40 (1) ◽

pp. 106-138 ◽

Cited By ~ 12

Author(s):

YONATA LEVY ◽

ARIELA EILAM

Keyword(s):

Down Syndrome ◽

Data Collection ◽

Williams Syndrome ◽

Language Delay ◽

Typically Developing ◽

Naturalistic Study ◽

Children With Down Syndrome ◽

Network Properties ◽

Development Of Language ◽

Language Onset

ABSTRACTThis is a naturalistic study of the development of language in Hebrew-speaking children with Williams syndrome (WS) and children with Down syndrome (DS), whose MLU extended from 1·0 to 4·4. Developmental curves over the entire span of data collection revealed minor differences between children with WS, children with DS, and typically developing (TD) controls of similar MLU. Development within one calendar year showed remarkable synchrony among the variables. However, age of language onset and pace of acquisition departed significantly from normal timing. It is argued that in view of the centrality of genetic timing and the network properties of cognition, normal schedules are crucial determinants of intact development. Consequently, with respect to neurodevelopmental syndromes, the so-called ‘language delay’ is indicative of deviance that is likely to impact development in critical ways.

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