The recently observed gravitational wave background is explained in terms of the quantum modification of the general relativity (Qmoger). Some UFO, FRB and supernova flares also can be explained in terms of Qmoger.
The function of a network is affected by its structure. For example, the presence of highly interactive individuals, or hubs, influences the extent and rate of information spread across a network. In a network of inte...The function of a network is affected by its structure. For example, the presence of highly interactive individuals, or hubs, influences the extent and rate of information spread across a network. In a network of interactions, the duration over which individual variation in interactions persists may affect how the network operates. Individuals may persist in their behavior over time and across situations, often referred to as personality. Colonies of social insects are an example of a biological system in which the structure of the coordinated networks of interacting workers may greatly influence information flow within the colony, and therefore its collective behavior. Here I investigate the effects of persistence in walking patterns on interaction networks us- ing computer simulations that are parameterized using observed behavior of harvester ants. I examine how the duration of persis- tence in spatial behavior influences network structure. Furthermore, I explore how spatial features of the environment affect the relationship between persistent behavior and network structure. I show that as persistence increases, the skewness of the weighted degree distribution of the interaction network increases. However, this relationship holds only when ants are confined in a space with boundaries, but not when physical barriers are absent. These findings suggest that the influence of animal personalities on network structure and function depends on the environment in which the animals reside [Current Zoology 61 （1）： 98-106, 2015].展开更多
A predominant benefit of social living is the ability to share knowledge that cannot be gained through the information an individual accumulates based on its personal experience alone. Traditional computational models...A predominant benefit of social living is the ability to share knowledge that cannot be gained through the information an individual accumulates based on its personal experience alone. Traditional computational models have portrayed sharing knowledge through interactions among members of social groups via dyadic networks. Such models aim at understanding the percolation of information among individuals and groups to identify potential limitations to successful knowledge transfer. How- ever, because many real-world interactions are not solely pairwise, i.e., several group members may obtain information from one another simultaneously, it is necessary to understand more than dyadic communication and learning processes to capture their full complexity. We detail a modeling framework based on the simplicial set, a concept from algebraic topology, which allows elegant encapsulation of multi-agent interactions. Such a model system allows us to analyze how individual information within groups accumulates as the group＇s collective set of knowledge, which may be different than the simple union of individually contained information. Furthermore, the simplicial modeling approach we propose allows us to investigate how information accumulates via sub-group interactions, offering insight into complex aspects of multi-way communication systems. The fundamental change in modeling strategy we offer here allows us to move from portraying knowledge as a ＂token＂, passed from signaler to receiver, to portraying knowledge as a set of accumulating building blocks from which novel ideas can emerge. We provide an explanation of relevant mathematical concepts in a way that promotes accessibility to a general audience [Current Zoology 61 （1）： 114--127, 2015].展开更多
The use of social network analysis to examine the behavior of social animals has grown rapidly in the past decade. Highly accessible books introducing network analysis techniques to the animal behavior research commun...The use of social network analysis to examine the behavior of social animals has grown rapidly in the past decade. Highly accessible books introducing network analysis techniques to the animal behavior research community （Croft et al., 2008; Whitehead, 2008） provide a gateway to the field. Furthermore, periodical reviews outlining the progress of the field and introducing both new biological questions and new analysis techniques （Krause et al., 2007; Wey et al., 2008; Sih et al., 2009; Croft et al,, 2011; Blonder et al., 2012; McDonald and Shizuka, 2013; Pinter-Wollman et al., 2014） fertilize the growth of the use of social network analysis to study animal social behavior.展开更多
Based on quantum modification of the general relativity (Qmoger) and on recent observations of early galaxies, it is argued that the universe was created not by a singular Big Bang, but by a continuous dynamical proce...Based on quantum modification of the general relativity (Qmoger) and on recent observations of early galaxies, it is argued that the universe was created not by a singular Big Bang, but by a continuous dynamical process of production of matter/energy from the quantum vacuum. This theory is in quantitative agreement with cosmic data (without fitting parameters) and has broad spectrum of important applications.展开更多
文摘The recently observed gravitational wave background is explained in terms of the quantum modification of the general relativity (Qmoger). Some UFO, FRB and supernova flares also can be explained in terms of Qmoger.
文摘The function of a network is affected by its structure. For example, the presence of highly interactive individuals, or hubs, influences the extent and rate of information spread across a network. In a network of interactions, the duration over which individual variation in interactions persists may affect how the network operates. Individuals may persist in their behavior over time and across situations, often referred to as personality. Colonies of social insects are an example of a biological system in which the structure of the coordinated networks of interacting workers may greatly influence information flow within the colony, and therefore its collective behavior. Here I investigate the effects of persistence in walking patterns on interaction networks us- ing computer simulations that are parameterized using observed behavior of harvester ants. I examine how the duration of persis- tence in spatial behavior influences network structure. Furthermore, I explore how spatial features of the environment affect the relationship between persistent behavior and network structure. I show that as persistence increases, the skewness of the weighted degree distribution of the interaction network increases. However, this relationship holds only when ants are confined in a space with boundaries, but not when physical barriers are absent. These findings suggest that the influence of animal personalities on network structure and function depends on the environment in which the animals reside [Current Zoology 61 （1）： 98-106, 2015].
文摘A predominant benefit of social living is the ability to share knowledge that cannot be gained through the information an individual accumulates based on its personal experience alone. Traditional computational models have portrayed sharing knowledge through interactions among members of social groups via dyadic networks. Such models aim at understanding the percolation of information among individuals and groups to identify potential limitations to successful knowledge transfer. How- ever, because many real-world interactions are not solely pairwise, i.e., several group members may obtain information from one another simultaneously, it is necessary to understand more than dyadic communication and learning processes to capture their full complexity. We detail a modeling framework based on the simplicial set, a concept from algebraic topology, which allows elegant encapsulation of multi-agent interactions. Such a model system allows us to analyze how individual information within groups accumulates as the group＇s collective set of knowledge, which may be different than the simple union of individually contained information. Furthermore, the simplicial modeling approach we propose allows us to investigate how information accumulates via sub-group interactions, offering insight into complex aspects of multi-way communication systems. The fundamental change in modeling strategy we offer here allows us to move from portraying knowledge as a ＂token＂, passed from signaler to receiver, to portraying knowledge as a set of accumulating building blocks from which novel ideas can emerge. We provide an explanation of relevant mathematical concepts in a way that promotes accessibility to a general audience [Current Zoology 61 （1）： 114--127, 2015].
文摘The use of social network analysis to examine the behavior of social animals has grown rapidly in the past decade. Highly accessible books introducing network analysis techniques to the animal behavior research community （Croft et al., 2008; Whitehead, 2008） provide a gateway to the field. Furthermore, periodical reviews outlining the progress of the field and introducing both new biological questions and new analysis techniques （Krause et al., 2007; Wey et al., 2008; Sih et al., 2009; Croft et al,, 2011; Blonder et al., 2012; McDonald and Shizuka, 2013; Pinter-Wollman et al., 2014） fertilize the growth of the use of social network analysis to study animal social behavior.
文摘Based on quantum modification of the general relativity (Qmoger) and on recent observations of early galaxies, it is argued that the universe was created not by a singular Big Bang, but by a continuous dynamical process of production of matter/energy from the quantum vacuum. This theory is in quantitative agreement with cosmic data (without fitting parameters) and has broad spectrum of important applications.
