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In this paper, we have tried to point out the features of the correlation between the lanes of a two-lane road, created by the entry of this facility. For this purpose, we have adopted a quasi-one-dimensional system composed of a diverging node connecting two roads and where no lanes’ changing is allowed. Our study has highlighted the strong effect of a node. We have found that if we create a disturbance in one lane, a spontaneous symmetry breaking occurs in the whole system. In fact, a self-anisotropy is produced at the node, to which the system responds via a self-organization mechanism. Those results have urged us to investigate the anisotropy as an extrinsic parameter. By privileging one lane over the other at the node, we have been able to confirm that the system can always get self-organized and that three phases can be established: the symmetric high density phase, the asymmetric low density phase and the asymmetric phase of transition low density/high density. Finally, we have found that the system is strongly correlated when it is in a symmetric phase, and is not when in an asymmetric phase. This finding brought us to the assumption that the cross-correlation of the observables of a quasi-one-dimensional system can be considered as an order parameter that defines the phases’ transitions.

Multi-hop teleportation is a quantum teleportation scheme for transferring quantum states on a large scale. In this paper, a new multi-hop teleportation protocol is investigated for transferring arbitrary N-qubit states between M-neighbor nodes. In this scheme, intermediate nodes are connected with each other by symmetric entangled Bell states as quantum channels. First, one-hop teleportation of single-qubit, two-qubit and N-qubit states are introduced, then this method is generalized to two-hop and multi-hop teleportation for N-qubit. Also, we calculate the efficiency of this scheme.

When the network is subject to intrusion and attack, the node output channel equalization will be affected, resulting in bit error and distortion in the output of network transmission symbols. In order to improve the anti-attack ability and equalization of network node, a network intrusion feature map node equalization algorithm based on modified variable step-size constant modulus blind equalization algorithm (MISO-VSS-MCMA) is proposed. In this algorithm, the node transmission channel model after network intrusion is constructed, and sequential processing is performed to intruded nodes with the variable structure feedback link control method. With diversity spread spectrum technology, the channel loss after network intrusion is compensated and the network intrusion map feature is extracted. According to the extracted feature amount, channel equalization processing is performed for the cost function with the MISO-VSS-MCMA method to reduce the damage of network intrusion to the channel. Simulation results show that in node transmission channel equalization after network intrusion, this algorithm can reduce the error bit rate of signal transmission in network, and provide a good ability of correcting phase deflection in the output constellation, thus avoiding the error bit distortion and channel damage caused by network intrusion to the signal with a good equalization effect. This algorithm provides stronger convergence and map concentration, which demonstrates that its anti-interference and signal recovery capabilities are better, so it improves the anti-attack ability of the network.

We consider the class of polynomial differential equations ẋ = λx + P_n(x, y), ẏ = μy + Q_n(x, y) in ℝ² where P_n(x, y) and Q_n(x, y) are homogeneous polynomials of degree n > 1 and λ ≠ μ, i.e. the class of polynomial differential systems with a linear node with different eigenvalues and homogeneous nonlinearities. For this class of polynomial differential equations, we study the existence and nonexistence of limit cycles surrounding the node localized at the origin of coordinates.

The general relativistic Lense–Thirring effect can be detected by means of a suitable combination of orbital residuals of the laser-ranged LAGEOS and LAGEOS II satellites. While this observable is not affected by the orbital perturbation induced by the zonal Earth solid and ocean tides, it is sensitive to those generated by the tesseral and sectorial tides. The assessment of their influence on the measurement of the parameter μ_LT, with which the gravitomagnetic effect is accounted for, is the goal of this paper. After simulating the combined residual curve by calculating accurately the mismodeling of the more effective tidal perturbations, it has been found that, while the solid tides affect the recovery of μ_LT at a level always well below 1%, for the ocean tides and the other long-period signals Δμ depends strongly on the observational period and the noise level: Δμ_tides ≃ 2% after seven years. The aliasing effect of K₁1=3 p=1 tide and SRP(4241) solar radiation pressure harmonic, with periods longer than four years, on the perigee of LAGEOS II yield to a maximum systematic uncertainty on μ_LT of less than 4% over different observational periods. The zonal 18.6-year tide does not affect the combined residuals.

This paper presents a technique for the enumeration of minimal paths of two-terminal networks. The method is developed based on the multiway tree structure that has been used widely for sorting and searching. The new technique does not require any matrix multiplication; it only requires a connection matrix. Furthermore, this simple method has capability of evaluating the reliability of a network after a topological modification, without going through the entire evaluation process. The method is compared with the existing algorithms, and the application simplicity of this method is demonstrated through examples.

Two concepts have long dominated vertebrate nerve electrophysiology: (a) Schwann cell-formed myelin sheaths separated by minute non-myelinated nodal gaps and spiraling around axons of peripheral motor nerves reduce current leakage during propagation of trains of axon action potentials; (b) "jumping" by action potentials between successive nodes greatly increases signal conduction velocity. Long-held and more recent assumptions and issues underlying those concepts have been obscured by research emphasis on axon-sheath biochemical symbiosis and nerve regeneration. We hypothesize: mutual electromagnetic induction in the axon-glial sheath association, is fundamental in signal conduction in peripheral and central myelinated axons, explains the g-ratio and is relevant to animal navigation.

A pathway is a collection of two or more proteins/molecules connected by their interactions within and around a cell. We study the informatics and evolutionary issues of pathways. Similar to the definition of homology in the comparison of nucleotide and protein sequences, we define homologous pathways as pathways that are evolved from the same ancestral pathway. We first present a survey of existing pathway databases and discuss their format of pathway representation. Then, our pathway representation, the SLIPR format, is presented. It is a semilinear graphic representation of nodes (proteins) and modes (interactions). Pathways in SLIPR format enable pathway comparisons for evolutionary relationship and large-scale pathway database searches. We also discuss how one can map out orthologous pathways, achieving a predictive power on functional assignment of novel genes, once the pathway is understood well-enough in a closely-related species.

The first section of this chapter is an introduction to relativistic complexity (a significant component of the intelligent organization theory). The presence of intense intelligence/consciousness-centricity and 3^rd order stability-centricity in the human world renders complexity relativistic. The impact of the human mental space is so tremendous that complexity is in the mind of the beholder, and predictability becomes highly subjective. In this situation, the state of relativistic static equilibrium may be beneficial. Certain spaces of complexity appear as spaces of relativistic order with surface patterns becoming more apparent. Such spaces must be creatively explored and exploited (higher exploratory capacity) leading to a more advanced level of intelligence advantage. In this respect, effective self-transcending constructions, high self-organizing capacity and emergence-intelligence capacity are significant attributes that the new leadership and governance system in intelligent human organizations must exploit. Holistically, the two strategies focus on concurrent exploitation of intelligence/consciousness-centricity and relative complexity, and optimizing the more comprehensive contributions of the integrated deliberate and emergent strategy.

Many issues/problems that present human organizations (nations, political systems, communities, business organizations, markets) are encountering due to accelerating changes (mindset, thinking, values, perceptions, expectations, redefined boundaries and high interactive dynamics) that cannot be well-managed with traditional knowledge and hierarchical practices are affecting governance and governance systems. Fundamentally, governance deals with power, interest, and conflict. The traditional governance systems are hierarchical, highly directed, controlled and managed, and the relational aspect has not been allocated sufficient priority resulting in extensive disparities. In the current complex dynamical and high interdependency environment, its weaknesses and constraints are highly apparent. The latter includes ‘space-time compression’; incoherency in thinking, values, perceptions, and expectations between the leadership and the other agents; diversification in stakeholders’ needs not accommodated; and constraints of current governance theories. Thus, a new theory that provides a more ‘realistic’ foundation is essential for deeper contemplation.

Primarily, recognizing the inherent strengths of human agents and the fundamental constraints/weaknesses of human organizations is a key foundation towards better adaptation, leadership, governance, resilience and sustainability. In all human organizations, the agents are intrinsic intense intelligence/consciousness sources that could easily transform their behavioral schemata. This observation contradicts the Newtonian/design paradigm, as the organizational dynamic of human agents is complex, nonlinear, constantly/continuously changing with limited predictability. In addition, human agents are self-centric, self-powered, stability-centric, independent and interdependent, network-centric and self-organizing due to high awareness. In this situation, high self-organizing capacity and emergence-intelligence capacity are new niches. However, this phenomenon can create new opportunities, innovation, and elevates competiveness; or destruction.

In particular, effective leadership and governance are spontaneously emerging key requirements in all human groupings — a primary trait for human collective survival. Historically, many organizations disintegrated because of the weaknesses in leadership and governance. Currently, with more knowledge-intensive and higher participative new agents (self-powered intrinsic leadership) possessing modified attributes that are dissimilar from the older generations (also due to the deeper integration of the economic, social, political, and environmental perspective), reduces consensus and collaboration, and renders governance and leadership even more nonlinear or dysfunctional. In particular, the traditional governance systems of more organizations are manifesting their constraints and incompetency, including incoherency due to new values and cultural pressure, and the wider spread of self-organizing networks. The emergent of informal networks is a more commonly observed phenomenon worldwide. Apparently, a deeper comprehension on the diminishing effect of the traditional organizational thinking (political, social, economic), governance capacity, precise strategic planning, decision making, hierarchical structure, communications and engagement, empowerment leadership, management, operations, and the highly nonlinear relational parameter is essential. Apparently, new principles of governance must emerge (intelligent human organization > thinking system + feeling system).

The new paradigmatic path of the intelligence governance strategy that exploits intelligence/consciousness-centricity, complexity-centricity, and network-centricity concurrently, introduces a new basic strategic path towards better adaptive governance and acceptance governance. The latter focuses on integrating self-powered self-organizing governance, reducing direct governance, and increasing e-governance and network-centric governance as a new necessity. In this case, the merits of adopting the intelligence leadership strategic approach simultaneously are more apparent. Hence, the new governance focal points must include more and better interconnected actors, the critical ability of self-organizing communications (supported by mobile/social media development), immersion of leadership nodes in networks (better exploitation of e-governance), increasing coherency of complex networks (exploiting interdependency of network of networks, and better network management), and elevating self-transcending constructions capability (higher self-organizing governance capacity and emergence-intelligence capacity) that better facilitates emergence through multi-level and ‘multi-lateral’ dynamics (complex adaptive networks <=> intelligent networks). Thus, the intelligence governance strategy emphasizes that mass lateral collectivity (acceptance governance) rather than selective enforced hierarchical empowerment as the more constructive approach in the present contact. In particular, the stabilityinducing role of leaders and institutions are critical. Apparently, optimizing the ‘everybody is in charge’ phenomenon (whenever necessary) is a more viable option.