Connection Rules Research Articles

Impacts of Hierarchy in Ethernet Ring Networks on Service Resiliency

In transport networks, a multi-ring architecture is very useful to facilitate network planning and to design and provide more resilient services for customers. Unlike traditional synchronous optical network multi-rings, the service resiliency of Ethernet-based multi-rings is significantly impacted by the ring hierarchy because a link or node failure in a certain level ring triggers filtering database flush actions in all higher level rings as well as in the ring with the failure, and consequently a large amount of duplicated data frames may be flooded. In this paper, we investigate how the ring hierarchy impacts the service resiliency of multi-ring networks. Based on extensive experiments on various single- and multiple-link failures, we suggest two effective inter-ring connection rules to minimize the transient traffic and to ensure more resilient multi-ring networks. In addition, we consider a flush optimization technique called e-ADV, and show that the combination of e-ADV and multi-ring structures satisfying our inter-ring connection rules results in a more attractive survivability performance.

Impacts of Hierarchy in Ethernet Ring Networks on Service Resiliency

In transport networks, a multi-ring architecture is very useful to facilitate network planning and to design and provide more resilient services for customers. Unlike traditional synchronous optical network multi-rings, the service resiliency of Ethernet-based multi-rings is significantly impacted by the ring hierarchy because a link or node failure in a certain level ring triggers filtering database flush actions in all higher level rings as well as in the ring with the failure, and consequently a large amount of duplicated data frames may be flooded. In this paper, we investigate how the ring hierarchy impacts the service resiliency of multi-ring networks. Based on extensive experiments on various single- and multiple-link failures, we suggest two effective inter-ring connection rules to minimize the transient traffic and to ensure more resilient multi-ring networks. In addition, we consider a flush optimization technique called e-ADV, and show that the combination of e-ADV and multi-ring structures satisfying our inter-ring connection rules results in a more attractive survivability performance.

A functional scaffold of CNS neurons for the vertebrates: The developing Xenopus laevis spinal cord

In young and developing amphibians and fish the spinal cord is functional but remarkably simple compared with the adult. Is the pattern of neurons and their connections common across at least these lower vertebrates? Does this basic pattern extend into the brainstem? Could the development of simple functioning neuronal networks depend on very basic rules of connectivity and act as pioneer networks providing a substrate for the development of more complex and subtle networks. In this review of the functional neuron classes in the Xenopus laevis tadpole spinal cord up to hatching, we will consider progress and difficulties in using anatomy, transcription factor expression, physiology, and activity to define spinal neuron types. Even here it is not straightforward and is rarely possible to bring all the different strands of evidence together. But, we think we have a rather complete picture of the hatchling tadpole spinal neuron types and can define clear roles for most of them in behavior. Our present knowledge about the hatchling Xenopus spinal cord should set up many of the problems to be unraveled in the future by more developmentally oriented research.

Integrating multidirectional connectivity requirements in systematic conservation planning for freshwater systems

AbstractAim Recent efforts to apply the principles of systematic conservation planning to freshwater ecosystems have focused on the special connected nature of these systems as a way to ensure adequacy (long‐term maintenance of biodiversity). Connectivity is important in maintaining biodiversity and key ecological processes in freshwater environments and is of special relevance for conservation planning in these systems. However, freshwater conservation planning has focused on longitudinal connectivity requirements within riverine ecosystems, while other habitats, such as floodplain wetlands or lakes and connections among them, have been overlooked. Here, we address this gap by incorporating a new component of connectivity in addition to the traditional longitudinal measure.Location Northern Australia.Methods We integrate lateral connections between freshwater areas (e.g. lakes and wetlands) that are not directly connected by the river network and the longitudinal upstream–downstream connections. We demonstrate how this can be used to incorporate ecological requirements of some water‐dependent taxa that can move across drainage divides, such as waterbirds.Results When applied together, the different connectivity rules allow the identification of priority areas that contain whole lakes or wetlands, their closest neighbours whenever possible, and the upstream/downstream reaches of rivers that flow into or from them. This would facilitate longitudinal and lateral movements of biota while minimizing the influence of disturbances potentially received from upstream or downstream reaches.Main conclusions This new approach to defining and applying different connectivity rules can help improve the adequacy of freshwater‐protected areas by enhancing movements of biodiversity within priority areas. The integration of multiple connectivity needs can also serve as a bridge to integrate freshwater and terrestrial conservation planning.

Ontology based interface design and control methodology for collaborative product development

Interfaces between subsystems in collaborative product development projects are presently defined by interface control documents. This paper presents a computer aided methodology for defining and controlling subsystem interfaces. Interfaces are considered as interconnections between subsystem ports. Ports are specified by using an ontology that ensures consistency of interface definitions among different design teams. Every port that is based on the ontology is eventually defined by a set of attributes that are derived from its form and function. Interfaces between ports are formed when ports are mated. The essence of port mating is described by logical information that is expressed in two forms. First, a set of requirements are defined for an individual port to ensure that it functions properly. Second, connectivity rules are expressed between ports to guarantee that they integrate correctly. A software architecture that operates on port information and controls the status of subsystem interfaces during collaboration is described. A piece of software is implemented based on the proposed architecture and its functionality is demonstrated by two examples. The examples show how the software can be used to replace interface control documents and support collaboration. The software allows designers to load subsystem descriptions from a shared repository and connect them together by defining connectivity rules. The software reports errors to designers when port requirements or connectivity rules are violated.

Isolated Single Primary Winding Multiple-Input Converters

Multiple-input converters (MICs) have attracted more attentions because of its simpler structure and less devices. In the traditional isolated MICs, each input source always has a primary winding, sharing a secondary winding. When the number of the input sources increases, the number of the primary windings increases, resulting in complicated structure of the transformer, poor coupling, and large leakage inductors. This paper first introduces the concept of pulsating source cells (PSCs), including pulsating voltage source cells and pulsating current source cells, and the connection rules for the PSCs. Then, series- or parallel-connected PSCs are used to replace the input dc voltage source or input dc current source in the isolated single-input converter, and a family of isolated single primary winding (SPW) MICs is proposed. Compared to the traditional isolated MICs, the transformer has only one primary winding, leading to a simplified structure and ease for manufacturing. Furthermore, the voltage stress of the power switches is reduced. The control method of the proposed isolated SPW MICs is proposed. Finally, a flyback SPW double-input converter is analyzed as an example. The operation principle and control method are discussed and a prototype is built to demonstrate the feasibility of this topology.

Activity-Dependent Clustering of Functional Synaptic Inputs on Developing Hippocampal Dendrites

During brain development, before sensory systems become functional, neuronal networks spontaneously generate repetitive bursts of neuronal activity, which are typically synchronized across many neurons. Such activity patterns have been described on the level of networks and cells, but the fine-structure of inputs received by an individual neuron during spontaneous network activity has not been studied. Here, we used calcium imaging to record activity at many synapses of hippocampal pyramidal neurons simultaneously to establish the activity patterns in the majority of synapses of an entire cell. Analysis of the spatiotemporal patterns of synaptic activity revealed a fine-scale connectivity rule: neighboring synapses (<16μm intersynapse distance) are more likely to be coactive than synapses that are farther away from each other. Blocking spiking activity or NMDA receptor activation revealed that the clustering of synaptic inputs required neuronal activity, demonstrating a role of developmentally expressed spontaneous activity for connecting neurons with subcellular precision.

Large-Scale Automated Histology in the Pursuit of Connectomes

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

Off-shell D = 5, = 2 Riemann squared supergravity

We construct a new off-shell invariant in supergravity whose leading term is the square of the Riemann tensor. It contains a gravitational Chern–Simons term involving the vector field that belongs to the supergravity multiplet. The action is obtained by mapping the transformation rules of a spin connection with bosonic torsion and a set of curvatures to the fields of the Yang–Mills multiplet with gauge group SO(4, 1). We also employ the circle reduction of an action that describes locally supersymmetric Yang–Mills theory in six dimensions.

A Perimotor Framework Reveals Functional Segmentation in the Motoneuronal Network Controlling Locomotion inCaenorhabditis elegans

The neuronal connectivity dataset of the nematode Caenorhabditis elegans attracts wide attention from computational neuroscientists and experimentalists. However, the dataset is incomplete. The ventral and dorsal nerve cords of a single nematode were reconstructed halfway along the body and the posterior data are missing, leaving 21 of 75 motoneurons of the locomotor network with partial or no connectivity data. Using a new framework for network analysis, the perimotor space, we identified rules of connectivity that allowed us to approximate the missing data by extrapolation. Motoneurons were mapped into perimotor space in which each motoneuron is located according to the muscle cells it innervates. In this framework, a pattern of iterative connections emerges which includes most (0.90) of the connections. We identified a repeating unit consisting of 12 motoneurons and 12 muscle cells. The cell bodies of the motoneurons of such a unit are not necessarily anatomical neighbors and there is no obvious anatomical segmentation. A connectivity model, composed of six repeating units, is a description of the network that is both simplified (modular and without noniterative connections) and more complete (includes the posterior part) than the original dataset. The perimotor framework of observed connectivity and the segmented connectivity model give insights and advance the study of the neuronal infrastructure underlying locomotion in C. elegans. Furthermore, we suggest that the tools used herein may be useful to interpret, simplify, and represent connectivity data of other motor systems.

Intuitionistic Logic and Elementary Rules

The interplay of introduction and elimination rules for propositional connectives is often seen as suggesting a distinguished role for intuitionistic logic. We prove three formal results concerning intuitionistic propositional logic that bear on that perspective, and discuss their significance. First, for a range of connectives including both negation and the falsum, there are no classically or intuitionistically correct introduction rules. Second, irrespective of the choice of negation or the falsum as a primitive connective, classical and intuitionistic consequence satisfy exactly the same structural, introduction, and elimination (briefly, elementary) rules. Third, for falsum as primitive only, intuitionistic consequence is the least consequence relation that satisfies all classically correct elementary rules.

Biswapped networks: a family of interconnection architectures with advantages over swapped or OTIS networks

We propose a new family of communication architectures called ‘biswapped networks’. Given any n-node basis network Ω, the associated biswapped network Bsw(Ω) is built of 2n copies of Ω, using a simple rule for connectivity that ensures desirable attributes, including regularity, modularity, fault tolerance, and algorithmic efficiency. In particular, if Ω is a Cayley digraph, then so is Bsw(Ω). Our biswapped connectivity provides a systematic scheme for synthesizing large, scalable, modular, and robust parallel architectures. Furthermore, many desirable attributes of the underlying basis network Ω are preserved, as the Bsw(Ω) parameters are related to the corresponding parameters of Ω. We obtain a number of results on internode distances, Hamiltonian cycles, optimal routing, and node-disjoint paths for Bsw(Ω). We explore the relations between biswapped and swapped or optical transpose interconnection system (OTIS) networks, which may use a mix of electronic and optical links. In particular, we demonstrate that the biswapped connectivity removes an inherent asymmetry of swapped/OTIS networks, as well as the attendant complications in analyses and applications. Finally, we show that biswapped networks are complementary to, and offer advantages over, well-known and widely used interconnection architectures for parallel processing.

Boundary representation of neural architecture and connectivity

The general objective of this work is to develop a description language for constructive 3D boundary representation [5] of neuroanatomical structures and connectivity at various levels of granularity (from coarse-resolution solids to fine meshes). This approach is motivated by a desire to capture regularities in neural circuitry as revealed by neuro-architectonic studies [4], while at the same time to explore hypotheses about anatomic variability of various origins, such as experimental uncertainties, cross species scaling factors, individual differences, and assess them for their impact on connectivity, and ultimately on network dynamics. Boundary representation is a general approach to describe 3D objects solely by their surface. Boundary representations consist of topological objects and their concrete geometrical representations in terms of enclosing boundaries. Topological elements include vertices, edges and faces, with corresponding geometrical elements being points, curves, and surfaces. The relationships between topological elements in a structure are expressed by means of a graph of topological connections. The description language is being implemented on top of the GNU Triangulated Surface library [3], and provides the ability to: • Specify compound topological objects with parametric geometry; • Specify geometric parameters for the instantiation of topological objects, such as coordinates for placement, or probability distributions for random placement of a group of identical objects; • Specify individual coordinate systems for different cell populations; • Define categories of topological objects, such as stellate, basket and Golgi cells, which may be part of a morphological continuum; • Define rules for connectivity between different categories of objects. We present the anisotropic cerebellar circuitry as a case study, and define boundary representations of the arrangement of Purkinje and Golgi cells in the cerebellar cortex. We use the hexagonal grid pattern suggested by Palkovits et al. in [1,2], while allowing for small variability in the placement of cells within a hexagon. The implementation of the language instantiates the topological objects, computes the intersections of the resulting surfaces, and given connectivity rules for the different categories of objects, computes the potential synaptic connectivity (producing graph theoretical measures, as well as connectivity histograms), and ultimately aims to generate connectivity descriptions for the NEURON simulator.

Tracking Controller Design for Nonlinear Dynamic Systems via Fuzzy Association Rule Reduction

One of the conventional significant criteria to be considered in real-time control applications is the computational complication of the controllers. The major weakness of fuzzy data mining is that after applying fuzzy data mining on the quantitative data, the number of extracted fuzzy association rules is very enormous. When many connection rules are obtained, the value of them will be reduced. This paper presents structures and a systematical progress method for two degree of freedom fuzzy controllers with nonhomogenous dynamics with respect to the two input channels. In this paper, singular value decomposition (SVD)-based complexity reduction technique and a reduced modified fuzzy logic controller (MFLC) are proposed. We introduce an approach to reduce and summarize the extracted fuzzy association rules after fuzzy data mining. Matlab/Simulink software is used to simulate the mathematical model of the Gun Turret-Barrel dynamic system. Different controllers are applied to the system. A comparison is introduced among the system performances under the control of each of FLC, a reduced FLC (in the number of membership functions and rules by using SVD method), and a reduced MFLC (reduction in the number of rules and modification in the shape of the membership functions by observing the system performance). The analysis points out that the proposed MFLC can ensure better control system performance with respect to the reference input in comparison with other controllers.

Searching substructures in fragment spaces

A common task in drug development is the selection of compounds fulfilling specific structural features from a large data pool. While several methods that iteratively search through such data sets exist, their application is limited compared to the infinite character of molecular space. The introduction of the concept of fragment spaces (FSs), which are composed of molecular fragments and their connection rules, made the representation of large combinatorial data sets feasible. At the same time, search algorithms face the problem of structural features spanning over multiple fragments. Due to the combinatorial nature of FSs, an enumeration of all products is impossible. In order to overcome these time and storage issues, we present a method that is able to find substructures in FSs without explicit product enumeration. This is accomplished by splitting substructures into subsubstructures and mapping them onto fragments with respect to fragment connectivity rules. The method has been evaluated on three dif...

A Framework to Model the Topological Structure of Supply Networks

Topological structure is considered more and more important in managing a supply network or predicting its development. In this paper, a new framework is proposed to model the topological structure of supply networks, where different types of supply networks can be created just by introducing different supplier-customer connecting rules. Generally, the networks created in the framework are much different from the random networks with the same degree sequences. The revealed phenomenon suggests that real-world supply networks may benefit from its intrinsic mechanism on flexibility, efficiency, and robustness to target attacks. Note to Practitioners-The topological structure of supply networks is considered more and more important in managing a supply network or predicting its development. In this paper, we introduce a framework to model and analyze the topological structure of supply networks. This work aims to characterize supply networks by statistical methods and can help researchers better understand the material dynamics on supply networks and further conveniently create their own supply networks by summarizing practical supplier-customer connecting rules or analyzing real-world supply network data. The work should be further expanded in other aspects, such as simulating material dynamics on supply networks, designing optimal structure by introducing proper supplier-customer connecting rules, rearranging local connections to enhance the competi tiveness and further ensure the long-term benefit of a target firm, and so on, all of which are of much interest for governors, investors, and managers and can be studied in the present framework in the future.

Distance Dependence of Neuronal Growth on Nanopatterned Gold Surfaces

Understanding network development in the brain is of tremendous fundamental importance, but it is immensely challenging because of the complexity of both its architecture and function. The mechanisms of axonal navigation to target regions and the specific interactions with guidance factors such as membrane-bound proteins, chemical gradients, mechanical guidance cues, etc., are largely unknown. A current limitation for the study of neural network formation is the ability to control precisely the connectivity of small groups of neurons. A first step in designing such networks is to understand the "rules" central nervous system (CNS) neurons use to form functional connections with one another. Here we begin to delineate novel rules for growth and connectivity of small numbers of neurons patterned on Au substrates in simplified geometries. These studies yield new insights into the mechanisms determining the organizational features present in intact systems. We use a previously reported atomic force microscopy (AFM) nanolithography method to control precisely the location and growth of neurons on these surfaces. By examining a series of systems with different geometrical parameters, we quantitatively and systematically analyze how neuronal growth depends on these parameters.

Monosynaptic Rabies Virus Reveals Premotor Network Organization and Synaptic Specificity of Cholinergic Partition Cells

Movement is the behavioral output of neuronal activity in the spinal cord. Motor neurons are grouped into motor neuron pools, the functional units innervating individual muscles. Here we establish an anatomical rabies virus-based connectivity assay in early postnatal mice. We employ it to study the connectivity scheme of premotor neurons, the neuronal cohorts monosynaptically connected to motor neurons, unveiling three aspects of organization. First, motor neuron pools are connected to segmentally widely distributed yet stereotypic interneuron populations, differing for pools innervating functionally distinct muscles. Second, depending on subpopulation identity, interneurons take on local or segmentally distributed positions. Third, cholinergic partition cells involved in the regulation of motor neuron excitability segregate into ipsilaterally and bilaterally projecting populations, the latter exhibiting preferential connections to functionally equivalent motor neuron pools bilaterally. Our study visualizes the widespread yet precise nature of the connectivity matrix for premotor interneurons and reveals exquisite synaptic specificity for bilaterally projecting cholinergic partition cells.

Least cost distance analysis for spatial interpolation

Spatial interpolation allows creation of continuous raster surfaces from a subsample of point-based measurements. Most interpolation approaches use Euclidean distance measurements between data points to generate predictions of values at unknown locations. However, there are many spatially distributed data sets that are not properly represented by Euclidean distances and require distance measures which represent their complex geographic connectivity. The problem of defining non-Euclidean distances between data points has been solved using the network-based solutions, but such techniques have historically relied on a network of connected line segments to determine point-to-point distances. While these vector-based solutions are computationally efficient, they cannot model more complex 2- and 3-dimensional systems of connectivity. Here, we use least-cost-path analyses to define distances between sampled points; a solution that allows for arbitrarily complex systems of connectivity to be interpolated. We used least-cost path distances in conjunction with the inverse distance weighting interpolation for a proof-of-concept interpolation of water temperature data in a complex deltaic river system. We compare our technique to Euclidean distance interpolation, and demonstrate that our technique, which follows connectivity rules, yields are more realistic interpolation of water temperature.

Extending the Resource-based View to the Mega-event: Entrepreneurial Rents and Innovation

The resource-based view of the firm has previously been expanded by including relational rents and rent from network and alliance participation. This paper extends the Dyer-Singh-Lavie synthesis by considering the special circumstances arising from the relationships, alliances, and networks of a mega-event, using the Beijing Olympics as a case for our analyses. The mega-event that is organized as a cartel increases the pricing power of the participants, produces relational rent, and is an ideal venue to introduce innovations. We discuss six factors that can influence the rent creation and capture from a mega-event and offer related propositions: periodicity (Proposition 1), event location (Proposition 2), governance structure (Proposition 3), media coverage (Proposition 4), network connectivity (Proposition 5), and membership rules (Proposition 6). We identify four innovation types associated with such mega-events and contend that the same factors can affect the entrepreneurial rent creation and capture within these innovation types (Proposition 7).