Information Flow Paths Research Articles

Information Flow Networks of Chinese Stock Market Sectors

Transfer entropy measures the strength and direction of information flow between different time series. We study the information flow networks of the Chinese stock market and identify important sectors and information flow paths. This paper uses the daily closing price data of the 28 level-1 sectors from Shenyin \& Wanguo Securities ranging from 2000 to 2017 to study the information transmission between different sectors. We construct information flow networks with the sectors as the nodes and the transfer entropy between them as the corresponding edges. Then we adopt the maximum spanning arborescence (MSA) to extracting important information flows and the hierarchical structure of the networks. We find that, during the whole sample period, the \textit{composite} sector is an information source of the whole stock market, while the \textit{non-bank financial} sector is the information sink. We also find that the \textit{non-bank finance}, \textit{bank}, \textit{computer}, \textit{media}, \textit{real estate}, \textit{medical biology} and \textit{non-ferrous metals} sectors appear as high-degree root nodes in the outgoing and incoming information flow MSAs. Especially, the \textit{non-bank finance} and \textit{bank} sectors have significantly high degrees after 2008 in the outgoing information flow networks. We uncover how stock market turmoils affect the structure of the MSAs. Finally, we reveal the specificity of information source and sink sectors and make a conclusion that the root node sector as the information sink of the incoming information flow networks. Overall, our analyses show that the structure of information flow networks changes with time and the market exhibits a sector rotation phenomenon. Our work has important implications for market participants and policy makers in managing market risks and controlling the contagion of risks.

Balancing Extrasynaptic Excitation and Synaptic Inhibition within Olfactory Bulb Glomeruli.

Glutamatergic transmission in the brain typically occurs at well-defined synaptic connections, but increasing evidence indicates that neural excitation can also occur through activation of “extrasynaptic” glutamate receptors. Here, we investigated the underlying mechanisms and functional properties of extrasynaptic signals that are part of a feedforward path of information flow in the olfactory bulb. This pathway involves glutamatergic interneurons, external tufted cells (eTCs), that are excited by olfactory sensory neurons (OSNs) and in turn excite output mitral cells (MCs) extrasynaptically. Using pair-cell and triple-cell recordings in rat bulb slices (of either sex), combined with ultrastructural approaches, we first present evidence that eTC-to-MC signaling results from “spillover” of glutamate released at eTC synapses onto GABAergic periglomerular (PG) cells in glomeruli. Thus, feedforward excitation is an indirect result of and must cooccur with activation of inhibitory circuitry. Next, to examine the dynamics of the competing signals, we assayed the relationship between the number of spikes in eTCs and excitation of MCs or PG cells in pair-cell recordings. This showed that extrasynaptic excitation in MCs is very weak due to single spikes but rises sharply and supralinearly with increasing spikes, differing from sublinear behavior for synaptic excitation of PG cells. Similar dynamics leading to a preference for extrasynaptic excitation were also observed during recordings of extrasynaptic and inhibitory currents in response to OSN input of increasing magnitude. The observed alterations in the balance between extrasynaptic excitation and inhibition in glomeruli with stimulus strength could underlie an intraglomerular mechanism for olfactory contrast enhancement.

Energy Consumption in Point-Coverage Wireless Sensor Networks via Bat Algorithm

Sensor nodes spend the most of their limited energy on communicating with environmental information gathered in receivers. Hence, it is important to determine the optimal monitoring sensor nodes and information flow paths to the destination and sink in order to survive the sensor networks. Additionally, the heavy traffic load for transferring packets in nodes closer to the sink increases energy consumption and reduces battery life. It is desirable to reduce the energy between nodes and sink. The main goal is to extend the network lifetime through extending the lifetime of operating sensors as well transferring gathered data from super node to the sink. In this paper, Bat Algorithm (BA) is used to select the optimum monitoring sensor node and resulted path to reduce energy consumption. Simulation results and comparison with other algorithms show the superiority of the proposed algorithm. The simulation results of the proposed algorithm show that the proposed algorithm has been able to reduce the power consumption of the network and increase the lifetime of the network. Also, the proposed algorithm is able to outperform the comparable algorithms on average by 27%.

A Decision Support System Architecture Based on Simulation Optimization for Cyber-Physical Systems

Simulation modeling (SM) is going to gain more interest due to the rise of Industry 4.0. Although, SM has been used extensively to analyze the behavior of complex manufacturing systems in a cost-efficient manner without disrupting the production process, it has many limitations that contradict with the industry 4.0 era. These limitations include; the large computational time, black-box characteristic, and not being able to directly run optimization analysis. Metamodeling combines the merits of SM and design of experiments by achieving optimal solutions at a limited computational time, and the ability to study complex systems with an explicit form and deterministic output. This paper proposes an architecture of a Decision Support System (DSS) based on a simulation metamodeling optimization approach to assist in making timely and informed decisions, using the emerging technologies of industry 4.0 and cyber-physical system concepts. The main modules and information flow path within the DSS are demonstrated in detail. To illustrate the applicability of the DSS, it has been implemented in a leading home appliance factory. The results indicate that this promising tool can easily be adopted in smart factories to aid in tactical and operational planning activities.

Neighbor Discovery and Rendezvous Maintenance with Extended Quorum Systems for Mobile Applications

In many mobile sensing applications, devices need to discover new neighbors and maintain the rendezvous with known neighbors continuously. Due to the limited energy supply, these devices have to duty cycle their radios to conserve the energy and bandwidth, making neighbor discovery and rendezvous maintenance even more challenging. To date, the main mechanism for device discover and rendezvous maintenance in existing solutions is pairwise, direct one-hop communication. We argue that such pairwise direct communication is sufficient but not necessary: there exist unnecessary active slots that can be eliminated, without affecting discovery and rendezvous. In this work, we propose a novel concept of extended quorum system , which leverages indirect discovery to further conserve energy. Specifically, we use quorum graph to capture all possible information flow paths where knowledge about known-neighbors can propagate among devices. By eliminating redundant paths, we can reduce the number of active slots significantly. Since a quorum graph can characterize arbitrary active schedules of mobile devices, our work can be broadly used to improve many existing quorum-based discovery and rendezvous solutions. We comprehensively evaluate $EQS$ in three different scales of networks, and the results show that $EQS$ reduces as much as 55 percent energy consumption with a maximal 5 percent increase in latency for existing solutions. To test the real-world values of $EQS$ , we further propose a taxicab dispatching application called $EQS$ -dispatch to navigate taxicab drivers to the area with less competition based on the discovery results of nearby taxicabs.

Harbour-side land parcel land-use changes: significance in re-development planning permit appraisal in Melbourne, Australia

Results are presented of spatial query at the land parcel level of a (digital) spatial database, referring to the twentieth century Harbour-side zone of the Port of Melbourne. They refer mainly to land-use histories of individual land parcels. Such histories can be now deployed routinely in decision support during assessment of heritage potential in aid of re-development/excavation permit appraisal.Such query has long been possible in a general way: the innovation brought forward in this presentation refers to the new level of detail that is achieved by adopting digital spatial database query. The prerequisite for such query is the kind of digital spatial database that we have built from imposing spatial compatibility on archival maps and air photos.It is argued that much interest will attach to implementing the spatial database building process exemplified in this paper for decision-making in planning permit appraisal. For instance, contaminated ground might be better identified. Modern data handling tools make this feasible in a routine way if the necessary data and information flow paths and data sharing can be arranged.

Production Improvement in an Aircraft Manufacturing Company Using Value Stream Mapping Approach

The purpose of this study is to develop a value stream mapping for a production in an aircraft manufacturing company. The process begins with creating a current state map and understands the production flow and the current cycle times. This provides the information needed to produce a future state map. The goal is to identify and eliminate the waste, which is any activity that does not add value to the final product, in the production process. In order to collect the information needed, the study was conducted within the production facility to enable the researcher gained knowledge and familiarized with the production flow and the activities being performed at the shop floor. Parameters such as cycle times, down times, work in process (WIP) for inventory and material, and information flow paths were recorded. This information will enable the researcher to visualize the current state of the process activities by mapping the material and information flow and looking for opportunities to eliminate wastes. ARENA simulation software package was used to simulate and analyze the process flow and times. Result from the analysis shows that there are areas where the company can further improve their production system. The results show the improvement of the cycle time up to 22% based on the new proposed arrangement of the layout. Therefore the propose layout will be guided to the company in order to improve their production.

Assessing direct paths of intracortical causal information flow of oscillatory activity with the isolated effective coherence (iCoh).

Functional connectivity is of central importance in understanding brain function. For this purpose, multiple time series of electric cortical activity can be used for assessing the properties of a network: the strength, directionality, and spectral characteristics (i.e., which oscillations are preferentially transmitted) of the connections. The partial directed coherence (PDC) of Baccala and Sameshima (2001) is a widely used method for this problem. The three aims of this study are: (1) To show that the PDC can misrepresent the frequency response under plausible realistic conditions, thus defeating the main purpose for which the measure was developed; (2) To provide a solution to this problem, namely the “isolated effective coherence” (iCoh), which consists of estimating the partial coherence under a multivariate autoregressive model, followed by setting all irrelevant associations to zero, other than the particular directional association of interest; and (3) To show that adequate iCoh estimators can be obtained from non-invasively computed cortical signals based on exact low resolution electromagnetic tomography (eLORETA) applied to scalp EEG recordings. To illustrate the severity of the problem with the PDC, and the solution achieved by the iCoh, three examples are given, based on: (1) Simulated time series with known dynamics; (2) Simulated cortical sources with known dynamics, used for generating EEG recordings, which are then used for estimating (with eLORETA) the source signals for the final connectivity assessment; and (3) EEG recordings in rats. Lastly, real human recordings are analyzed, where the iCoh between six cortical regions of interest are calculated and compared under eyes open and closed conditions, using 61-channel EEG recordings from 109 subjects. During eyes closed, the posterior cingulate sends alpha activity to all other regions. During eyes open, the anterior cingulate sends theta-alpha activity to other frontal regions.

INFLUENCE OF AN EDUCATIONAL FILM ON THE EFFECTIVENESS OF TECHNICAL EDUCATION

Given its capacity to stimulate several senses simultaneously, the educational film triggers many paths of information flow during the learning process. Not only does it offer a diversified form of transmitting information, but it also makes the learning pro cess more effective and attractive. This feature is particularly important in technical education, where the problems and issues discussed are often complex and difficult for students. The following paper contains an analysis of the impact of an educational film on the efficiency of technical education based on a pedagogical experiment per formed on middle school students.

Application effect of contact team in international cooperation of Chinese registered nurse-helping smokers quit project (CRN-HSQ)

Objective To complete the large international cooperation nursing research project Adapting a Smoking Cessation Intervention Distance Learning Program to Educate Nurses in China(CRN-HSQ) cooperating with International Society of Nurses in Cancer Care (ISNCC).Methods The contact team was formed,convenience sampling method was used to choose 350 clinical nurses in our hospital.They were trained and investigated by web-based education mode.Results The contact team finished the project tasks smoothly.The satisfaction degree of research object with the contact team was high.Conclusions Establishment of contact team is good for shortening the information flow path,reducing the information transmission error,increasing the research objects' confidence and reducing the research objects turnover.It is very helpful for project with long period and large number of research objects. Key words: Contact team; International cooperation project; Project management

Dynamic information flow during neutrophil polarization

While many interactions of biochemical networks have been characterized, the evolving nature of these links and their influence in shaping highly‐coordinated, multistep cellular responses is poorly understood. Here, we tracked the flow of information in the biochemical network responsible for the rapid response of primary human neutrophils to stimuli. We found that not only do paths of information flow rapidly evolve over time, but directionality depends strongly on the observed phenotype. Surprisingly, the set of persistent crosstalk revealed an underlying simplicity: a linear cascade controls signaling activity levels, and a feed‐forward network in the opposite direction controls signaling localization. Our work provides a clear example that a simple flow of information may lay hidden beneath the complexity of “everything‐connects‐to‐everything” biochemical networks.

Communication and wiring in the cortical connectome.

In cerebral cortex, the huge mass of axonal wiring that carries information between near and distant neurons is thought to provide the neural substrate for cognitive and perceptual function. The goal of mapping the connectivity of cortical axons at different spatial scales, the cortical connectome, is to trace the paths of information flow in cerebral cortex. To appreciate the relationship between the connectome and cortical function, we need to discover the nature and purpose of the wiring principles underlying cortical connectivity. A popular explanation has been that axonal length is strictly minimized both within and between cortical regions. In contrast, we have hypothesized the existence of a multi-scale principle of cortical wiring where to optimize communication there is a trade-off between spatial (construction) and temporal (routing) costs. Here, using recent evidence concerning cortical spatial networks we critically evaluate this hypothesis at neuron, local circuit, and pathway scales. We report three main conclusions. First, the axonal and dendritic arbor morphology of single neocortical neurons may be governed by a similar wiring principle, one that balances the conservation of cellular material and conduction delay. Second, the same principle may be observed for fiber tracts connecting cortical regions. Third, the absence of sufficient local circuit data currently prohibits any meaningful assessment of the hypothesis at this scale of cortical organization. To avoid neglecting neuron and microcircuit levels of cortical organization, the connectome framework should incorporate more morphological description. In addition, structural analyses of temporal cost for cortical circuits should take account of both axonal conduction and neuronal integration delays, which appear mostly of the same order of magnitude. We conclude the hypothesized trade-off between spatial and temporal costs may potentially offer a powerful explanation for cortical wiring patterns.

Information Routing Driven by Background Chatter in a Signaling Network

Living systems are capable of processing multiple sources of information simultaneously. This is true even at the cellular level, where not only coexisting signals stimulate the cell, but also the presence of fluctuating conditions is significant. When information is received by a cell signaling network via one specific input, the existence of other stimuli can provide a background activity –or chatter– that may affect signal transmission through the network and, therefore, the response of the cell. Here we study the modulation of information processing by chatter in the signaling network of a human cell, specifically, in a Boolean model of the signal transduction network of a fibroblast. We observe that the level of external chatter shapes the response of the system to information carrying signals in a nontrivial manner, modulates the activity levels of the network outputs, and effectively determines the paths of information flow. Our results show that the interactions and node dynamics, far from being random, confer versatility to the signaling network and allow transitions between different information-processing scenarios.

A neuroendocrine-inspired bionic manufacturing system

Due to rapid changes of markets and pressures of competitions, the manufacturing companies are forced to adapt their production ways to support diversity of customer’s needs and increase of new product developments. As biological organisms are quite capable of adapting to environmental changes and stimulus, bio-inspired concepts have been recognized much suitable for adaptive manufacturing system control. This paper, therefore, proposes a novel concept of NeuroEndocrine-Inspired Manufacturing System (NEIMS). The proposed NEIMS control architecture is based on analogies with neuro-control and hormone-regulation principles. It has the capability to explicitly specify production control schemes including control points, material, information flow paths and logical operations, and to agilely deal with the frequent occurrence of unexpected disturbances at the shop floor level. From the cybernetics point of view, the control model of NEIMS indicates adaptive behavior to the changes in products demands due to external environment and malfunction of manufacturing cells as an internal environment. Finally, a prototype system has been set up to enable the NEIMS simulation.

Efficient integer programming formulations for optimum sink location and routing in heterogeneous wireless sensor networks

Sensors spend most of their limited battery energy on communicating the collected environmental information to sinks. Therefore, the determination of the optimal sink locations and sensor-to-sink information flow routes becomes important for the survivability of sensor networks. In this work, we address these important design issues using an integrated approach and propose new mixed-integer linear programming models to determine the optimal sink locations and information flow paths between sensors and sinks when sensor locations are given. The first group of proposed models is energy-aware and tries to minimize total routing energy, whereas the second group is financially driven with the objective of minimizing total cost. We do not only report computational results providing information on the solution efficiency of the new formulations, and the accuracy of their linear programming relaxations, but also propose and test new heuristics and lower bounding approaches for the most efficient formulation.

A new technique for modelling production control schemes in manufacturing systems

This paper presents a new modelling technique to model continuous manufacturing systems. The new dynamic model is based on analogies with electrical systems, and it has the capability to explicitly specify production control schemes including control points, material and information flow paths, and logical operations. The electrical analogues provide an excellent tool to model control signals and logical operations. This is especially important for pull control schemes where qualitative descriptions often found in the literature can be ambiguous. The model provides standard graphical representations and governing equations to describe both the steady state and transient responses of continuous manufacturing systems. For deterministic systems, these equations can be solved to obtain closed-form solutions. For stochastic systems, numerical solutions can be obtained for any probabilistic distribution. The proposed technique is demonstrated by modelling push and a variety of pull systems.

Bickering In-Depth: Rethinking the Composition of Competing Security Systems

A vast array of security software exists, and because most of it addresses only relatively small facets of information security, it remains unclear how users should compose such software to achieve a reasonable degree of protection coverage. Furthermore, the many companies, organizations, and individuals that create such software don't design it to cooperate with similar software. We believe the resulting level of competition for resources and measurement points (kernel, library, or user hooks; disk access events; the system call API; and so on) can unnecessarily degrade system performance and interfere with the efficacy of the systems themselves. In essence, the broad call for defense in-depth can exacerbate existing performance and usability problems and lead to an unintentional loss of security. We suggest a paradigm in which security programmers intentionally design their code to cooperate with similar software by negotiating over security-critical resources, system measurement points, event types, and trusted information flow paths.

Merlin

The last several years have seen a proliferation of static and runtime analysis tools for finding security violations that are caused by explicit information flow in programs. Much of this interest has been caused by the increase in the number of vulnerabilities such as cross-site scripting and SQL injection. In fact, these explicit information flow vulnerabilities commonly found in Web applications now outnumber vulnerabilities such as buffer overruns common in type-unsafe languages such as C and C++. Tools checking for these vulnerabilities require a specification to operate. In most cases the task of providing such a specification is delegated to the user. Moreover, the efficacy of these tools is only as good as the specification. Unfortunately, writing a comprehensive specification presents a major challenge: parts of the specification are easy to miss, leading to missed vulnerabilities; similarly, incorrect specifications may lead to false positives. This paper proposes Merlin, a new approach for automatically inferring explicit information flow specifications from program code. Such specifications greatly reduce manual labor, and enhance the quality of results, while using tools that check for security violations caused by explicit information flow. Beginning with a data propagation graph, which represents interprocedural flow of information in the program, Merlin aims to automatically infer an information flow specification. Merlin models information flow paths in the propagation graph using probabilistic constraints. A naive modeling requires an exponential number of constraints, one per path in the propagation graph. For scalability, we approximate these path constraints using constraints on chosen triples of nodes, resulting in a cubic number of constraints. We characterize this approximation as a probabilistic abstraction, using the theory of probabilistic refinement developed by McIver and Morgan. We solve the resulting system of probabilistic constraints using factor graphs, which are a well-known structure for performing probabilistic inference. We experimentally validate the Merlin approach by applying it to 10 large business-critical Web applications that have been analyzed with CAT.NET, a state-of-the-art static analysis tool for .NET. We find a total of 167 new confirmed specifications, which result in a total of 322 additional vulnerabilities across the 10 benchmarks. More accurate specifications also reduce the false positive rate: in our experiments, Merlin-inferred specifications result in 13 false positives being removed; this constitutes a 15% reduction in the CAT.NET false positive rate on these 10 programs. The final false positive rate for CAT.NET after applying Merlin in our experiments drops to under 1%.

DEX-1 and DYF-7 Establish Sensory Dendrite Length by Anchoring Dendritic Tips during Cell Migration

Cells are devices whose structures delimit function. For example, in the nervous system, neuronal and glial shapes dictate paths of information flow. To understand how cells acquire their shapes, we examined the formation of a sense organ in C. elegans. Using time-lapse imaging, we found that sensory dendrites form by stationary anchoring of dendritic tips during cell-body migration. A genetic screen identified DEX-1 and DYF-7, extracellular proteins required for dendritic tip anchoring, which act cooperatively at the time and place of anchoring. DEX-1 and DYF-7 contain, respectively, zonadhesin and zona pellucida domains, and DYF-7 self-associates into multimers important for anchoring. Thus, unlike other dendrites, amphid dendritic tips are positioned by DEX-1 and DYF-7 without the need for long-range guidance cues. In sequence and function, DEX-1 and DYF-7 resemble tectorins, which anchor stereocilia in the inner ear, suggesting that a sensory dendrite anchor may have evolved into part of a mechanosensor.

First approaches towards modelling glacial hazards in the Mount Cook region of New Zealand's Southern Alps

Abstract. Flood and mass movements originating from glacial environments are particularly devastating in populated mountain regions of the world, but in the remote Mount Cook region of New Zealand's Southern Alps minimal attention has been given to these processes. Glacial environments are characterized by high mass turnover and combined with changing climatic conditions, potential problems and process interactions can evolve rapidly. Remote sensing based terrain mapping, geographic information systems and flow path modelling are integrated here to explore the extent of ice avalanche, debris flow and lake flood hazard potential in the Mount Cook region. Numerous proglacial lakes have formed during recent decades, but well vegetated, low gradient outlet areas suggest catastrophic dam failure and flooding is unlikely. However, potential impacts from incoming mass movements of ice, debris or rock could lead to dam overtopping, particularly where lakes are forming directly beneath steep slopes. Physically based numerical modeling with RAMMS was introduced for local scale analyses of rock avalanche events, and was shown to be a useful tool for establishing accurate flow path dynamics and estimating potential event magnitudes. Potential debris flows originating from steep moraine and talus slopes can reach road and built infrastructure when worst-case runout distances are considered, while potential effects from ice avalanches are limited to walking tracks and alpine huts located in close proximity to initiation zones of steep ice. Further local scale studies of these processes are required, leading towards a full hazard assessment, and changing glacial conditions over coming decades will necessitate ongoing monitoring and reassessment of initiation zones and potential impacts.