353 research outputs found
Traffic congestion in interconnected complex networks
Traffic congestion in isolated complex networks has been investigated
extensively over the last decade. Coupled network models have recently been
developed to facilitate further understanding of real complex systems. Analysis
of traffic congestion in coupled complex networks, however, is still relatively
unexplored. In this paper, we try to explore the effect of interconnections on
traffic congestion in interconnected BA scale-free networks. We find that
assortative coupling can alleviate traffic congestion more readily than
disassortative and random coupling when the node processing capacity is
allocated based on node usage probability. Furthermore, the optimal coupling
probability can be found for assortative coupling. However, three types of
coupling preferences achieve similar traffic performance if all nodes share the
same processing capacity. We analyze interconnected Internet AS-level graphs of
South Korea and Japan and obtain similar results. Some practical suggestions
are presented to optimize such real-world interconnected networks accordingly.Comment: 8 page
Dynamic Behavior of Interacting between Epidemics and Cascades on Heterogeneous Networks
Epidemic spreading and cascading failure are two important dynamical
processes over complex networks. They have been investigated separately for a
long history. But in the real world, these two dynamics sometimes may interact
with each other. In this paper, we explore a model combined with SIR epidemic
spreading model and local loads sharing cascading failure model. There exists a
critical value of tolerance parameter that whether the epidemic with high
infection probability can spread out and infect a fraction of the network in
this model. When the tolerance parameter is smaller than the critical value,
cascading failure cuts off abundant of paths and blocks the spreading of
epidemic locally. While the tolerance parameter is larger than the critical
value, epidemic spreads out and infects a fraction of the network. A method for
estimating the critical value is proposed. In simulation, we verify the
effectiveness of this method in Barab\'asi-Albert (BA) networks
A Scale-Free Topology Construction Model for Wireless Sensor Networks
A local-area and energy-efficient (LAEE) evolution model for wireless sensor
networks is proposed. The process of topology evolution is divided into two
phases. In the first phase, nodes are distributed randomly in a fixed region.
In the second phase, according to the spatial structure of wireless sensor
networks, topology evolution starts from the sink, grows with an
energy-efficient preferential attachment rule in the new node's local-area, and
stops until all nodes are connected into network. Both analysis and simulation
results show that the degree distribution of LAEE follows the power law. This
topology construction model has better tolerance against energy depletion or
random failure than other non-scale-free WSN topologies.Comment: 13pages, 3 figure
WirePlanner: Fast, Secure and Cost-Efficient Route Configuration for SD-WAN
As enterprises increasingly migrate their applications to the cloud, the
demand for secure and cost-effective Wide Area Networking (WAN) solutions for
data transmission between branches and data centers grows. Among these
solutions, Software-Defined Wide Area Networking (SD-WAN) has emerged as a
promising approach. However, existing SD-WAN implementations largely rely on
IPSec tunnels for data encryption between edge routers, resulting in drawbacks
such as extended setup times and limited throughput. Additionally, the SD-WAN
control plane rarely takes both latency and monetary cost into consideration
when determining routes between nodes, resulting in unsatisfactory Quality of
Service (QoS). We propose WirePlanner, an SD-WAN solution that employs a novel
algorithm for path discovery, optimizing both latency and cost, and configures
WireGuard tunnels for secure and efficient data transmission. WirePlanner
considers two payment methods: Pay-As-You-Go, where users pay for a fixed
amount of bandwidth over a certain duration, and Pay-For-Data-Transfer, where
users pay for the volume of transmitted data. Given an underlay topology of
edge routers and a user-defined budget constraint, WirePlanner identifies a
path between nodes that minimizes latency and remains within the budget, while
utilizing WireGuard for secure data transmission
Bioactive SrO-SiO2 glass with well-ordered mesopores: Characterization, physiochemistry and biological properties
For a biomaterial to be considered suitable for bone repair it should ideally be both bioactive and have a capacity for controllable drug delivery; as such, mesoporous SiO2 glass has been proposed as a new class of bone regeneration material by virtue of its high drug-loading ability and generally good biocompatibility. It does, however, have less than optimum bioactivity and controllable drug delivery properties. In this study, we incorporated strontium (Sr) into mesoporous SiO2 in an effort to develop a bioactive mesoporous SrOāSiO2 (SrāSi) glass with the capacity to deliver Sr2+ ions, as well as a drug, at a controlled rate, thereby producing a material better suited for bone repair. The effects of Sr2+ on the structure, physiochemistry, drug delivery and biological properties of mesoporous SrāSi glass were investigated. The prepared mesoporous SrāSi glass was found to have an excellent release profile of bioactive Sr2+ ions and dexamethasone, and the incorporation of Sr2+ improved structural properties, such as mesopore size, pore volume and specific surface area, as well as rate of dissolution and protein adsorption. The mesoporous SrāSi glass had no cytotoxic effects and its release of Sr2+ and SiO44ā ions enhanced alkaline phosphatase activity ā a marker of osteogenic cell differentiation ā in human bone mesenchymal stem cells. Mesoporous SrāSi glasses can be prepared to porous scaffolds which show a more sustained drug release. This study suggests that incorporating Sr2+ into mesoporous SiO2 glass produces a material with a more optimal drug delivery profile coupled with improved bioactivity, making it an excellent material for bone repair applications. Keywords: Mesoporous SrāSi glass; Drug delivery; Bioactivity; Bone repair; Scaffold
PETformer: Long-term Time Series Forecasting via Placeholder-enhanced Transformer
Recently, the superiority of Transformer for long-term time series
forecasting (LTSF) tasks has been challenged, particularly since recent work
has shown that simple models can outperform numerous Transformer-based
approaches. This suggests that a notable gap remains in fully leveraging the
potential of Transformer in LTSF tasks. Consequently, this study investigates
key issues when applying Transformer to LTSF, encompassing aspects of temporal
continuity, information density, and multi-channel relationships. We introduce
the Placeholder-enhanced Technique (PET) to enhance the computational
efficiency and predictive accuracy of Transformer in LTSF tasks. Furthermore,
we delve into the impact of larger patch strategies and channel interaction
strategies on Transformer's performance, specifically Long Sub-sequence
Division (LSD) and Multi-channel Separation and Interaction (MSI). These
strategies collectively constitute a novel model termed PETformer. Extensive
experiments have demonstrated that PETformer achieves state-of-the-art
performance on eight commonly used public datasets for LTSF, surpassing all
existing models. The insights and enhancement methodologies presented in this
paper serve as valuable reference points and sources of inspiration for future
research endeavors
Evaluation of Urban Infrastructure Investment Efficiency: Empirical Evidence from Heilongjiang Province, China
The rapid growth of urban infrastructure investment in China has brought with it some serious problems that cannot be ignored, such as low investment efficiency and faulty investment decision-making. Therefore, based on the latest research findings related to infrastructure efficiency evaluation theory and evaluation methods, this paper uses empirical evidence from Heilongjiang province to analyze urban infrastructure investment efficiency. To analyze investment efficiency in the province, a new infrastructure investment efficiency evaluation model is developed known as the SDEA-Malmquist model. The model reveals that urban infrastructure investment projects in Heilongjiang province are relatively effective and stable but that the efficiency of such investments varies according to the city in which they are made. Overall efficiency is consistent with the TFC (total final consumption) index, but the index fluctuates within a narrow range between cities due to technological differences
In silico screening of anti-inflammatory constituents with good drug-like properties from twigs of Cinnamomum cassia based on molecular docking and network pharmacology
Purpose: To investigate by in silico screening the anti-inflammatory constituents of Cinnamomum cassia twigs.
Methods: Information on the constituents of C. cassia twigs was retrieved from the online Traditional Chinese Medicines (TCM) database and literature. Inflammation-related target proteins were identified from DrugBank, Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), Genetic Association Database (GAD), and PharmGKB. The identified compounds were filtered by Lipinskiās rules with Discovery Studio software. The āLibdockā module was used to perform molecular docking; LibdockScores and default cutoff values for hydrogen bonds and van der Waals interactions were recorded. LibdockScores between the prototype ligand and target protein were set as the threshold; compounds with higher LibdockScores than threshold were regarded as active compounds. Cytoscape software was used to construct active constituent-target protein interaction networks.
Results: Sixty-nine potential inflammatory constituents with good drug-like properties in C. cassia twigs were screened in silico based on molecular docking and network pharmacology analysis. JAK2, mPEGS-1, COX-2, IL-1Ī², and PPARĪ³ were considered the five most important target proteins. Compounds such as methyl dihydromelilotoside, hierochin B, dihydromelilotoside, dehydrodiconiferyl alcohol, balanophonin, phenethyl (E)-3-[4-methoxyphenyl]-2-propenoate, quercetin, and luteolin each interacted with more than six of the selected target proteins.
Conclusion: C. cassia twigs possess active compounds with good drug-like properties that can potentially be developed to treat inflammation with multi-components on multi-targets
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