Mechanism of AiTongXiao granule in the treatment of hepatocellular carcinoma based on network pharmacology and rat transplanted liver cancer model

Objective:To investigate the mechanism of action and material basis of AiTongXiao granule in the treatment of hepatocellular carcinoma(HCC)based on network pharmacology and transplanted liver cancer rat model.Methods:TCMSP database was used to screen out effective components and its corresponding potential pharmaceutical targets,and databases including Gene Cards,OMIM,Drugbank and TTD were further used to collect HCC-related drug targets.The intersecting targets were obtained by mapping the drug and disease targets.The component-targets network was constructed and visualized by Cytoscape 3.8.2 software.Protein-protein interaction(PPI)network was built by STRING online platform,and the topological relationship and core targets was analyzed and screened by using CytoNCA software.In addition,Metascape database was used to perform gene ontology(GO)enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis of the core targets.At last,rat liver transplanted liver cancer model was established by using Walker-256 cell line and treated by AiTongXiao granule for 15 days.Western blot was used to further compare the expression levels of AKT,pAKT,p53,p-p53,ERK1/2 and ERK1/2 in the tumor between treatment group and the control group.Results:257 active components were obtained from AiTongXiao granule,corresponding to 294 drug targets.Meanwhile,233 of the 7993 HCC disease targets were screened out between AiTongXiao granule drug and HCC disease targets.11 core targets including AKT1,IL6,TP53,MAPK3,TNF,JUN,CASP3,MAPK1,MYC,PTGS2,MMP9 were further obtained by median screening.GO and KEGG analysis results showed that these core targets enriched to HBV,TNF and cancer related pathways.The rat transplanted liver cancer model results indicated significant down regulation for AKT,p-AKT,pERK1/2,and significant up regulation of p-p53 after AiTongXiao granule treatment(P<0.05).Conclusion:AiTongXiao granule could act to multiple cancer related pathways,and AKT,p53 and ERK1/2 were validated to be regulated by ATXF in rat model.The mechanism may be through the regulation of the above signaling pathways to exert anti-liver cancer effect.

Virtualized Wireless SDNs:Modelling Delay Through the Use of Stochastic Network Calculus

Software-defined networks （SDN） have attracted much attention recently because of their flexibility in terms of network management. Increasingly, SDN is being introduced into wireless networks to form wireless SDN. One enabling technology for wireless SDN is network virtualization, which logically divides one wireless network element, such as a base station, into multiple slices, and each slice serving as a standalone virtual BS. In this way, one physical mobile wireless network can be partitioned into multiple virtual networks in a software-defined manner. Wireless virtual networks comprising virtual base stations also need to provide QoS to mobile end-user services in the same context as their physical hosting networks. One key QoS parameter is delay. This paper presents a delay model for software-defined wireless virtual networks. Network calculus is used in the modelling. In particular, stochastic network calculus, which describes more realistic models than deterministic network calculus, is used. The model enables theoretical investigation of wireless SDN, which is largely dominated by either algorithms or prototype implementations.

Enhancing Wireless Sensor Network Efficiency through Al-Biruni Earth Radius Optimization

The networks of wireless sensors provide the ground for a range of applications,including environmental moni-toring and industrial operations.Ensuring the networks can overcome obstacles like power and communication reliability and sensor coverage is the crux of network optimization.Network infrastructure planning should be focused on increasing performance,and it should be affected by the detailed data about node distribution.This work recommends the creation of each sensor’s specs and radius of influence based on a particular geographical location,which will contribute to better network planning and design.By using the ARIMA model for time series forecasting and the Al-Biruni Earth Radius algorithm for optimization,our approach bridges the gap between successive terrains while seeking the equilibrium between exploration and exploitation.Through implementing adaptive protocols according to varying environments and sensor constraints,our study aspires to improve overall network operation.We compare the Al-Biruni Earth Radius algorithm along with Gray Wolf Optimization,Particle Swarm Optimization,Genetic Algorithms,and Whale Optimization about performance on real-world problems.Being the most efficient in the optimization process,Biruni displays the lowest error rate at 0.00032.The two other statistical techniques,like ANOVA,are also useful in discovering the factors influencing the nature of sensor data and network-specific problems.Due to the multi-faceted support the comprehensive approach promotes,there is a chance to understand the dynamics that affect the optimization outcomes better so decisions about network design can be made.Through delivering better performance and reliability for various in-situ applications,this research leads to a fusion of time series forecasters and a customized optimizer algorithm.

Hybrid Power Bank Deployment Model for Energy Supply Coverage Optimization in Industrial Wireless Sensor Network

Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN.

A mathematical model of a P53 oscillation network triggered by DNA damage

Taking the interaction between a DNA damage repair module, an ATM module, and a P53--MDM2 oscillation module into account, this paper presents a mathematical model of a P53 oscillation network triggered by a DNA damage signal in individual cells. The effects of the DNA damage signal and the delay time of P53-induced MDM2 expression on the behaviours of the P53 oscillation network are studied. In the oscillatory state of the P53--MDM2 oscillator, it is found that the pulse number of P53--P oscillation increases with the increase of the initial DNA damage signal, whereas the amplitude and the period of P53--P oscillation are fixed for different initial DNA damage signals, and the period numbers of P53--P oscillations decrease with the increase of time delay of MDM2 expression induced by P53. These theoretical predictions are consistent with previous experimental results. The combined negative feedback of P53--MDM2 with the time delay of P53-induced MDM2 expression causes oscillation behaviour in the P53 network.

Modeling of Node Energy Consumption for Wireless Sensor Networks

Energy consumption is the core issue in wireless sensor networks (WSN). To generate a node energy model that can accurately reveal the energy consumption of sensor nodes is an extremely important part of protocol development, system design and performance evaluation in WSNs. In this paper, by studying component energy consumption in different node states and within state transitions, the authors present the energy models of the node core components, including processors, RF modules and sensors. Furthermore, this paper reveals the energy correlations between node components, and then establishes the node energy model based on the event-trigger mechanism. Finally, the authors simulate the energy models of node components and then evaluate the energy consumption of network protocols based on this node energy model. The proposed model can be used to analyze the WSNs energy consumption, to evaluate communication protocols, to deploy nodes and then to construct WSN applications.

Modelling and Analysis of TCP Performance in Wireless Multihop Networks

Researchers have used extensive simulation and experimental studies to understand TCP performance in wireless multihop networks. In contrast, the objective of this paper is to theoretically analyze TCP performance in this environment. By examining the case of running one TCP session over a string topology, a system model for analyzing TCP performance in multihop wireless networks is proposed, which considers packet buffering, contention of nodes for access to the wireless channel, and spatial reuse of the wireless channel. Markov chain modelling is applied to analyze this system model. Analytical results show that when the number of hops that the TCP session crosses is ?xed, the TCP throughput is independent of the TCP congestion window size. When the number of hops increases from one, the TCP throughput decreases ?rst, and then stabilizes when the number of hops becomes large. The analysis is validated by comparing the numerical and simulation results.

Mathematical Model Validation of Search Protocols in MP2P Networks

Broadcasting is a basic technique in Mobile ad-hoc network(MANET),and it refers to sending a packet from one node to every other node within the transmission range.Flooding is a type of broadcast where the received packet is retransmitted once by every node.The naive flooding technique,floods the network with query messages,while the random walk technique operates by contacting the subsets of every node’s neighbors at each step,thereby restricting the search space.One of the key challenges in an ad-hoc network is the resource or content discovery problem which is about locating the queried resource.Many earlier works have mainly focused on the simulation-based analysis of flooding,and its variants under a wired network.Although,there have been some empirical studies in peer-to-peer(P2P)networks,the analytical results are still lacking,especially in the context of P2P systems running over MANET.In this paper,we describe how P2P resource discovery protocols perform badly over MANETs.To address the limitations,we propose a new protocol named ABRW(Address Broadcast Random Walk),which is a lightweight search approach,designed considering the underlay topology aimed to better suit the unstructured architecture.We provide the mathematical model,measuring the performance of our proposed search scheme with different widely popular benchmarked search techniques.Further,we also derive three relevant search performance metrics,i.e.,mean no.of steps needed to find a resource,the probability of finding a resource,and the mean no.of message overhead.We validated the analytical expressions through simulations.The simulation results closely matched with our analyticalmodel,justifying our findings.Our proposed search algorithm under such highly dynamic self-evolving networks performed better,as it reduced the search latency,decreased the overall message overhead,and still equally had a good success rate.

RESEARCH ON KEY NODES OF WIRELESS SENSOR NETWORK BASED ON COMPLEX NETWORK THEORY

On the basis of complex network theory, the issues of key nodes in Wireless Sensor Networks (WSN) are discussed. A model expression of sub-network fault in WSN is given at first; subsequently, the concepts of average path length and clustering coefficient are introduced. Based on the two concepts, a novel attribute description of key nodes related to sub-networks is proposed. Moreover, in terms of node deployment density and transmission range, the concept of single-point key nodes and generalized key nodes of WSN are defined, and their decision theorems are investigated.

Stochastic Modeling and Power Control of Time-Varying Wireless Communication Networks

Wireless networks are characterized by nodes mobility, which makes the propagation environment time-varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) that varies from one observation instant to the next. This paper is concerned with dynamical modeling of time-varying wireless fading channels, their estimation and parameter identification, and optimal power control from received signal measurement data. The wireless channel is characterized using a stochastic state-space form and derived by approximating the time-varying DPSD of the channel. The expected maximization and Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Moreover, we investigate a centralized optimal power control algorithm based on predictable strategies and employing the estimated channel parameters and states. The proposed models together with the estimation and power control algorithms are tested using experimental measurement data and the results are presented.

Management of Intelligent Campus Wireless Sensor Networks Based on Runtime Model

To quick customize and develop intelligent campus internet of things (ICIOT) system more efficiently, in this paper an approach based on runtime model to managing intelligent campus wireless sensor networks is proposed. Firstly, manageability of intelligent campus wireless sensors is abstracted as runtime models which automatically and immediately propagate any observable runtime changes of target resources to corresponding architecture models. Then, a composite model of intelligent campus wireless sensors is constructed through merging their runtime models in order to manage different kinds of devices in a unified way. Finally, a customized model is constructed according to the personalized management requirement and the synchronization between the customized model and the composite model is ensured through model transformation. Thus, all the management tasks can be carried through executing operating programs on the customized model. In the part of the teaching area schools conducted experiments and compared with the traditional method, this method can be more effective management of campus facilities, more energy efficient and orderly, which can reach a 16.7% energy saving.

ON THE CAPACITY REGION OF WIRELESS AD HOC RELAY NETWORKS

Network capacity is a key characteristic to evaluate the performance of wireless networks, The goal of this paper is to study the capacity of wireless ad hoe relay network. In the model, there is at lnost ns source nodes transmitting signal simultaneously in the network and the arbitrarily complex network coding is allowed. The upper capacity bound of the network model are derived From the max-flow rain-cut theorem and the lower capacity bound are obtained by the rate-distortion function For the Gaussian source. Finally, simulation results show that the upper network capacity will decrease as the number of source nodes is increased.

Design and application of wireless signal strength measurement system on the near-ground

The wireless communication system's performance is greatly constrained by the wireless channel characteristics,especially in some specific environment.Therefore,signal transmission will be greatly impacted even if not in a complicated topography.Testing results show that it is hardly to characterize the radio propagation properties for the antenna installed on the ground.In order to ensure a successful communication,the radio frequency(RF)wireless signal intensity monitor system was designed.We can get the wireless link transmission loss through measuring signal strength from received node.The test shows that the near-ground wireless signal propagation characteristics still can be characterized by the log distance propagation loss model.These results will conduce to studying the transmission characteristic of Near-Earth wireless signals and will predict the coverage of the earth's surface wireless sensor network.

Research on Beta Trust Model of Wireless Sensor Networks Based on Energy Load Balancing

This paper proposed beta trust model based on energy load balancing combines the recent achievements of the trust models in distributed networks, together with the characteristics of wireless sensor networks. The inter-node trust relation is established after an overall evaluation of node trust value based on the monitor results of the node packets forwarding behavior conducted by inter-node collaboration. Due to the node energy limitation in wireless sensor networks, energy load balancing mechanism is applied to prolong the node survival time. And the redundant routing protocol involves the presented trust model to develop the novel trust routing protocol of beta trust model based on energy load balancing. Simulation performance demonstrates that the beta trust model based on energy load balancing outperforms current schemes in energy consumption.

Physiological signal acquisition system based on wireless sensor networks

Based on wireless sensor networks, a physiological signal acquisition system is proposed. The system is used in classroom education in order to understand the physiological changes in the students. In the system,the biological electrical signal related to student attention and emotion states can be measured by electrocardiography signals. The bioelectrical signal is digitalized at a 200 Hz sampling rate and is transmitted by the ZigBee protocol. Simultaneously, the Bluetooth technology is also embedded in the nodes so as to meet the high sampling rate and the high-bandwidth transmission. The system can implement the monitoring tasks for 30 students, and the experimental results of using the system in the classroom are proposed. Finally, the applications of wireless sensor networks used in education is also discussed.

Dynamical analysis for a malware propagation model in wireless sensor network

The threat of malware in wireless sensor network has stimulated some activities to model and analyze the malware prevalence.To understand the dynamics of malware propagation in wireless sensor network,we propose a novel epidemic model named as e-SEIR(susceptible-exposed-infectious-recovered)model,which is a set of delayed differential equations,in this paper.The model has taken into account the following two factors:1 Multi-state antivirus measures;2 Temporary immune period.Then,the stability and Hopf bifurcation at the equilibria of linearized model are carefully analyzed by considering the distribution of eigenvalues of characteristic equations.Both mathematical analysis and numerical simulations show that the dynamical features of the proposed model rely on the basic reproduction number R0 and time delayτ.This novel model can help us to better understand and predict the propagation behaviors of malware in wireless sensor networks.

Characteristics analyzing and parametric modeling of the arc sound in CO_2 GMAW for on-line quality monitoring

For on-line monitoring of welding quality, the characteristics of the arc sound signals in short circuit CO2 GMAW were analyzed in the time and frequency domains. The arc sound presents a series of ringing-like oscillations that occur at the end of short circuit i. e. the moment of arc re-ignition, and distributes mainly in the frequency band below 10 kHz. A concept of the arc tone channel and its equivalent electrical model were suggested, which is considered a time-dependent distributed parametric system of which the transmission properties depend upon the geometric and physical characteristics of the arc and surroundings, and is excited by the sound source results from the change of arc energy so that results in arc sound. The linear prediction coding （ LPC ） model is an estimation of the tone channel. The radial basis function （ RBF ） neural networks were built for on-line pattern recognition of the gas-lack in welding, in which the input vectors were formed with the LPC coefficients. The test results proved that the LPC model of arc sound and the RBF networks are feasible in on-line quality monitoring.

A Rule-Based Approach for Grey Hole Attack Prediction in Wireless Sensor Networks

The Wireless Sensor Networks(WSN)are vulnerable to assaults due to the fact that the devices connected to them have a reliable connection to the inter-net.A malicious node acts as the controller and uses a grey hole attack to get the data from all of the other nodes in the network.Additionally,the nodes are dis-carding and modifying the data packets according to the requirements of the sys-tem.The assault modifies the fundamental concept of the WSNs,which is that different devices should communicate with one another.In the proposed system,there is a fuzzy idea offered for the purpose of preventing the grey hole attack from making effective communication among the WSN devices.The currently available model is unable to recognise the myriad of different kinds of attacks.The fuzzy engine identified suspicious actions by utilising the rules that were gen-erated to make a prediction about the malicious node that would halt the process.Experiments conducted using simulation are used to determine delay,accuracy,energy consumption,throughput,and the ratio of packets successfully delivered.It stands in contrast to the model that was suggested,as well as the methodologies that are currently being used,and analogue behavioural modelling.In comparison to the existing method,the proposed model achieves an accuracy rate of 45 per-cent,a packet delivery ratio of 79 percent,and a reduction in energy usage of around 35.6 percent.These results from the simulation demonstrate that the fuzzy grey detection technique that was presented has the potential to increase the net-work’s capability of detecting grey hole assaults.

Virtual reality mobility model for wireless ad hoc networks

For wireless ad hoc networks simulation, node＇s mobility pattern and traffic pattern are two key elements. A new simulation model is presented based on the virtual reality collision detection algorithm in obstacle environment, and the model uses the path planning method to avoid obstacles and to compute the node＇s moving path. Obstacles also affect node＇s signal propagation. Considering these factors, this study implements the mobility model for wireless ad hoc networks. Simulation results show that the model has a significant impact on the performance of protocols.

Finding the Optimal Percentage of Cluster Heads from a New and Complete Mathematical Model on LEACH

Network lifetime is one of the important metrics that indicate the performance of a sensor network. Different techniques are used to elongate network lifetime. Among them, clustering is one of the popular techniques. LEACH (Low-Energy Adaptive Clustering Hierarchy) is one of the most widely cited clustering solutions due to its simplicity and effectiveness. LEACH has several parameters that can be tuned to get better performance. Percentage of cluster heads is one such important parameter which affects the network lifetime significantly. At present it is hard to find the optimum value for the percentage of cluster head parameter due to the absence of a complete mathematical model on LEACH. A complete mathematical model on LEACH can be used to tune other LEACH parameters in order to get better performance. In this paper, we formulate a new and complete mathematical model on LEACH. From this new mathematical model, we compute the value for the optimal percentage of cluster heads in order to increase the network lifetime. Simulation results verify both the correctness of our mathematical model and the effectiveness of computing the optimal percentage of cluster heads to increase the network lifetime.