Comprehensive integration of single-cell transcriptomic data illuminates the regulatory network architecture of plant cell fate specification

Plant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors(TFs)in intricate regulatory networks in a cell-type specific manner.Here we introduced a comprehensive single-cell transcriptomic atlas of Arabidopsis seedlings.This atlas is the result of meticulous integration of 63 previously published scRNA-seq datasets,addressing batch effects and conserving biological variance.This integration spans a broad spectrum of tissues,including both below-and above-ground parts.Utilizing a rigorous approach for cell type annotation,we identified 47 distinct cell types or states,largely expanding our current view of plant cell compositions.We systematically constructed cell-type specific gene regulatory networks and uncovered key regulators that act in a coordinated manner to control cell-type specific gene expression.Taken together,our study not only offers extensive plant cell atlas exploration that serves as a valuable resource,but also provides molecular insights into gene-regulatory programs that varies from different cell types.

NOMA Empowered Energy Efficient Data Collection and Wireless Power Transfer in Space-Air-Ground Integrated Networks

As the sixth generation network(6G)emerges,the Internet of remote things(IoRT)has become a critical issue.However,conventional terrestrial networks cannot meet the delay-sensitive data collection needs of IoRT networks,and the Space-Air-Ground integrated network(SAGIN)holds promise.We propose a novel setup that integrates non-orthogonal multiple access(NOMA)and wireless power transfer(WPT)to collect latency-sensitive data from IoRT networks.To extend the lifetime of devices,we aim to minimize the maximum energy consumption among all IoRT devices.Due to the coupling between variables,the resulting problem is non-convex.We first decouple the variables and split the original problem into four subproblems.Then,we propose an iterative algorithm to solve the corresponding subproblems based on successive convex approximation(SCA)techniques and slack variables.Finally,simulation results show that the NOMA strategy has a tremendous advantage over the OMA scheme in terms of network lifetime and energy efficiency,providing valuable insights.

Create Your Own Data and Energy Integrated Communication Network:A Brief Tutorial and a Prototype System

In order to satisfy the ever-increasing energy appetite of the massive battery-powered and batteryless communication devices,radio frequency(RF)signals have been relied upon for transferring wireless power to them.The joint coordination of wireless power transfer(WPT)and wireless information transfer(WIT)yields simultaneous wireless information and power transfer(SWIPT)as well as data and energy integrated communication network(DEIN).However,as a promising technique,few efforts are invested in the hardware implementation of DEIN.In order to make DEIN a reality,this paper focuses on hardware implementation of a DEIN.It firstly provides a brief tutorial on SWIPT,while summarising the latest hardware design of WPT transceiver and the existing commercial solutions.Then,a prototype design in DEIN with full protocol stack is elaborated,followed by its performance evaluation.

UAV-Aided Data and Energy Integrated Network: System Design and Prototype Development

Terminal devices deployed in outdoor environments are facing a thorny problem of power supply.Data and energy integrated network(DEIN)is a promising technology to solve the problem,which simultaneously transfers data and energy through radio frequency signals.State-of-the-art researches mostly focus on theoretical aspects.By contrast,we provide a complete design and implementation of a fully functioning DEIN system with the support of an unmanned aerial vehicle(UAV).The UAV can be dispatched to areas of interest to remotely recharge batteryless terminals,while collecting essential information from them.Then,the UAV uploads the information to remote base stations.Our system verifies the feasibility of the DEIN in practical applications.

Towards Practical Implementation of Data and Energy Integrated Networks

With the rapid development of the mobile internet and the massive deployment of the Internet of Things, mobile devices, including both the consumer electronics and the sensors, become hungrier for the energy than ever before. Conventional cable based charging largely restrict the movement of the mobile devices. Wireless charging hence emerges as an essential technique for enabling our ultimate goal of charging anytime and anywhere. By efficiently exploiting the legacy of the existing communication infrastructure, we propose a nov- el data and energy integrated network （DEIN） in order to re- alise the radio frequency （RF） based wireless charging with- out degrading the information transmission. In this treatise, we focus on the implementation of the DEIN in both the theoretical and practical aspects, concerning the transceiver architecture design and the rectifier circuit design. Furthermore, we also present a Wi-Fi based testbed for demonstrating the availability of the RF based wireless charging.

Intelligent Data Pre-processing Model in Integrated Ocean Observing Network System

There are a number of dirty data in observation data set derived from integrated ocean observing network system. Thus, the data must be carefully and reasonably processed before they are used for forecasting or analysis. This paper proposes a data pre-processing model based on intelligent algorithms. Firstly, we introduce the integrated network platform of ocean observation. Next, the preprocessing model of data is presemed, and an imelligent cleaning model of data is proposed. Based on fuzzy clustering, the Kohonen clustering network is improved to fulfill the parallel calculation of fuzzy c-means clustering. The proposed dynamic algorithm can automatically f＇md the new clustering center with the updated sample data. The rapid and dynamic performance of the model makes it suitable for real time calculation, and the efficiency and accuracy of the model is proved by test results through observation data analysis.

Investigating Approaches of Data Integrity Preservation for Secure Data Aggregation in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) typically use in-network processing to reduce the communication overhead. Due to the fusion of data items sourced at different nodes into a single one during in-network processing, the sanctity of the aggregated data needs to be ensured. Especially, the data integrity of the aggregated result is critical as any malicious update to it can jeopardize not one, but many sensor readings. In this paper, we analyse three different approaches to providing integrity support for SDA in WSNs. The first one is traditional MAC, in which each leaf node and intermediate node share a key with parent (symmetric key). The second is aggregate MAC (AMAC), in which a base station shares a unique key with all the other sensor nodes. The third is homomorphic MAC (Homo MAC) that is purely symmetric key-based approach. These approaches exhibit diverse trade-off in resource consumption and security assumptions. Adding together to that, we also propose a probabilistic and improved variant of homomorphic MAC that improves the security strength for secure data aggregation in WSNs. We carry out simulations in TinyOS environment to experimentally evaluate the impact of each of these on the resource consumption in WSNs.

PIR-based data integrity verification method in sensor network

Since a sensor node handles wireless communication in data transmission and reception and is installed in poor environment, it is easily exposed to certain attacks such as data transformation and sniffing. Therefore, it is necessary to verify data integrity to properly respond to an adversary's ill-intentioned data modification. In sensor network environment, the data integrity verification method verifies the final data only, requesting multiple communications. An energy-efficient private information retrieval(PIR)-based data integrity verification method is proposed. Because the proposed method verifies the integrity of data between parent and child nodes, it is more efficient than the existing method which verifies data integrity after receiving data from the entire network or in a cluster. Since the number of messages for verification is reduced, in addition, energy could be used more efficiently. Lastly, the excellence of the proposed method is verified through performance evaluation.

Integrated Navigation Filtering Method Based on Wavelet Neural Network Optimized by MEA Model

In the experiment of combined navigation filtering using wavelet neural network, the initial parameters of the network have the influence of randomness on network convergence and navigation accuracy. A combined navigation filtering method based on wavelet neural network optimized by mind evolution algorithm is proposed. Firstly, the efficient global search ability of the mind evolution algorithm was used to quickly and accurately obtain the initial parameters of the appropriate wavelet neural network, and then the optimized wavelet neural network was applied to directly predict the position and velocity error data. This method is different from the traditional filtering method, while avoiding the drawbacks of the neural network. The simulation experiments with wavelet neural network and GA-wavelet network were carried out. The results show that the proposed method can effectively improve the accuracy of the integrated navigation system and provide a feasible path for combined navigation filtering.

Digital Coal Mine Integrated Automation System Based on ControlNet

A three-layer model for digital communication in a mine is proposed. Two basic platforms are discussed: A uniform transmission network and a uniform data warehouse. An actual,ControlNet based,transmission network plat-form suitable for the Jining No.3 coal mine is presented. This network is an information superhighway intended to inte-grate all existing and new automation subsystems. Its standard interface can be used with future subsystems. The net-work,data structure and management decision-making all employ this uniform hardware and software. This effectively avoids the problems of system and information islands seen in traditional mine-automation systems. The construction of the network provides a stable foundation for digital communication in the Jining No.3 coal mine.

Integration and development of energy and information network in the Pan-Arctic region

The Global Energy Interconnection is an important strategic approach used to achieve efficient worldwide energy allocation.The idea of developing integrated power,information,and transportation networks provides increased power interconnection functionality and meaning,helps condense forces,and accelerates the integration of global infrastructure.Correspondingly,it is envisaged that it will become the trend of industrial technological development in the future.In consideration of the current trend of integrated development,this study evaluates a possible plan of coordinated development of fiber-optic and power networks in the Pan-Arctic region.Firstly,the backbone network architecture of Global Energy Interconnection is introduced and the importance of the Arctic energy backbone network is confirmed.The energy consumption and developmental trend of global data centers are then analyzed.Subsequently,the global network traffic is predicted and analyzed by means of a polynomial regression model.Finally,in combination with the current construction of fiber-optic networks in the Pan-Arctic region,the advantages of the integration of the fiber-optic and power networks in this region are clarified in justification of the decision for the development of a Global Energy Interconnection scheme.

Structural Reliability Analysis Based on Support Vector Machine and Dual Neural Network Direct Integration Method

Aiming at the reliability analysis of small sample data or implicit structural function,a novel structural reliability analysis model based on support vector machine(SVM)and neural network direct integration method(DNN)is proposed.Firstly,SVM with good small sample learning ability is used to train small sample data,fit structural performance functions and establish regular integration regions.Secondly,DNN is approximated the integral function to achieve multiple integration in the integration region.Finally,structural reliability was obtained by DNN.Numerical examples are investigated to demonstrate the effectiveness of the present method,which provides a feasible way for the structural reliability analysis.

Determining Web Data Currency Based on Markov Logic Network

This paper proposes a method based on Markov Logic Network (MLN) to determine the time order of entity attribute values. We use the characteristics of web sources’ currency, web sources inter-dependency and attribute data currency in a certain web source as predicates in MLN. We define five rules (new rules can be added) to infer the currency of different values provided by different sources. On one hand, this method considers currency problem based on entity attribute instead of the entire entity, which is critical to improve the qualityof data provided by Web Integration Systems; on the other hand, this method summarizes characteristics of web sources and web data based on carefully analysis. It is noteworthy that it is not complicate for the MLN model to incorporate new rules, which shows that the proposed method is extensible.

Understanding biological functions through molecular networks

The completion of genome sequences and subsequent high-throughput mapping of molecular networks have allowed us to study biology from the network perspective. Experimental, statistical and mathematical modeling approaches have been employed to study the structure, function and dynamics of molecular networks, and begin to reveal important links of various network properties to the functions of the biological systems. In agreement with these functional links, evolutionary selection of a network is apparently based on the function, rather than directly on the structure of the network. Dynamic modularity is one of the prominent features of molecular networks. Taking advantage of such a feature may simplify network-based biological studies through construction of process-specific modular networks and provide functional and mechanistic insights linking genotypic variations to complex traits or diseases, which is likely to be a key approach in the next wave of understanding complex human diseases. With the development of ready-to-use network analysis and modeling tools the networks approaches will be infused into everyday biological research in the near future.

Secure Remote Access IPSEC Virtual Private Network to University Network System

With the popularity of the Internet and improvement of information technology,digital information sharing increasingly becomes the trend.More and More universities pay attention to the digital campus,and the construction of digital library has become the focus of digital campus.A set of manageable,authenticated and secure solutions are needed for remote access to make the campus network be a transit point for the outside users.Remote Access IPSEC Virtual Private Network gives the solution of remote access to e-library resources,networks resources and so on very safely through a public network.It establishes a safe and stable tunnel which encrypts the data passing through it with robust secured algorithms.It is to establish a virtual private network in Internet,so that the two long-distance network users can transmit data to each other in a dedicated network channel.Using this technology,multi-network campus can communicate securely in the unreliable public internet.

Vertical Integration by Means of Profinet

This paper discusses some aspects of interdisciplinary problems of industrial automation curriculum in Virumaa College of Tallinn University of Technology at engineering level. The problems being faced by engineers are increasingly interdisciplinary and complicated because the development of new products and processes depends upon the integration of many different technologies. Expansion of possibilities of already existing fieldbus systems is carried out by means of integration them into Profinet （PROcess Field NET） communications. The lab set-model of vertical integration-for data gathering from smart Profibus PA sensor, data transmission, controllers configuration for Profinet IO direct interfacing of distributed field devices on the Ethernet is discussed in this paper.

应用生成对抗网络的地震数据重建和去噪一体化方法

在实际采集过程中,受地形条件和人为因素的影响,地震数据不仅在空间上会出现采样不足或不规则的情况,而且会混入噪声,不利于后续地震数据的处理和解释。通常将重建与去噪分为两个阶段处理,这样往往会引入额外的误差。为此,文中提出了一种基于条件韦氏生成对抗网络(cWGAN)的地震数据重建去噪一体化方法,该方法研究的重点是在缺失道和噪声的混合干扰下,准确提取地震数据的有效特征。首先,以U-Net模型为基本网络结构来构建生成器模型,分级提取地震数据同相轴特征;在判别器模型中引入条件约束,引导生成器优化梯度方向。其次,建立重建和去噪误差描述模型,该模型设计了一体化损失函数,可以兼顾重建与去噪两方面的处理任务。最后,经过合成数据和实际数据测试,证明文中所提的网络模型恢复的地震数据信噪比更高且具有较强鲁棒性。

循环神经网络模型下道路碳排放浓度预测

以湖南省永州市永州大道基本路段CO_(2)浓度时序数据为研究对象,旨在实现道路CO_(2)浓度的实时预测。测得用于模型训练和预测精度计算的路段CO_(2)浓度数据,利用Savitzky-Golay滤波器对数据进行平滑去噪,在调试并建立循环神经网络最优模型结构的基础上,引入多元预测模型(MLR、SVR、BP)和时序预测模型(BP、RF、RNN、LSTM、GRU)进行预测性能对比,为路段CO_(2)浓度的实时预测提供参照。结果表明:时序预测模型相比于多元预测模型具有更好的预测效果,特别是循环神经网络模型中的GRU表现出较高的预测精度,其次是LSTM,最后是RNN;循环神经网络模型在处理路段CO_(2)浓度时序数据的训练和预测任务中具备突出性能,能够实时且精准预测道路路段CO_(2)浓度。

基于BP神经网络的伪设计样本融合研究

由于实施简单、样本收集快速,非概率抽样已经成为获取数据的重要方式之一,但非概率样本代表性往往无法得到验证,样本无法多次利用,从而造成了数据资源浪费的问题。融合概率样本及非概率样本进行统计推断可以进一步提升估计的精度,减少数据资源的浪费。由此,本文采用伪设计样本融合思路,提出基于BP神经网络的伪设计样本融合方法,创新性地将BP神经网络引入非概率样本权重构造中,并采用最短距离法对倾向得分生成的初始权重进行二次校准。实验结果显示,本文提出的方法可以获得更高精度的估计结果,在协变量维数较高的情况下仍能保持良好的估计精度。本文不仅为网络时代下海量的高维样本融合分析提供了一个切实的方法,并且为概率样本与非概率样本融合领域的研究提供了一种新的思路。

多用户源头无线传感网络不完整数据挖掘算法

针对无线传感网络多用户源头数据受噪声影响,导致数据缺失的问题,为了提高数据的完整性,提出多用户源头无线传感网络不完整数据挖掘算法。采用组合广义形态滤波方法对多用户源头无线传感网络数据展开去噪处理,避免噪声数据影响数据填补结果;采用集成学习方法对数据进行深度挖掘,将挖掘出的数据展开分类处理;利用低秩矩阵填充理论对分类后的数据展开首次填补,在此基础上引入曲线相似分类对缺失数据进行二次填补,完成多用户源头无线传感网络数据的完整挖掘。仿真结果表明,所提方法在不同数据集中获得的均方根误差低于0.164%,信噪比高于41.8dB,补全后的数据平均绝对误差为0.023%、平均百分比误差为3.5%、均方根误差为0.021%。因此,所提方法具有较好的去噪效果和较高的数据填补性能。