Effective remediation of cadmium and lead contaminated soils by a novel slow-release phosphate amendment

Phosphate is widely used to immobilize cadmium(Cd)and lead(Pb)in soils through the insoluble metal phosphate precipitation.However,an increase in the phosphorus content of the environment can cause new pollution.In this study,five slow-release phosphate amendments(SRPAs)were synthesized and their characteristics including BET,SEM,FTIR,swelling ratio,and thephosphorus release were determined.The results show that SRPA was a sphere with a network structure with a specific surface area of 5 to 7.18 m^(2)/g andcontained phosphate,hydroxyl,carboxyl and other functional groups.Among five SRPAs,S3 sample showed good performance for phosphate release.Phosphate release from SRPA was well fitted with Ritger-Peppas model with constant n between 0.45 and 0.85,indicating that the phosphate release was in accordance with non-Fickian diffusion.As compared with monocalcium phosphate(MCP),SRPA application led to a lower concentration of water-soluble phosphorus in the soil sample and higher remediation efficiencies of Cd and Pb.The remediation efficiencies of water-soluble Cd and Pb in soil with SRPA were 97.1%and 97.9%,respectively.The remediation efficiencies of bioavailable Cd and Pb were 71.85%and 76.47%,respectively.The results of Tessier extraction showed that the exchangeable and carbonatebound fractions of Cd and Pb in the soil sample after SRPA application significantly reduced,while the residual fraction increased,indicating the stability of heavy metals increased.

Research on Mobile Internet Mobile Agent System Dynamic Trust Model for Cloud Computing

This paper analyzes the reasons for the formation of security problems in mobile agent systems, and analyzes and compares the security mechanisms and security technologies of existing mobile agent systems from the perspective of blocking attacks. On this basis, the host protection mobile agent protection technology is selected, and a method to enhance the security protection of mobile agents (referred to as IEOP method) is proposed. The method first encrypts the mobile agent code using the encryption function, and then encapsulates the encrypted mobile agent with the improved EOP protocol IEOP, and then traces the suspicious execution result. Experiments show that using this method can block most malicious attacks on mobile agents, and can protect the integrity and confidentiality of mobile agents, but the increment of mobile agent tour time is not large.

Evolutionary Dynamics Modeling of Symbolic Social Network Structure Equilibrium

The use of symbol attributes on the side of symbolic social networks to analyze,understand,and predict the topology,function,and dynamic behaviour of complex networks,and has important theoretical significance for personalized recommendations,attitude prediction,user feature analysis,and clustering and application value.However,due to the huge scale of online social networks,this poses a challenge to traditional symbolic social network analysis methods.Based on the theory of structural equilibrium,this paper studies the evolutionary dynamics of symbolic social networks,proposes the energy function of weak structural equilibrium theory,and uses the evolution of evolutionary algorithms to obtain the weak imbalance of the network.The simulation experiment results show that the calculation method in this paper can get the optimal solution faster.It provides an idea for the study of real and complex social networks.

Nonlinear Prediction with Deep Recurrent Neural Networks for Non-Blind Audio Bandwidth Extension

Non-blind audio bandwidth extension is a standard technique within contemporary audio codecs to efficiently code audio signals at low bitrates. In existing methods, in most cases high frequencies signal is usually generated by a duplication of the corresponding low frequencies and some parameters of high frequencies. However, the perception quality of coding will significantly degrade if the correlation between high frequencies and low frequencies becomes weak. In this paper, we quantitatively analyse the correlation via computing mutual information value. The analysis results show the correlation also exists in low frequency signal of the context dependent frames besides the current frame. In order to improve the perception quality of coding, we propose a novel method of high frequency coarse spectrum generation to improve the conventional replication method. In the proposed method, the coarse high frequency spectrums are generated by a nonlinear mapping model using deep recurrent neural network. The experiments confirm that the proposed method shows better performance than the reference methods.

Mobile Internet Mobile Agent System Dynamic Trust Model for Cloud Computing

In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the cloud.Aiming at the security and trust management of mobile agent system in mobile cloud computing environment,the Human Trust Mechanism(HTM)is used to study the subjective trust formation,trust propagation and trust evolution law,and the subjective trust dynamic management algorithm(MASTM)is proposed.Based on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data,the public trust host selection algorithm is given.The isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host,so as to enhance the security interaction between the mobile agent and the host.Given algorithm simulation and verification were carried out to prove its feasibility and effectiveness.

Research on Prediction Methods of Prevalence Perception under Information Exposure

With the rapid development of information technology,the explosive growth of data information has become a common challenge and opportunity.Social network services represented by WeChat,Weibo and Twitter,drive a large amount of information due to the continuous spread,evolution and emergence of users through these platforms.The dynamic modeling,analysis,and network information prediction,has very important research and application value,and plays a very important role in the discovery of popular events,personalized information recommendation,and early warning of bad information.For these reasons,this paper proposes an adaptive prediction algorithm for network information transmission.A popularity prediction algorithm is designed to control the transmission trend based on the gray Verhulst model to analyze the law of development and capture popular trends.Experimental simulations show that the proposed perceptual prediction model in this paper has a better fitting effect than the existing models.

The development trend and practical innovation of smart cities under the integration of new technologies

Smart cities have rapidly developed in the context of the integration of new digital technologies such as big data,Internet of Things,artificial intelligence,blockchains,and virtual reality.These cities have conducted practical innovations and typical cases in many sectors,such as in government,transportation,environmental protection,energy,medical care,and logistics,and have produced many social,economic,and ecological benefits.However,there are still some problems that continue to hinder the construction of smart cities.This paper examines such problems in depth and proposes some relevant countermeasures and suggestions.

A New Time-Aware Collaborative Filtering Intelligent Recommendation System

Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy,this paper introduces project attribute fuzzy matrix,measures the project relevance through fuzzy clustering method,and classifies all project attributes.Then,the weight of the project relevance is introduced in the user similarity calculation,so that the nearest neighbor search is more accurate.In the prediction scoring section,considering the change of user interest with time,it is proposed to use the time weighting function to improve the influence of the time effect of the evaluation,so that the newer evaluation information in the system has a relatively large weight.The experimental results show that the improved algorithm improves the recommendation accuracy and improves the recommendation quality.

Research on the ecological compensation standard of the basin pollution control project based on evolutionary game theory and by taking Xiangjiang River as a case

Ecological compensation is a new resource and environment management model.As one of the main areas for implementing ecological compensation policies,basin ecological compensation has become an important measure for encouraging basin pollution control projects and improving the quality of regional economic development.By applying the basic game analysis of evolutionary game theory and building an evolutionary game model with a“reward-punishment”mechanism,this paper compares the interest-related decision-making behaviors of the upstream and downstream stakeholders of basin ecological compensation.By using data on the water quality of Xiangjiang River Basin,this paper calculates the rewards and penalties in different intervals by building a parametric regression mathematical model and employing the local linear regression method.Results show that a decline in water quality should be fined RMB 925500 yuan,an improvement in water quality should be awarded RMB 1227800 yuan,and a deteriorating water quality should be severely fined RMB 5087600 yuan.

A New Behavior-Assisted Semantic Recognition Method for Smart Home

In the recent Smart Home(SH)research work,intelligent service recommendation technique based on behavior recognition,it has been extensively preferred by researchers.However,most current research uses the Semantic recognition to construct the user’s basic behavior model.This method is usually restricted by environmental factors,the way these models are built makes it impossible for them to dynamically match the services that might be provided in the user environment.To solve this problem,this paper proposes a Semantic behavior assistance(Semantic behavior assistance,SBA).By joining the semantic model on the intelligent gateway,building an SA model,in this way,a logical Internet networks for smart home is established.At the same time,a behavior assistant method based on SBA model is proposed,among them,the user environment-related entities,sensors,devices,and user-related knowledge models exist in the logical interconnection network of the SH system through the semantic model.In this paper,the data simulation experiment is carried out on the method.The experimental results show that the SBA model is better than the knowledge-based pre-defined model.

Spatial and Temporal Distribution of PM_(2.5) Pollution and Control Strategy in the Chang-Zhu-Tan City Cluster

Utilizing the initial hourly monitoring data of PM_(2.5) concentrations at 23 monitoring sites across the Chang-Zhu-Tan city cluster between January 2013 and February 2014 that released in Real-time Air Quality Reporting System in Hunan Province, this paper draws diagrams and analyzes the change rule of the pollutants concentration over time. In addition, this paper studies the regional distribution of PM_(2.5) seasonal pollution in the vicinity of the monitoring sites using Arc GIS geographic information system with the Kriging interpolation method.On this basis, this paper puts forward some effective control strategies to cope with regional PM_(2.5) pollution combined with the information of industry distribution and development status in the Chang-Zhu-Tan city cluster.

Research on Intelligent Mobile Commerce Transaction Security Mechanisms Based on Mobile Agent

In networked mobile commerce network transactions,trust is the prerequisite and key to a smooth transaction.The measurement of trust between entities involves factors such as transaction amount,transaction time,personal income of consumer entities and their risk attitude towards trust,etc.,so it is difficult to accurately calculate quantitatively.In order to find out the essential characteristics of this trust relationship,based on the research background of mobile commerce in the mobile network environment,a dynamic trust mechanism is proposed through the research of trust in the mobile network environment,trust influencing factors and trust mechanism.The calculation model of mobile interactive services based on mobile service business transactions.The model calculates feedback credibility through feedback deviation and feedback robustness,and combines transaction context factors and trust mapping mechanism to judge the seller’s credibility.This model better reflects the degree of influence of subjective factors such as personal preferences and risk attitudes on trust calculations,And the sensitivity of trust algorithms and transaction attributes has been greatly improved.After a large number of experiments and theoretical analysis,this mechanism provides an effective explanation for solving the problem of network trust computing.and provides valuable new ideas for the study of secure transactions in the mobile Internet environment.

A New Method Based on Evolutionary Algorithm for Symbolic Network Weak Unbalance

The symbolic network adds the emotional information of the relationship,that is,the“+”and“-”information of the edge,which greatly enhances the modeling ability and has wide application in many fields.Weak unbalance is an important indicator to measure the network tension.This paper starts from the weak structural equilibrium theorem,and integrates the work of predecessors,and proposes the weak unbalanced algorithm EAWSB based on evolutionary algorithm.Experiments on the large symbolic networks Epinions,Slashdot and WikiElections show the effectiveness and efficiency of the proposed method.In EAWSB,this paper proposes a compression-based indirect representation method,which effectively reduces the size of the genotype space,thus making the algorithm search more complete and easier to get better solutions.

Understanding Farmers' Perceptions and Risk Responses to Climate Change in China

Agriculture is likely to bear the brunt of the impacts of climate change. The extent to which these impacts are felt depends in large part on the extent of adaptation in response to climate change. The overall aim of this paper is to attempt to identify farmers' knowledge,perceptions and risk responses towards climate change(or potential change). In order to achieve this goal, several specific objectives are pursued. First, the paper investigates whether or not farmers have perceived the long-term climate change and extreme weather events. Second, the paper describes how farmers respond to climate change and tries to assess the determinants of their adaptation. Based on data collected from a survey among farm households in three provinces in rural China, the findings demonstrate that farmers are aware of climate variability and identify the rising temperature, decreasing precipitation and the increasing frequency of drought. Only about 25% of farmers are willing to adjust their farming structures as a risk reaction. Household size, wealth, farm size, and the number of plots are found to be important factors that influence farmer adaptive capacity. Implications for policymaking on agriculture and adaptation to climate change will be to focus on providing farmers with information about the climate in time and facilitating enhancement of their adaptive capacity.

Special issue:Resource-saving and environment-friendly(two oriented)engineering management and decision making

Huang et al.reviewed the status and development of natural gas in the world’s energy evolution,and pointed out that natural gas has become the primary energy source and the five dimensions of resource development,resource acquisition,trade system,infrastructure,and security system needs to be strengthened.

Special issue:Blockchain technology application

As a game-changer,the emergence of blockchain technology is profoundly shaping the business,organization,economy,and society around the world.The blockchain is an open,distributed ledger that records transactions between two parties efficiently and in a verifiable and permanent way.It exhibits a chain structure composed of increasing blocks.The transaction data per unit time is encrypted into the block for that time period and used to generate a cryptographic hash of the next block.Underlying the novel technology,there are several distinguished features including distributed database,peer-to-peer transmission,transparency with pseudonymity,irreversibility of records,and computational logic.With blockchain,a new world could be imaged in which all form of transactions are embedded in digital code and protected from deletion,tampering and revision.The trust could be perfectly established by using the“algorithmic proof mechanism”in an asymmetric,uncertain,and insecure environment.