With the advent of the era of self media, the demand for video trading is becoming more and more obvious. Alliance blockchain has the characteristics of traceable transaction records, tamper proof transaction records, decentralized transactions and faster transaction speed than public chains. These features make it a trading platform. Trusted computing can solve the problem of non Byzantine attack in the aspect of hardware. This paper proposes a video transaction algorithm considering FISCO alliance chain and improved trusted computing. First, an improved trusted computing algorithm is used to prepare a trusted transaction environment. Second, the video summary information extraction algorithm is used to extract the summary information that can uniquely identify the video. Finally, based on the video transactions algorithm of FISCO alliance chain, the video summary information is traded on the chain. Experimental results show that the proposed algorithm is efficient and robust for video transactions. At the same time, the algorithm has low computational power requirements and algorithm complexity, which can provide technical support for provincial and county financial media centers and relevant media departments. In terms of video content provision, User Generated Content (UGC) has developed into Professional Generated Content (PGC)/ Occupationally-Generated Content (OGC), which will provide more professional content. Additionally, with the development of Multi-Channel Network (MCN), content that is easier to commercialize will be provided more and more in the future . The aboHash to establish a trust relationship in the node cluster which lacks trust. This trust does not rely on any central party to make endorsement. In addition, the alliance chain is tamper proof and not traceable, which is suitable for video transaction application scenarios. Therefore, the alliance chain can be used to build video transaction index, trace the source of the traded video and identify the ownership of the video. Then, the technological innovation of trusted computing from the aspects of logical correctness verification, computing architecture and computing mode fundamentally improves the security of computer hardware and network environment, and reduces the possibility of hackers attacking the computer and its network that are trading.The existing video transaction mode has strong limitations. The video seller and the video buyer are isolated, and the relationship between them cannot be established directly, so the traditional trading mode cannot meet the demand of video trading. First of all, alliance blockchain technology uses cryptographic algorithms such as This paper proposes a video transaction algorithm considering alliance chain and trusted computing. Based on alliance chain and trusted computing, and assisted by the algorithm of non encrypted symmetric system in cryptography, this paper hopes to solve the current transaction problems of video transactions: data can easily be stolen, the transaction environment is not secure and the transaction file size is limited. The specific objectives of the algorithm are as follows:hash function, which is used as the video index information and stored in the alliance blockchain.(1) The video seller uses the distributed storage method to store the original video file locally and obtain the video storage path. Then, based on the video digest calculation method, the digest file that can uniquely identify the video is calculated, and the hash value of the digest file is calculated through the (2) The buyer of video records the transaction process and the use of video through the alliance blockchain.(3) Trusted computing technology ensures the security of the video trading environment, ensures that the video will not be leaked in the subsequent use process, and also ensures that the new data generated in the video use process will not be leaked.The blockchain proposed by When blockchain is applied to transaction, experts and scholars have done a lot of research. In the field of blockchain technology applied to video and other media transactions, Lin There are many researches on the application of trusted computing technology in transaction. Trusted computing is applied in the field of video media transaction. The existing research team has done a very good job on TPM (trusted platform module), and the research results explain this problem very clearly. This paper will make further thinking based on the research results of this team .The existing video transaction scenarios have many disadvantages, such as high redundancy of the transaction system, lack of tracking of copyright information, and user privacy is easy to be eavesdropped. In this case, the importance of trusted computing is highlighted. This scenario can be used in trusted computing technology, such as authority control, authority delegation and direct anonymous authentication.FISCO bcos is a low-level blockchain platform independently developed and completely open-source by the open-source working group of jinlianmeng. The architecture of the platform is divided from bottom to top into algorithm library layer, blockchain core layer, network layer, permission layer and user layer, as shown in (a) Key technology analysis(1) Node access and permission control mechanismThe public link in mechanism in the traditional blockchain technology allows any node to join the blockchain network at any time, and has the right to obtain the world state of the blockchain and all the data of the ledger from the global ledger. Any node in the alliance chain is not allowed to join the blockchain network without permission, and has a verification link.FISCO alliance chain technology does not adopt the traditional mechanism of “one account book for one chain”, but adopts its unique mechanism of “n account books for one chain”. This strategy realizes the data isolation of the same alliance chain in the dimension of group. All the members of the FISCO alliance chain will recognize a third-party management organization manager that can issue access mechanism authorization. When the node with manager authorization certificate logs in to the network of the FISCO alliance chain, it needs to initiate SSL two-way authentication operation. Through authentication, it can join the FISCO alliance chain. At this time, the traditional alliance chain will allow node to synchronize the alliance chain data and participate in consensus, so as to obtain the data on the chain. However, the FISCO alliance chain added an “access mechanism” before that, which requires node to request the system administrator’s authorization after successful login, and then become a node in the group. The permission of the group node is limited to “observation node” and “consensus node” Among them, the former can only participate in the synchronization of blocks in FISCO alliance chain, while the latter can participate in both synchronization and consensus initialization. The authorization of this permission depends on the system administrator.Based on the above foundation, (2) Parallel computingTraditional blockchain transaction performance is low. The parallel transaction processing model of FISCO alliance chain can make the transactions in the block execute in parallel, which improves the performance of transaction execution. FISCO provides users with the interface to write parallel contracts and the environment to execute parallel transactions. Developers define each interface in Le contract by defining mutually exclusive parameters.(3) Distributed storage technologyFISCO redefines the underlying storage model of blockchain and supports key-value database. The storage model architecture is shown in Traditional Merkel tree storage has performance bottleneck. (4) Consensus algorithmFISCO supports two different consensus algorithms: practical Byzantine fault tolerance algorithm and raft consensus algorithm. The former uses cryptography algorithm to ensure the anti-counterfeiting, anti tampering and non repudiation in the process of message delivery. The fault tolerance is 3f+1, in which f represents the number of malicious nodes. As mentioned above, the parallel computing capability of FISCO will make all nodes run in parallel as far as possible, and optimize the critical path to reduce the time loss in the consensus process, so as to improve the efficiency of the practical Byzantine fault-tolerant algorithm.For different application scenarios, 2f+1, where f represents the number of malicious nodes. FISCO alliance chain optimizes the network delay and jitter, and raft consensus algorithm can get better robustness in extreme network environment. Combined with smart contract, it realizes the dynamic in and out of nodes.In the latter, each node competes fairly in the time window to obtain accounting rights, and the fault tolerance is (a) Key feature analysis(1) Security featuresFISCO alliance chain is based on SSL protocol. Moreover, the access mechanism of nodes, the approval mechanism of administrators and the distributed permission control mechanism also ensure the security of FISCO alliance chain. Among them, admission mechanism and recognition mechanism not only break the connection between FISCO alliance chain and malicious nodes. Moreover, the blacklist is set, which fundamentally eliminates the possibility of the node attacking again. Access control mechanism strictly controls the access of sensitive data. In addition, the FISCO alliance chain also introduces homomorphic encryption and zero knowledge proof mechanism to further improve the security.The communication between all nodes in (2) Available featuresFISCO alliance chain simplifies the process of building alliance chain and reduces the standard of deployment mode. In addition, fsico alliance chain supports multiple programming languages and SDK interfaces, which reduces the development threshold and can better adapt to complex and changeable application scenarios, and improves the availability of FISCO alliance chain.(3) Performance featuresFISCO alliance chain ensures that the system automatically constructs DAG of transaction dependency according to mutually exclusive variables and transaction order in the transaction, and then uses DAG to execute transactions concurrently as much as possible, so as to improve the transaction processing speed in the block. FISCO alliance chain supports C + + to write smart contracts, so it can achieve about 20,000 TPS per chain. In addition, the support of FISCO alliance chain for multi group architecture is reflected in the process of ledger data sharing and consensus. It can improve the system throughput per unit time and the performance of the alliance chain.The transaction concurrent execution model of In the early research, trusted computing technology focused on the security of the operating system. With the rise of Internet of things, big data and cloud computing, the research scope of trusted technology is expanding. If the behavior of an entity is always carried out in the expected way and towards the expected goal, then the entity is considered to be credible, and its characteristics are shown in (1) Trusted computing will provide reliable protection on the hardware level for encrypted information. The method is to bind the encrypted information with the software configuration. If the configuration value given by the software accessing the encrypted information does not conform to the standard, the system will not release the encrypted information to resist hackers and viruses. This feature is called “encapsulated storage”;prover, and the prover uses the AIK (attachment identity key) of the TPM, AIK) signature is fed back to the challenger, and the Challenger verifies the integrity or running state of the platform by comparing the expected value with the signature value. The feature that “one running program can send the verification challenge information to another running program to verify its integrity or running state” is called “remote proof”;(2) The method is that the Challenger sends the challenge information to the (3) Trusted computing will provide protection against hackers’ attacks by monitoring keyboard input information and capturing screen display information. The method is to provide a secure channel from “keyboard to program” and “program to screen”, which is called “secure I/O”;(4) Trusted computing will provide a means of shielding against attacks launched by different programs reading the same memory. The method is to make different programs read memory information in isolation. This feature is called “memory shielding”.This paper improves the trusted computing technology by fusing the traditional zero knowledge proof and improving the identity authentication mechanism, and analyzes the improved trusted computing technology from multiple dimensions.The core of trusted computing is Trusted Platform Module TPM. Trusted platform module is a kind of hardware core module integrated in trusted computing platform, which is used to establish and guarantee trust source. It provides integrity measurement, secure storage, trusted report, platform authentication and control, password service and other functions for trusted computing. Usually, TPM is embedded on the main board of computer, which provides services for DRM system by using hardware characteristics. The specific composition of TPM is shown in I/O component: is mainly responsible for managing the information flow on the communication bus, executing the communication protocol between the internal bus and the external bus, and sending messages to the appropriate components.Key generator: responsible for generating the key pair required by TPM. For RSA algorithm, it needs to complete the test of large prime number, and the key generation process will use the data randomly generated by random number generator.HMAC engine: it provides information for TPM by confirming whether the message data is correct or not. It can find that the data or command is wrong or tampered.Random number generator: it is responsible for generating random numbers needed by various operations. It transforms an unpredictable input into a 32 byte random number through an internal state machine and one-way hash function.Power detection: help TPM take appropriate limiting measures when power state changes.Option controller: provides the mechanism to turn on and off the TPM function. By changing some permanent variable flag bits, you can set the TPM function options.Executive part: it is responsible for executing the commands sent to TPM through I/O. before executing the commands, it should be sure that the command execution environment is isolated and safe.Nonvolatile memory: used to store some permanent data.(a) Zero knowledge proofprover P proves to verifier Q that he knows information I, but the proof process cannot disclose any information of I. its essence is that N participants perform a task according to certain rules. Its characteristics are as followsZero knowledge proof means that (1) Certainty: if P doesn’t know information I, he can’t convince Q that he will prove it;(2) Integrity: if P knows information I, then P can make Q believe that he will prove it;(3) Zero knowledge: Q cannot acquire any additional knowledge about information I.prover P knows the secret order and wishes to prove it to the verifier V, but does not wish to disclose it, then:The cave model, the most typical zero knowledge proof case in trusted computing technology, is shown in (1) First, the verifier V stands at point A and the prover P stands at point B;(2) Prover P randomly chooses to go to point C or D, and verifier V can’t see the direction of prover P at point A;(3) The verifier V goes to point B and asks the verifier P to come out from the left/right channel;(4) The prover P comes out from the designated direction according to the requirements of the verifier V. if necessary, he needs to use the secret order to open the secret door.If the prover P knows the secret order, he will be able to come out correctly from the direction required by the verifier V.In the application of blockchain, the data interaction verification of different participants can be realized by zero knowledge proof, which can avoid the mutual leakage of sensitive information; in the application of multi-party computing, participants can ask each other to provide zero knowledge proof results of the calculation process for verification after the privacy calculation protected by homomorphic encryption and other methods is completed. This method prevents the false calculation, and at the same time does not disclose the sensitive information in the calculation.(b) Improve identity authentication mechanismThe direct anonymous authentication protocol proposed by the trusted computing organization solves the problem of low efficiency of the private CA (certificate authority) protocol, but it also reduces the privacy. Therefore, based on the above zero knowledge proof, the double random number signature algorithm based on Elgamal encryption strategy will be innovatively used in the signature phase to authenticate the trusted anonymous identity.pri is a large prime in the finite field GF(pri), and set Zpri and Suppose that ran is selected from the subset pri is 1, as shown in Formula The random number pri_key, the public key is pub_key, as shown in Formula In the definition of public and private key, the private key is user seeks the verification of the signed message mes from the verifier verd, and the specific steps are as follows:The User selects the random number ran′ from the subset pri-1 satisfy the greatest common divisor of 1, as shown in Formula (1) mid is calculated as shown in Formula (2) The middle number tem in the congruence equation, as shown in Formula (3) Calculate the temporary variable user’s signature on mes is , and user sends the request verification message req to verd, as shown in Formula The verd receives req, it first verifies whether mid is in the closed interval , if not, it directly rejects the signature; otherwise, it continues to calculate to verify whether the equation ranmes is true, as shown in Formula After ran′, if the random number is stolen by the attacker, the above calculation cannot guarantee the security. On this basis, this paper proposes a double random number signature authentication mechanism to improve the identity authentication mechanism in trusted computing:If it is not true, the signature will be rejected directly, otherwise the signature will be verified to be true and valid. But the above scheme only uses a random number ran∗ from the subset pri-1, as shown in Formula (1) User again selects the random number mid′, as shown in Formula (2) Calculate the intermediate number tem′ in the congruence equation, as shown in Formula (3) Calculate the temporary variable ranmes is calculated as shown in Formula (4) The verification equation user’s signature on mes is , and user sends the request verification message req to verd, as shown in Formula The verd receives the req, it first verifies whether mid and mid′ are in the closed interval , if not, it directly rejects the signature; otherwise, it continues to calculate whether the verification equation ranmes is true, if not, it directly rejects the signature, otherwise, it verifies that the signature is true and valid. The above trusted anonymous authentication process is shown in After (c) Technical analysisTrusted computing is frequently used in untrusted transactions. This paper will analyze the improved trusted computing.(1) Security—attackers steal signaturesmid and mid′ in the signature, the paper proposes a more secure double random number signature authentication mechanism, which makes the verification equation change from Formula Assuming that the attacker successfully steals (2) Security—attacker associated random numberran′ selected by two successive signatures is the same, then Formula mid is the same, and then Formula ran′′, so the security cannot be guaranteed, so the random number generated each time must be random enough; in addition, if there is a simple addition and subtraction operation relationship between the random numbers selected by two signatures, the impact is small, because Formula mid is different, and then the N(N > 1) equations are calculated according to Formula If the random number (3) Security—attacker steals private keyprimary_key, we cannot calculate the random number ran′. This kind of problem of solving discrete logarithm in the finite field cannot guarantee the unique calculation of the random number ran′ and ran′′. Even if we calculate the solution set, it is almost impossible to complete the verification by substituting it into the congruence equation, so the security can be guaranteed.Because of the complexity of the congruence equation in Formula (4) Anonymitymid, mid′, tem), mid and mid′ are calculated by random numbers ran′ and ran′′, so the signature is unique and unpredictable, which ensures the anonymity of trusted computing.In the process of authentication, the algorithm uses zero knowledge proof, and never publishes the private identity information. In the signature stage, it also uses the double random number signature authentication mechanism with the same anonymity. In the signature information ((5) Computational complexitymid′ shown in Formula m ≡ (xr + kλ + ts)mod(p − 1). In this paper, two large prime numbers, P and Q, are randomly selected in a credible way, and then the value of n is calculated by n = PQ. Because this paper uses double random number signature, the traditional algorithm only uses one random number. Therefore, the operation of random number in double random number signature will be calculated once more.In order to ensure the security of random number calculation after being stolen by attackers, this paper proposes a double random number signature authentication mechanism based on single random number calculation, and adds gm ≡ yrrλλsmodp becomes more complex and increases the amount of calculation. λ = gtmodp is added to the signature, but the time will not change much. So the time complexity can be calculated. The above operation increases the computational complexity, but the time complexity T(n) does not change, as shown in Formula In addition, compared with the traditional algorithm, the calculation of To sum up, the performance of the improved trusted computing technology proposed in this paper is better than that of the traditional trusted computing technology in terms of security and anonymity, and it is no more complex than the traditional trusted computing technology in terms of computational complexity, especially in terms of time complexity. Therefore, the improved trusted computing technology proposed in this paper is feasible. This paper have proposed that the double random number signature method proposed in this paper will perform one more operation, but the change of time is small, which can still guarantee the original time complexity.The proposed algorithm is mainly composed of trusted computing preparation, transaction model permission control, key storage migration, video abstract information extraction, and video transaction based on FISCO alliance chain. Through trusted identity authentication and DRM use control of FISCO alliance chain node, video summary information can be traded on the chain.FISCO alliance chain cannot resist the Byzantine attack without considering the non Byzantine attack initiated by the attacker, so the trusted authentication mechanism is essential in a secure and perfect transaction system. In addition, the transfer of video digest information is often accompanied by the transaction between the members of FISCO alliance chain, so it is necessary to prepare a trusted computing environment for the transaction. In this paper, the preparation method of trusted computing environment for transaction is divided into two stages, which are transaction model permission control method and key storage migration method.The node of video transaction based on (a) Access control method of transaction modelIn the traditional research field of copyright protection and privacy protection, the subject with its own unique behavior attribute can have partial authority to control the object, and the subject can take corresponding deployment decisions according to the behavior attribute. In addition, the transaction model permission control method also includes inherent permission control and user permission control.(1) Inherent authority control methodFISCO alliance chain should be within the scope of the license file all_license of the alliance chain, and the license of the alliance chain, as the core license file of the whole alliance chain, can Formulate the specific permission of video abstract information through the contract. In this paper, the license is defined by the right description language XrML It is unique and universal. The administrator can describe the information of the buyer or seller node freely and normatively, including the user permission information.This control method stipulates that the use of video abstract information by all the member nodes based on (2) Method of user authority controlThis control method first authenticates all the member nodes entering the trading system in the form of password, password, fingerprint, etc. only the user who has passed the authentication has the right to access and operate the trading system, and the system can track the user’s usage log.(b) Key storage migration methodFISCO alliance chain needs to replace the hardware device bound with the key due to irresistible reasons or non Byzantine errors, the new hardware device must have a strong robustness and fault-tolerant key storage migration method to ensure that it can continue to use the completed video.If the member node in (1) Key storage methodMerkleroot. The parent key starts from the root node. The storage root node is the core of the system, and the exposure of the root node means the loss of all the keys, as shown in The trusted platform includes binding key, signature key, legacy key, migration key, storage key and identity key. Due to the limited storage capacity of the trusted platform, the platform is not enough to store all the keys at the same time. Therefore, this paper considers the combination of external storage and platform module storage. Therefore, the concept of parent key is introduced. The parent key storage system is similar to (2) Key migration methodTPM_TakeOwnership function and stored in the trusted platform module. Therefore, when the key is migrated, the certificate of the trusted platform module cannot be provided and the migration operation cannot be completed.The authorization value of the key is determined by the user, and the certificate of the trusted platform module is randomly generated by the TPM_AuthorizeMigrationKey function to authorize the migration and protect the key, generates the authorization package and obtains the authorization information, and then creates the key migration block through TPM_CreateMigrationBlob function. After receiving the key migration block, the new trusted platform module converts it into a new platform key block through TPM_ConvertMigrationBlob function, and finally loads the new key into the trusted platform module using TPM_LoagKey function to complete the key migration. The process is shown in The trusted platform module uses DoS attacks, bitcoin sets the block size to 1MB/block. This regulation limits the possibility of large files trading on the blockchain. Therefore, this paper uses Merkle tree to collect transactions and package them. In the algorithm proposed in this paper, each transaction will go through different processes from the generation of the client to the sending of the signature to the nodes in the alliance chain. In order to improve the efficiency of the transaction, this paper uses the video abstract information which can uniquely identify the video as the transaction object.To prevent (a) Analysis of video abstract informationFISCO alliance chain and improved trusted computing, which allows video transaction between member nodes joining the alliance chain. The object of transaction is the video summary information of the traded video, including the video ID automatically generated by the local database of the video seller, the video name, video size, video format and video content provided by the video seller Frequency duration, video frame rate, resolution (wide), resolution (high), total video frames, video creation time, video latest access time, video latest modification time, responsible person signature and signature time. All the above information is expressed in string form, and finally connected into a long string that can uniquely represent the video. In order to facilitate the processing of video abstract information, this paper uses Hash based on sha256 to calculate the Hash value of video abstract information for transaction, as shown in This paper proposes a video transaction algorithm considering (b) Video abstract information extractionFISCO alliance chain, member nodes trade the Hash value of video abstract information, so this paper uses OpenCV, a cross platform computer vision and machine learning software library licensed by BSD, to extract video abstract information. As shown in Hangzhou’s latest Promo”.In order to improve the efficiency of video transaction based on FISCO alliance chain is priced. Secondly, match transaction execution. Finally, a smart contract is developed to supervise the execution of the transaction. The transaction algorithm is divided into base layer, core layer, service layer and user layer from bottom to top, as shown in The proposed algorithm is divided into three steps in the specific transaction. Firstly, among the videos waiting for transaction, the video that can be matched by (a) Video intelligent pricing strategyFISCO alliance chain, some videos can be priced by member nodes independently. Meanwhile, in order to improve the transaction rate and execution efficiency, we must consider the short-term video transactions with the characteristics of “extremely fast output speed, extremely fast passing speed and extremely fast depreciation speed”. This paper innovatively proposes that the algorithm intelligently price the short videos, etc (hereinafter referred to as “pricing video”). “Massive, inexpensive, unified pricing” of video resources for intelligent pricing.In the video transaction algorithm based on m video media producers (sellers) in the member nodes of FISCO alliance chain, that is the seller producer ∈ {1, 2, …, m}; there are n video media buyers. These nodes as sellers can also become buyers when they have the intention to buy, so the maximum number of buyers may be m+n, that is consumer ∈ {1, 2, …, m + n}. The actual number of pricing videos sold by a member node in a transaction cycle is videooutput, and the total number of pricing videos actually purchased is videoinput. Suppose that in a certain period, the average purchase price  of all member nodes for the pricing video is priin and sale price priout of the pricing video to be calculated by the smart pricing strategy in this period should be at the average price In the interval, as shown in Formula Suppose that there are In this paper, two different situations are considered to calculate the price of the pricing video:(1)videooutput ≥ videoinputThe total number of pricing videos actually sold by all member nodes in a transaction cycle is greater than the total number of pricing videos actually purchased, which means that the number of pricing videos is sufficient. In order to ensure the normal sale of pricing videos, the pricing strategy should be inclined to low price, that is, the sum of the total amount of selling pricing videos and the total amount of purchasing pricing videos should be equal to the total income of the seller, as shown in Formula FISCO alliance chain exchange, as shown in Formula In the pricing strategy proposed in this paper, the buyers and sellers get the same additional income as those from the priin and the sale price priout can be calculated, as shown in Formula According to the above Formula, the purchase price (2)videooutput < videoinputThe total number of pricing videos actually sold by all member nodes in a transaction cycle is less than the total number of pricing videos actually purchased, which means that the number of pricing videos is insufficient. In order to ensure the normal sale of pricing videos, the pricing strategy should be inclined to high price, that is, the sum of the amount of extra expenses and the total revenue of the seller is the total expenditure of the buyer, as shown in Formula priin and the sale price priout can be calculated, as shown in Formula According to the above Formula, the purchase price (b) Video transaction algorithm(1) Token and incentive mechanism ofFISCOalliance chainThe algorithm will set a certain number of initial tokens for each member node. The initial token is directly transferred to the trading smart contract account through the process specified in the smart contract, which is called the minimum admission fee. The role of this rule is to prevent the remaining tokens from being insufficient to pay for the actual purchase of video in the previous period in the transaction settlement stage. After the transfer of the minimum admission fee is successful, the smart contract will create an admission fee data structure for the member node, as shown in Algorithm 1.After the data amount of member node reaches the amount specified in the smart contract, it enters the pre transaction stage. In this stage, the seller of the pricing video submits the forecast sales volume of the next cycle through the video volume function, and the buyer pays in advance through the prepaid pricing video transaction fee. Before the prepaid transaction fee is used up, the buyer can continue to purchase the pricing video.Settlement strategy(2) FISCO alliance chain network through the actual transaction function. The data package sent when uploading contains the summary information of the sale/purchase video, the user’s Ethereum account address, and the digital signature generated by using the user’s private key. The function of digital signature is to verify whether the packet is real and valid, as shown in Algorithm 2.The video sold by the member node, or the data generated by the purchase of video, is uploaded to the (c) Strategy of smart contract makingFISCO alliance chain token contract and transaction contract. Because the transaction of member nodes in FISCO alliance chain is cyclical and corresponding to real world currency. Therefore, in order to facilitate the settlement between financial institutions, the FISCO alliance chain token should have stable value. The consensus mechanism of POA does not have the feature of block reward, which makes it necessary for financial institutions to issue tokens. The token set in this paper is based on ERC233 standard, as shown in Algorithm 3.The algorithm proposed in this paper is divided into two modules in the aspect of intelligent contract making. balanceOf(address_owner) function can query the number of FISCO alliance chain representatives, transfer function can transfer the FISCO federation chain token to another account address.Where FISCO alliance chain specified by the algorithm, and the video transactions based on the FISCO alliance chain are realized through the transaction contract, which mainly includes five core functions: admission function, video volume function, prepayment function, actual transaction volume function and transaction settlement function, as shown in The transaction contract is issued by the member nodes of the FISCO alliance chain innovatively proposes a distributed storage permission control scheme in order to control the permissions of alliance chain more flexibly. Based on external account access, the algorithm controls the rights of contract deployment and read-write table operation. The transaction process can be monitored and traced. In the experiment, FISCO alliance chain member nodes include alliance chain administrator, system administrator, member node user and smart contract, as shown in In the algorithm proposed in this paper, FISCO alliance chain initiate the transaction request through the client, the member nodes get the data about the transaction. Through the data to obtain the external account, obtain the table to be operated and the operation table.In the experiment, after the member nodes of The digital ID card contains public information and encrypted information. The public information includes video ID, storage location, owner, video summary and generation time; The encrypted information includes the video source code obtained in the previous step, watermark information coding and video fingerprint information coding.After getting this digital ID card, all videos involved in the transaction method are uniquely identified by this digital ID card.If the node chooses to register, it will submit its basic information and wait for the existing member nodes to confirm in turn, and then return to log in again after the confirmation. If you do not choose to register, the system denies the node’s access request. The identity authentication of the parent chain member node is shown in The smart contract will integrate the process information and the signature of the person in charge of this step to perform a hash operation, and obtain the hash code of this step as label information and store it in the private area. In the blockchain, the current progress of the video work is then transferred to the video improvement team. the calculation process of the video traceability source code is shown in Establish a video ID card, which contains two sets of information: public information-video ID, storage location, party of the video, brief introduction of the video and the time the video was generated; encrypted information-video watermark code, video fingerprint code and video Trace the source code. Calculate the HID code of the video ID card for all the information of the video ID card. This Hash code can represent the operation of the on-chain storage and transaction information on the video. the calculation process of the video watermark code, fingerprint code and ID card is shown in FISCO alliance chain and improved trusted computing provide a trusted, traceable and provable transaction environment for video transaction, and use hierarchical intelligent contract structure to manage the transaction. Among them, the factory contract is agreed by all parties of the member node in advance, which stores the effective conditions of the transaction and manages the generation of the transaction; the transaction contract is generated by the factory contract, which stores the unique identification serial number (ID), Hash value and signature value of all parties, that is, each transaction has a contract. The interaction between factory contract and trade contract can make the system more scalable. The main business process of the experiment is to collect and analyze the public key information of all the member nodes in the FISCO alliance chain and deploy the factory contract, then in the process of transaction, the video seller sends the signed transaction information and broadcast the uplink request, the member nodes receive the uplink request, take out the transaction information and confirm and sign, and finally complete the uplink operation of the transaction information.build_ chain.sh Deploy a 4-node FISCO federation chain, download the console and update the public and private key information of the signature authority after the completion of the construction, and finally copy the node certificate.The experiment will be based on the Ubuntu 20.04 64bit system using the development tool FISCO federation chain configuration file applicationContext, where User is the member node user and the corresponding private key file is user.jks. Arbitrator is the member node of transaction verification, and the corresponding private key file is arbitrator.jks. Depositor is the member node of transaction storage, and the corresponding private key file is depositor.jks.This paper experimentally conFigures the role public key of the FISCO alliance chain.The video material used in the paper experiment is from the public data set HMDB51 , which cbin folder, the toolkit configuration file is stored in conf folder, the transaction algorithm dependent package is stored in lib folder, and the smart contract is stored in contracts folder. Firstly, the environment of the toolkit is initialized, and the public–private key pair is updated according to the actual needs, in which the public key is stored in the configuration file in the form of key-value.In the experiment, the execution script is stored in FISCO alliance chain provides intelligent contract interface development mode, which can operate the creation table, add, delete, modify and query data table in the database through intelligent contract. Moreover, intelligent contract needs to be compiled into ABI file and BIN file before it can be deployed to FISCO alliance chain. This file can be deployed and called by virtue of JavaSDK. java directory generated org/FISCO/bcos/asset/contract/ package path directory, the directory contains Asset.java and Tablejava Two files, of which Asset.java, it’s a Java application call Asset.sol documents required for the contract. Thesis experiment in build.gradle Add a reference to FISCO bcos Java SDK under dependencies in the file and modify the build.gradle. The file introduces the spring framework.SDK certificate is consistent with the Java SDK configuration. In the experiment, there are initialization code, construction of contract class object and interface call in the calling of FISCO alliance chain Java SDK.The experiment configuration WEB3J, deploying contract object, loading deployed contract, creating transaction, sending transaction signature data, obtaining transaction details and verifying transaction correctness. The experimental process of this paper can be summarized as follows: the FISCO federation chain node communicates with the FISCO federation chain client node through the Java-Wrapper class generated by WEB3J and the JsonRpc call, and then the client returns the response request JsonRpc to the node.The call of smart contract in the experimental client mainly includes initializing Compared with the traditional video transaction algorithm, the video transaction algorithm considering FISCO alliance chain and improved trusted computing proposed in the paper is efficient and can make obvious progress in many aspects, In terms of [convention of data storage], [data capacity], [data storage flexibility], [operational flexibility], the algorithm proposed in this paper has advantages, which greatly improves the performance of pow algorithm and traditional storage, In the aspect of [data atomicity] [privacy and security], the algorithm proposed in this paper is not greatly improved, but also improved. In the aspect of representativeness of stored data, the algorithm proposed in this paper has no obvious improvement compared with the traditional storage, which is the problem to be studied in the next step, as shown in This paper provides a new algorithm for video transaction. The experimental results show that the method performs well in robustness and efficiency. This paper first solves the problem that large video files cannot be traded on the chain by extracting video abstract information. Then, through the improved trusted computing, the non Byzantine attack in the transaction process is solved. The next research goal of this paper is how to store the large capacity video on the chain, and how to encrypt the transaction details.10.7717/peerj-cs.594/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj-cs.594/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj-cs.594/supp-3Supplemental Information 3Click here for additional data file.10.7717/peerj-cs.594/supp-4Supplemental Information 4Click here for additional data file.10.7717/peerj-cs.594/supp-5Supplemental Information 5Click here for additional data file.10.7717/peerj-cs.594/supp-6Supplemental Information 6Click here for additional data file.10.7717/peerj-cs.594/supp-7Supplemental Information 7Click here for additional data file.


CDKN1ACip1/ (p21) and its family members p27 and p57 regulate signaling pathways fundamental to placental development. The aim of the present study was to enlighten the individual roles of these cell cycle regulators in placental development and their molecular involvement in the pathogenesis of PE. The expression and localization of p21, phospho-p21 (Thr-145), p27, and p57 was immunohistochemically analyzed in placental tissues from patients with early-onset PE, early-onset PE complicated by the HELLP  syndrome as well as late-onset PE compared to their corresponding control tissues from well-matched women undergoing caesarean sections. The gene level was evaluated using real-time quantitative PCR. We demonstrate that the delivery mode strongly influenced placental gene expression, especially for CDKN1A (p21) and CDKN1B (p27), which were significantly upregulated in response to labor. Cell cycle regulators were highly expressed in first trimester placentas and impacted by hypoxic conditions. In support of these observations, p21 protein was abundant in trophoblast organoids and hypoxia reduced its gene expression. Microarray analysis of the trophoblastic BeWo cell line depleted of p21 revealed various interesting candidate genes and signaling pathways for the fusion process. The level of p21 was reduced in fusing cytotrophoblasts in early-onset PE placentas and depletion of p21 led to reduced expression of fusion-related genes such as syncytin-2 and human chorionic gonadotropin (β-hCG), which adversely affected the fusion capability of trophoblastic cells. These data highlight that cell cycle regulators are important for the development of the placenta. Interfering with p21 influences multiple pathways related to the pathogenesis of PE.Preeclampsia (PE), a gestational hypertensive disease originating from the placenta, is characterized by an imbalance of various cellular processes. The cell cycle regulator p21 Pregnancy can be affected by various health problems, of which preeclampsia (PE) is the most common. PE is a multisystemic gestational disease with a global prevalence of up to 8% . It is cDefective placentation is considered to be causative for the development of pregnancy-related disorders like PE, fetal growth restriction , and theCip1, encoded by the gene CDKN1A (cyclin-dependent kinase inhibitor 1A), is a pivotal broad cell cycle regulator with heterogeneous roles and the founding member of the Cip/Kip (cyclin-dependent kinase interacting protein/kinase inhibitory protein) family including p27Kip1 (CDKN1B) and p57Kip2 (CDKN1C) [The rapid development of the human placenta requires strictly regulated and coordinated cell proliferation and differentiation processes, crucial for tissue homeostasis . While a(CDKN1C) . Interes(CDKN1C) . Apart f(CDKN1C) . p21 act(CDKN1C) ,24. Sinc(CDKN1C) . In the This study was approved by the Ethics Committee at the University Hospital (reference number: 375/11), Goethe-University Frankfurt. Written informed approval was obtained from all donors. PE was diagnosed as an occurrence of hypertension after 20 weeks of gestation with a blood pressure ≥140/90 mmHg and proteinuria with ≥300 mg in 24 h. The HELLP syndrome was defined as the presence of hemolysis, elevated liver enzymes, and thrombocytopenia . The reasons for delivery of early-onset control groups were PE-irrelevant like breech presentation, premature rupture of membranes, premature placental abruption, non-reassuring fetal heart rate, or umbilical cord prolapse. Tissue samples were taken from placentas within 30 min post-delivery, formalin-fixed and paraffin-embedded (FFPE) for immunohistochemistry staining (IHC), or frozen immediately in liquid nitrogen for mRNA and protein extraction, which were stored at −80 °C until usage. Clinical information of all participants is shown in . For IHC4Cl, 10 mM KHCO3, 0.1 mM EDTA) [g, 5 min), and washed twice with PBS. Cells were plated onto 24 well Corning Costar ultra-low attachment plates  or embedded in Matrigel . The trophoblast organoid medium (TOM) contained Advanced DMEM/F12 supplemented with 1× N2 (Life Technologies), 1× B27 (Life Technologies), 100 µg/mL primocin , 1.25 nM N-Acetyl-l-cysteine , 2 mM L-glutamine , 1 mM A83-01 , 1.5 µM CHIR99021 , 50 ng/mL EGF  , 100 ng/mL R-spondin 1 , 100 ng/mL FGF-2 (fibroblast growth factor) , 50 ng/mL HGF (hepatocyte growth factor) , 2 µM Y-27632 , and 2.5 µM prostaglandin E2  [2 in a humidified incubator at 37 °C. Medium was replaced every 2–3 days. Small organoid clusters became visible around day 10  , incubatMN, USA) . Cultured day 10 .® Histofix solution  for 30 min on ice, washed twice with PBS containing 0.1% BSA and stored at least overnight in 70% ethanol at 4 °C. For visualization, organoids were stained with a drop of hematoxylin for 5–10 min, washed gently with Aqua dest., mixed with 100 µL Histowax , and incubated for 30 min on ice for embedding. Five µm sections were prepared. After deparaffinization, the slides were incubated with the target retrieval solution from DAKO EnVisionTM FLEX Kit  for 15 min, or 30 min in the case of placental tissue sections in a water bath (100 °C), blocked with peroxidase for 5 min, and incubated with primary antibodies for 60 min at room temperature. Following primary antibodies were used: rabbit monoclonal p21 , mouse monoclonal cytokeratin 7 , mouse monoclonal E-cadherin , rabbit monoclonal epidermal growth factor receptor (EGFR) , mouse monoclonal human leukocyte antigen G (HLA-G) , and mouse monoclonal Ki67 . This was followed by the incubation with secondary antibodies for 30 min at room temperature: goat anti-rabbit or goat anti-mouse Alexa Fluor® 594  and goat-anti mouse DyLight® 488 or goat anti-rabbit Alexa Fluor® 488 . DAPI  was used to stain the DNA content. Slides were examined with an AxioObserver.Z1 microscope  equipped with an AxioCam MRm camera .For paraffin embedding, organoids embedded in Matrigel were gently collected into cold medium, washed with PBS containing 0.1% BSA , fixed in ROTIIsolation of villous cytotrophoblasts from first trimester placenta was performed according to Haider et al.  and VondThe isolation protocol by Stiegman et al.  was modig, 15 min). The digestion, transfer, and centrifugation steps were repeated two more times. The pellet was resuspended in DMEM  and filtered with a 100 μm cell strainer . The cells were centrifuged , resuspended in Ca/Mg-free Hank’s balanced salt solution, and stratified on two Percoll gradients . The gradients were centrifuged without brake . The fractions between 35 and 50% of the gradients were used, pooled, and diluted in pre-warmed medium for centrifugation . The cell pellet was resuspended in erythrocyte lysis buffer  [g, 5 min), and washed twice with PBS. The remaining cells were seeded onto 15 cm cell culture plates in DMEM/F12 (Life Technologies) containing 20% FBS , 100 μg/mL streptomycin, 100 U/mL penicillin, and 1 µg/mL amphotericin B  for 45 min to remove adherent stromal cells. Non-adherent trophoblastic cells were collected, seeded onto collagen-coated plates , and cultured under standard cell culture conditions.Villous cytotrophoblast cell isolation and purification was carried out according to Petroff et al. . In briemM EDTA) , incubatTMFLEX Kit  was used to stain FFPE placental tissue sections from PE patients and matched controls, as stated [A standard staining procedure with DAKO EnVisions stated . The fols stated ,35.SDHA , TBP (TATA box-binding protein), and YWHAZ  or TBP alone served as the endogenous control [GAPDH  was used as the endogenous control. The primers and probes for GAPDH (Hs_02786624), CDKN1A (Hs00355782_m1), CDKN1B (Hs_00153277_m1), CDKN1C (Hs00175938_m1), TP53 (Hs01034249_m1), HERV-FRD (Hs01942443_s1), CGbeta5 (Hs00361224_gH), GCM1 (Hs_00961601_m1), GATA3 (Hs00231122_m1), TFAP2A (Hs01029413_m1), TFAP2C (Hs00231476_m1), ELF5 (Hs01063023_g1), SDHA (Hs00188166_m1), TBP (Hs99999910_m1), and YWHAZ (Hs00237047_m1) were obtained from Applied Biosystems . All results were shown as relative quantification (RQ) [Total RNAs were extracted with EXTRACTME Total RNA Kit, with DNase digestion for tissue samples or without DNase digestion for cell lines, according to manual instructions . In the case of first trimester samples, total RNAs were extracted from FFPE tissues using the ReliaPrep™ FFPE Total RNA Miniprep System as instructed . Reverse transcription was performed using the Go Script Reverse Transcription Mix as instructed . A StepOnePlus Real-time PCR System  was used to perform real-time quantitative PCR and data were analyzed with StepOne Software v2.3 . To analyze primary placental tissue, the mean value of expression levels of  control ,37. For  Hs001759_m1, TP532 incubator .The HTR-8/SVneo cell line (referred to as HTR) was kindly provided by Prof. Dr. Charles Graham  and the TM  [siRNA targeting p21  was manufactured by Sigma-Aldrich . A different siRNA against p21 (referred to as sip21 #2), containing a mixed pool of siRNAs, was obtained from Santa Cruz . Control siRNA was obtained from Qiagen . siRNAs (30 nM). Cells were transiently transfected with siRNA with OligofectamineGermany) .Trophoblast fusion was induced by treating cells with 25 μM forskolin  for indicated time points. An equal amount of dimethyl sulfoxide  was used as the vehicle control.Western blot analysis was performed as reported . Cells wIndirect immunofluorescence was performed as reported ,41. Foll® HD transfection reagent  for 48 h. Cells were harvested with cell culture lysis reagent from Promega GmbH  and the assays were performed with the luciferase assay system from Promega GmbH .BeWo or JEG-3 cells were treated with scrambled siRNA (sicon) or siRNA against the 3′-untranslated region (UTR) of p21 (sip21) or mixed siRNAs against the coding region of p21 (sip21 #2). After 24 h, the syncytin-2 (2 µg) promoter plasmid  was tranp-value (Student’s t-test) less than 0.05 were selected. A full gene list is available as p-value smaller than 0.05.BeWo cells were treated with control siRNA or siRNA targeting the UTR of p21 (sip21) for 48 h. Cells from three independent experiments were harvested and the total RNA was isolated using RNeasy Kits . The expression was assessed using Human HT-12 v4 Beadchip , a direct hybridization whole-gene expression array. The expression profiling service from the German Cancer Research Center  was used. The most significant genes with a t test, or, if not Gaussian distributed, with the non-parametric Wilcoxon-test (paired) or the Mann–Whitney U test (unpaired samples). Difference was defined as statistically significant when p < 0.05.Outliers were detected with Grubbs’ test . Data distribution normality was analyzed with the Shapiro–Wilk test and statistical significance was analyzed with the Student’s CDKN1C (p57), which was elevated over 2-fold in placental tissues from labor deliveries compared to elective caesarean sections [CDKN1A (p21), CDKN1B (p27), and CDKN1C (p57). Placental tissues were collected from healthy women with different delivery modes without significant differences in gestational age, maternal age, and maternal body mass index (BMI)  . Total RGATA3 (GATA binding protein 3), TFAP2A , TFAP2C (transcription factor AP-2 gamma), and ELF5 (E74 like ETS transcription factor 5)  isolated from first trimester placental tissues. Additionally, relative to first trimester pCTBs, trophoblast organoids expressed very high levels of CGbeta5 (β-hCG)  according to well-established protocols ,28,29. Vactor 5) , previou (β-hCG) . IHC-IF  (β-hCG) . In comp (β-hCG) C. Intere (β-hCG) B,C, in tFor further analyses, we used sections of placental tissues with gestational ages between six and nine weeks, between 25 and 33 weeks as well as between 34 and 40 weeks from normal donors. Using IHC, placental sections were stained for p21, p–p21 (Thr-145), p27 or p57, and counterstained with hematoxylin. Whereas p21’s role in cell cycle arrest is attributed to its nuclear localization, its phosphorylation at Thr-145 by distinct kinases is described as a marker for cytoplasmic translocation or enhanced protein stability contributing to cell cycle progression . Placentn = 6), between 25 and 33 weeks , CDKN1B (p27), and CDKN1C (p57) was evaluated in placental tissues from the first trimester samples (named 6–9 week) compared to early- and late-onset controls  and CDKN1B (p27)  F.Ten late-onset PE samples and ten control tissues from well-matched donors  were alsCDKN1A (p21) and CDKN1B (p27) (Since early-onset PE is often complicated by the HELLP syndrome (ePEH) , placent1B (p27) F, as obs1B (p27) F.2) or hypoxic conditions (1% O2) for 48 h. The gene levels of CDKN1A (p21), CDKN1B (p27), CDKN1C (p57), and TP53 (p53), the master regulator of p21, were measured. CDKN1A was significantly reduced under hypoxic conditions in SGHPL-4 cells, whereas CDKN1B, CDKN1C, and TP53 were decreased but not significantly (CDKN1A and CDKN1B (2) or under hypoxic conditions (1% O2) for 48 h. The expression of cell cycle regulator genes was also affected, showing a significant decline in CDKN1A, CDKN1B, CDKN1C, and TP53 under hypoxia , CDKN1B (p27), and TP53 (p53) were significantly reduced in primary cytotrophoblasts under hypoxic conditions  were isolated from five term placentas of healthy donors, which were grown under normoxia or hypoxia and compared to pCTBs isolated from late-onset PE patients grown under normoxic conditions . The chanditions G. Intereple size G.p-value smaller than 0.05, and a fold change greater than 1 (red color code) and below 1 (blue color code), respectively . ERK3 is a distantly related member of the mitogen-activated protein kinase (MAPK) superfamily [HERV-FRD (syncytin-2), ERVWE1 (syncytin-1), CGbeta5 (β-hCG), KLF6 (Krüppel-like factor 6), and GCM1  were reduced  and its family members p27 (CDKN1B) and p57 (CDKN1C) as well as their roles in normal pregnancy and hypertensive disorders. We show here that these cell cycle regulators are highly expressed in first trimester placentas, while their expression generally decreases in the second and third trimester placenta at the protein as well as gene level. Notably, fCTBs, a special portion of CTBs ongoing to fuse into the STB, express high levels of p21 and its family members, which remain high throughout gestation. Importantly, the level of p21 is only reduced in fCTBs of early-onset PE placental tissues and its overall protein expression is decreased in early-onset PE complicated by the HELLP syndrome. These data strongly support the notion that early- and late-onset PE derive from distinct pathogenesis. Moreover, cell cycle regulators are decreased upon hypoxic conditions and depletion of p21 leads to reduced expression of fusion-related genes and an impaired fusion capacity of trophoblastic cells. In addition, the expression of these cell cycle regulators is dependent on the delivery mode, underscoring the importance of optimization and standardization of patient selection and placental collection for proper interpretation of existing data on cell cycle regulators.The cell cycle regulator p21 is a key player in various cellular events including cell differentiation, migration, stem cell maintenance, and gene transcription , processWe show that overall p21 was reduced in early-onset PE and early-onset PE complicated by the HELLP syndrome, whereas it was unaltered in late-onset PE, suggesting its potential involvement in the development of early-onset PE. Several studies provide insight into p21′s roles in PE and are, however, accompanied by inconsistency and divergence: one study reported that the gene and protein expression of p21 was increased in preeclamptic placentas , wherebyCDKN1A (p21) and CDKN1B (p27) in diverse trophoblastic cell lines, organoids derived from first trimester placenta, and isolated primary cytotrophoblasts. Others reported that the p21 protein was downregulated in CTBs upon 2% oxygen supply for 72 h, which was 3.8-fold higher in normoxia cell extracts isolated from explants of anchoring villi of first trimester placenta [TP53 (p53), the upstream regulator of p21. However, the p53 protein expression from whole cellular lysates was not affected. p53 downregulation was reported in the STB of primary isolated term trophoblasts upon 1% hypoxia for 24 h, associated with the induction of apoptosis [CDKN1A in human pulmonary artery smooth muscle cells upon hypoxia [PE, especially early-onset PE, is associated with constant hypoxia and oxidative stress of the placenta . Interesplacenta . Moreovepoptosis . Evaluatpoptosis  or TFAP2poptosis  are knowpoptosis ,59. In a hypoxia . Interes hypoxia . These rCDKN1A during differentiation of mouse trophoblast stem cells and fusion of BeWo cells upon forskolin treatment [HERV-FRD (syncytin-2), CGbeta5 (β-hCG), and GCM1 were reduced upon p21 depletion. Importantly, decreased p21 significantly reduced the expression of syncytin-2 in a promoter-dependent manner in BeWo and JEG-3 cells. Indeed, p21 has been reported to interact as a co-activator with GCM1 to bind to the promoter region of syncytin-2, regulating its transcription [PE is associated with profound cellular dysfunctions including reduced differentiation and fusion ability , and p21reatment , whereasreatment . We repocription . Our fincription . Recentlcription . Of signcription . In sum,The studies concerning p27 and p57 in PE are rather limited: in one study, p27 and p57 were significantly increased in preeclamptic placentas . HoweverDimerization partner, RB-like proteins, E2Fs And Multi-vulval B) multiprotein complex [TXNIP, which encodes the protein thioredoxin interacting protein, a major regulator of the cellular redox signaling, protecting cells from oxidative stress [It has been shown that the co-expression of p53 and p21 can lead to cell cycle arrest via suppression of G2 phase and mitotic (M) genes by the DREAM ( complex ,77. In c complex . Remarkae stress . Interese stress . TXNIP le stress , wherease stress . FurtherTaken together, we show that p21 and its family members p27 and p57 are highly expressed in the first trimester of pregnancy, pointing to their importance in early placental development. The expression of p21 in CTBs and the STB is further highlighted with 3D trophoblast organoids, which have been reported to mimic the placental villi structurally, phenotypically, metabolically, and endocrinologically ,29. More


The present experimental design allowed binary decisions . These decisions were made on complex social interaction scenarios displayed on videos. The videos were taken from a first-person perspective. They were preceded by one sentence each that provided additional information about the context of the displayed scenario. The sentence preceding the video and the video jointly provided a context of emotional valence. That context varied from trial to trial. We observed that provocative and threatening videos produced predominantly fear and anger responses. Fear was associated with withdrawal decisions, while anger led to approach decisions. Negative contextual information increased the probability of approach decisions in aggressive provocative videos; positive contextual information enhanced the chance of approach decisions in socially positive videos. In neutral situations, displayed in videos, the probability of the approach behavior was reduced in case of negative contextual information. Yet, the probability for approach behavior was increased if positive contextual information preceded neutral videos. Our experimental setup provided a paradigm that can be adapted and accommodated for the examination of future research questions on social decisions in multidimensional, complex social situations. Social interaction, especially in conflict situations, is characterized by ambiguity and uncertainty .In the present study, we intend to answer this question with a quasi-realistic experimental design. For this purpose, we manipulated two kinds of information. The first kind of information was presented in one sentence that constituted a specific social context . This information established a context for a social interaction that was afterward presented in a short video clip. Each social interaction displayed in the video clips was filmed from a first-person perspective. The videos showed the beginning of a social interaction between a spectator  and another person that was not known by the participants. Participants were asked to decide how they would respond in this situation. In particular, participants were asked if they would decide to get proactively involved in the social interaction , or if they would prefer to withdraw calmly from the social interaction  that created the context we expected to influence participants' decisions in the social interactions. Hence, we combined two sources of information  about the social interaction in each experimental trial. The first source was the sentence . The second source of information was the video-clip  presented in each trial.All social interactions were filmed in everyday life contexts as for instance in public places in a city, in underground car parks, in gardens and parks, and so forth. The video-clips displayed social interactions that were either a threat  or socially positive  or the social interaction was rather neutral . We predicted that emotional information on a social context that precedes a social interaction  modulates decisions distinct in different kinds of social interaction scenarios . Based on our past experience and current theoretical models we propose the following predictions:(1) Evaluation of the sentences : Analogously to Fehr et al. , we expeValence ratings of the sentences will be lowest for sentences with negative content, moderate for sentences with neutral contents, and highest for sentences with a positive content  Evaluation of the social interactions displayed in video-clips (= attribute 2): Based on the findings by Fehr et al. , we expeBased on their own life experience, participants were expected to be most familiar with socially positive and neutral interactions compared to aggressive provocative social interactions resulting in higher familiarity ratings. Unambiguity ratings for the contents of the video-clips  were expected to be higher rated than a moderate level of 5 on a 10-point rating-scale for all categories of the video-clips. This means that the interpretation of the social interactions was expected to be rather clear in all three categories of social interactions.We assumed that the categorization of the video-clips based on the affect they induce would result in the same profile for negative , socially positive (predominantly rated as inducing happy feelings), and neutral (producing serenity) social interactions as for the sentences .In the video evaluation part, participants were asked to decide whether they would approach, remain passive, or withdraw in the given situation. According to Fehr et al. , we expe(3) Expected interactions between sentences and video-clips in the experimental run: Sentences preceding the video-clips  were expected to strengthen behavioral tendencies associated with a certain kind of social interaction. For example, sentences providing negative social information like “Thomas is known to harm weaker persons” were maintained to support approach tendencies in response to provocative aggressive social interactions  Correlation analyses: We expected that traits potentially related to physical aggression  and INTENSITY  = 170.1; p < 0.001, GG-Epsilon = 0.95]. These main effects were explained by high arousal and intensity ratings of sentences with negative social information , followed by sentences describing positive social information , and lowest arousal and intensity ratings of sentences with neutral information .Details about the assessments of the sentences preceding the video-clips are illustrated in F = 384.8; p < 0.001, GG-Epsilon = 0.58] was explained by significantly higher negative ratings for negative sentences , ratings around 0 for neutral sentences, and rather positive ratings for positive sentences . There was a significant interaction between the emotional categories of SENTENCEs  and the CATEGORIZATION of the emotions triggered by these sentences into the four categories of anger, fear, serenity, and happiness, F = 540.8; p < 0.001, GG-Epsilon = 0.49. The interaction could be explained by the fact that emotions generated by negative sentences were mostly categorized as anger or fear, emotions triggered by neutral sentences were mostly categorized as serenity, and emotions caused by positive sentences  were mostly categorized as feelings of happiness  = 40.1; p < 0.001, GG-Epsilon = 0.65], FAMILIARITY , and UNAMBIGUITY . Provocative aggressive video-clips received the highest AROUSAL ratings, followed by socially positive video-clips, and neutral video-clips. Socially positive video-clips were rated as most FAMILIAR, followed by neutral video-clips and provocative aggressive video-clips. UNAMBIGUITY ratings were highest for socially positive video-clips.Details about the assessments of the video-clips  on post-experimental stimulus evaluation are illustrated in F = 271.9; p < 0.001, GG-Epsilon = 0.46]. This interaction could be explained by high ratings of anger and fear as responses on provocative aggressive interactions, by high ratings of serenity for neutral social interactions, and by high ratings of happiness for socially positive interactions  and the CATEGORIZATION of emotions provoked by the video-clips  . This interaction was due to a high frequency of withdrawal choices, followed by a lower frequency of approach choices in provocative aggressive interactions. For neutral interactions, participants chose predominantly to remain passive. In socially positive interactions, participants most often picked the option to approach this social interaction  and BEHAVIORAL TENDENCY on how to respond in this social interaction . There was also a main effect of the factor CATEGORY of the video-clips . Interactions and/or main effects could be explained by generally lower scores on the preference index (PI) in CCs that included provocative aggressive video-clips. Furthermore, provocative aggressive video-clips that were preceded by negative sentences compared to neutral sentences resulted in higher scores on the PI, while neutral interactions  preceded by negative sentences compared to neutral video-clips preceded by neutral sentences ended up in lower PI scores  and negative (NEG) sentences (= context attribute 1) as a subset of sentences as one within-factor and the subset provocative aggressive (A) and neutral (N) video-clips (= context attribute 2) as a second within-factor revealed an interaction between SENTENCES (within: NEU vs. NEG) and CATEGORY of the video-clips (within: A vs. N) , a main effect of SENTENCE , and a main effect of CATEGORY of video-clip . Interactions and/or main effects were based on higher PI scores in positive social interactions  compared to the neutral interactions presented in video-clips and on higher PI scores whenever video-clips, irrespective of their emotional content, were preceded by sentences with positive information  and positive (POS) sentences (= context attribute 1) as one within-factor and socially positive (P) and neutral (N) video-clips (= context attribute 2) as a second within-factor in an ANOVA revealed an interaction between SENTENCE (within: NEU vs. POS) and CATEGORY of video-clips (within: P and N) [F = 11.5; p < 0.001, GG-Epsilon = 0.75. All UIs were significantly below 0.5 when tested in one-tailed t-tests  estimated the consistency of participants' decisions in identical combinations of sentences and video-clips (see above). To justify subsequent statistical analyses, we calculated a repeated-measurement ANOVA including UIs of all seven CCs. This ANOVA turned out as significant, T-tests showed significance levels of p < 0.05).All reported correlations in this section were significant  between self-reported ANGER and FEAR ratings on an 11-point scale (see above). ANGER correlated positively with approach decisions (r = 0.56), while it correlated negatively with the decision to withdraw from the social interaction (r = −0.62). FEAR correlated negatively with the approach decisions (r = −0.51) and with the decision to remain passive as well (r = −0.53). Self-reported FEAR also correlated positively with the decision to withdraw (r = 0.71). Further, self-reported ANGER correlated positively, and self-reported FEAR correlated negatively with personality traits that indicated the proneness to spontaneous (proactive) aggression  and proneness to reactive aggression , and it also correlated with the sum-score of the proneness to aggressive behavior  measured through the FAF  with the physical aggression scale of the AQ  correlated negatively , reactive aggression , and the sum-score of aggression of the FAF  and with ratings on the physical aggression scale  of the AQ .Data from the sentence stimulus evaluation and personality trait assessment: The same pattern of correlations between FEAR and ANGER CATEGORIZATION values and personality trait scores as reported above for the video-clips was found for the negative sentences. Self-reported ANGER and FEAR ratings on an 11-point scale (see above) correlated with trait spontaneous (proactive) aggression (ANGER: r = −0.65) and negative (CC neg-A: r = −0.43) sentences preceding provocative aggressive interactions . Furthermore, PI scores for neutral social interactions (displayed in the video-clips) preceded by negative sentences  and positively with physical aggression ratings on the AQ .Data from the experimental decision making runs  and personality trait assessment: Scores of the PI correlated negatively with the inhibition factor in the FAF in case of neutral . FEAR ratings were related to females . Familiarity with provocative aggressive interactions presented in video-clips was related to males (A-video-clips: r = −0.38). For neutral interaction video-clips  and serenity ratings were associated with males (r = −0.39).In order to inspire future research, several dot-biserial correlations were calculated between GENDER , several personality traits, and decisions. For both negative sentences NEG, see  and provs N, see , FEAR rar = −0.52), while withdrawal decisions were associated with females (r = 0.48). Based on data from the experimental runs , provocative aggressive interactions  and negative sentences . Neutral interaction video-clips .Based on the evaluation data, in provocative aggressive interactions , and in particular the reactive aggression score (r = −0.38). The subscale inhibition of aggression of the FAF . Scores of the AQ . Both the SFT .The sum score of the FAF  was constructed in a way that it presented realistic social interactions. The material was validated on different dimensions . The sentences (= context attribute 1) preceding the social interactions displayed in video-clips (= context attribute 2) modulated decisions on these social interactions. Note that the social interactions were of different valence and emotional category . Results are discussed in detail in the following sections.We predicted that our experimental material  reliably produced similar or even the same patterns of findings as Fehr et al. . Our resAs predicted, both reading sentences with a negative social content and watching video-clips with provocative aggressive interactions mainly produced feelings of anger and fear  prior to watching a social interaction  on approach or withdrawal decisions. We suggested that the information provided in the sentences and in the video-clips were integrated and used jointly for decisions in different emotional social contexts . An uncertainty index revealed that participants consistently decided on how to respond to a given social interaction across two experimental runs.In line with Bettencourt et al. , who sugSummarizing, context information that was displayed prior to social interactions modulated decisions on how to respond to a given social interaction. This observation confirmed assumptions about the modulatory potential of context information in quasi-realistic decision situations . Fear as an emotional response on provocative aggressive interactions correlated with preferences for withdrawal  significantly increased the likelihood of approaching the social interaction. In contrast, approach decisions in provoking aggressive social interactions  were supported by preceding negative information. Decisions in neutral social interactions interacted with preceding positive information resulting in more prosocial involvement decisions , while negative preceding information increased the likelihood of withdrawal decisions, and neutral preceding information led to both proactive and withdrawal decisions.The video-clips were evaluated reliably (cf., Fehr et al., The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical approval was not provided for this study on human participants because at Bremen University, behavioral studies involving human individuals do not require an approval by the ethics committee. The patients/participants provided their written informed consent to participate in this study.TF: conceptualization, methodology, software, formal analysis, visualization, investigation, and writing—original draft. AA: conceptualization, methodology, writing—review and editing, and project administration. Both authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.