Inter-leg coordination is of great importance to guarantee the safety of the prostheses wearers, especially for the subjects at high amputation levels. The mainstream of current controllers for lower-limb prostheses is based on the next motion state estimation by the past motion signals at the prosthetic side, which lacks immediate responses and increases falling risks. A bio-inspired gait pattern generation architecture was proposed to provide a possible solution to the bilateral coordination issue. The artificial movement pattern generator (MPG) based on the temporal convolution network, fusing with the motion intention decoded from the surface electromyography (sEMG) measured at the impaired leg and the motion status from the kinematic modality of the prosthetic leg, can predict four sub gait phases. Experiment results suggested that the gait phase decoder exhibited a relatively high intra-subject consistency in the gait phase inference, adapted to various walking speeds with mean decoding accuracy ranging from 89.27 to 91.16% across subjects, and achieved an accuracy of 90.30% in estimating the gait phase of the prosthetic leg in the hip disarticulation amputee at the self-selected pace. With the proof of concept and the offline experiment results, the proposed architecture improves the walking coordination with prostheses for the amputees at hip level amputation. High-level amputation like hip disarticulation requires the utilization of an intelligent prosthesis to restore the amputee's natural gait. One way to achieve this goal is to employ a phase-based controller  is proposed by scientists to explain the emerging coordination mechanism from the bottom up. One definition describes the gait MPG as the neural circuits localized in the spinal cord with the capability to produce a periodic rhythmic pattern during walking  is convenient to access  Provide a novel proof-in-conception prosthesis myocontrol approach with a focus on hip disarticulation amputees; 2) Investigate the performance of gait phase decoder fusing bilateral neuromechanical signals.The function of the proposed gait phase decoder, as well as a scene of the experiment, can be perceived in Surface electromyography is the electrical potential captured in the skin during the muscle fibers contract and relax. It can be affected by multiple factors such as the relative displacement between the electrode and the skin. To correctly interpret the motion intention from the measurement, possible noises must be removed. The sEMG signals from each walking trial were first band-passed with a 20–450 Hz Butterworth band-pass filter to eliminate the majority of the inherent device noise and motion artifacts. The data was then filtered through a notch filter to remove the electrical interference. In this proposed method, both filtered sEMG and knee motion modalities were segmented by a 64 ms sliding window with a half overlap increment. The length of the sliding window was set to minimize the user's awareness of the time delay of the decoder dynamical response and the classification accuracy loss for further online validation. The EMG signal starts about 20–80 ms before the muscle contraction , STD (standard deviation), RMS (root mean square), MAV , MAX (maximum), WL (wavelength), WA (Willison amplitude), SSC (slope sign change), and iEMG (integrated EMG) were extracted from the multiple-channel sEMG signals of the dominant or unimpaired leg when sliding the window (Details of these features can be found in the Appendix). Only the mean values across the sliding windows were calculated from the knee angle and angular velocity data considering time-invariability stability during periodic walking. Then nine features per muscle  and one feature from each kinematic signal  were fused in parallel to an In this offline mode, foot pressure captured by Zebris-FDM-T System  served as the ground truth. Following the nomenclature of gait phases suggested in the article  are the typical option in the time sequence decoding task, but a new neural network framework called Temporal Convolution Network (TCN) , the layer was constructed from 20 filters with the kernel size k of 3. Other transformations were added in succession after the basic dilated causal convolution, including weight normalization (Weight Norm), rectified linear unit (ReLU), and a spatial dropout. The inputs of the residual block were passed through the two modified dilated causal convolutions, and the outputs after these transformations were added to the inputs of the block. An illustration of one residual block can be found in In our implementation, the input parameters include the ipsilateral knee angle and angular velocity, the contralateral sEMG from four muscles. The input size is 38 which is equal to the fusion feature set dimension. The output of TCN is the current gait phase estimation out of the four categories. We specified our network architecture with four residual blocks. Within each block, the TCN had two layers of dilated causal convolution. Each dilated causal convolutions layer had two hidden sub layers, and the dilation factor The TCN was implemented using MATLAB R2020a  on Lenovo ThinkStation with an Intel Xeon CPU processor E3-1225 V2 @ 3.2 GHz and 12 GB RAM, and we adopted the training strategy similar to the study by Su et al.  of across-speed classification accuracy of the decoder fusing either ipsilateral or contralateral sEMG. A smaller IQR indicated a better consistency.For long-period prosthesis control, bilateral gait coordination relies on both decoding accuracy and decoding consistency. The decoding accuracy is defined as the average decoding correctness compared to the ground truth, and the decoding consistency is referred to as the variation of the decoding accuracy. The mean intra-subject classification accuracy of the decoder was calculated by comparing the predictions on the held-out test set with the true gait phase labels. Then the decoding consistency was intuitively compared Knee motion provides abundant information about the gait phase, and the agonist and antagonist muscle groups are needed to power the joint to accomplish the walking task. Experimental evidence  were used to improve the contact of the electrode with the skin and obtain a reliable measurement. Following the recommendation guidance  group enrolled in the experiments, and all the participants were self-reported as right leg dominant according to their handwriting habits. Besides, one unilateral HD (hip disarticulation) amputee wearing our customized lower-limb prosthesis  index which is calculated in the following formula:Detrended cross-correlation analysis (DCCA) was applied to analyze bilateral sEMG channels because it is suitable for analyzing non-stationary time series with periodic trends  and FDFA(n) can be defined as the following:where the DFA denotes the Detrended Fluctuation Analysis which calculates the power-law auto-correlation of the ipsilateral sEMG signal, and fn, i)DCCADFA is larger than 0.185 for the 95% confidence level.In our study, R was employed to implement the DCCA. Referring to the empirical value suggested in Podobnik et al. , the crop < 0.05 unless otherwise stated. P-values between 0.05 and 0.10 were considered to indicate a statistical trend.In the session of decoding accuracy analysis, a normality test was performed in the dataset with the outliers deleted by the quartile detection (threshold at 1.5). The level of significance for all statistical analyses was accepted at t-test indicates that the gait phase decoding result exhibits no difference when we substituted the ipsilateral sEMG sensors for the contralateral as the fusion information source. Both the floating range of the decoding results and the mean value of gait phase recognition are similar. Additionally, the p-value (P = 0.98) supports the decoder's ability to handle the bilateral sensory feedback.The overall assessments of the decoder's ability to extract information from the ipsilateral fusion sensors using multiple-subject testing results were shown in However, the pattern of muscular activities varies from person to person, the overall assessment is not complete to assess the decoder's performance, hence, we further checked the intra-subject decoding accuracy and consistency. To estimate the detailed effects of speed variability on the decoder's performance fusing ipsilateral sensors, the radar chart in FDCCA(n) index, which has a physical meaning of muscle contribution in our case, varies across channels across walking speeds. Combining the DCCA index table, all channels are significantly cross-correlated, and bilateral VM-VM and VL-VL exhibit the highest relevance, then followed by RF-RF and ST-ST pairs.The results of DCCA for bilateral sEMG are presented in P = 0.0036) between groups, both groups reported a high accuracy (90.30% for the amputee and 93.00% for the subject HC-6). In both cases, the errors mainly occur during the continuous transition of the gait phase. Besides, there is a greater probability for the decoder to make the wrong estimation about the gait phase of the prosthetic side during the stance phase compared to the healthy control group.As walking speed is a prominent factor in gait pattern generation, we chose the record of Subject HC-6 for further comparison since his self-selected speed is the same as the HD's . Figure One hypothesis about the architecture of MPG involves a Central Pattern Generator (CPG) and a neural reflex loop .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.


The Internet of Health Things (IoHT) has emerged as an attractive networking paradigm in wireless communications, integrated devices and embedded system technologies. In the IoHT, real-time health data are collected through smart healthcare sensors and, in recent years, the IoHT has started to have an important role in the Internet of Things technology. Although the IoHT provides comfort in health monitoring, it also imposes security challenges in maintaining patient data confidentiality and privacy. To overcome such security issues, in this paper, a novel blockchain-based privacy-preserving authentication scheme is proposed as an approach for achieving efficient authentication of the patient without the involvement of a trusted entity. Moreover, a secure handover authentication mechanism that ensures avoiding the patient re-authentication in multi-doctor communication scenarios and revoking the possible malicious misbehavior of medical professionals in the IoHT communication with the patient is developed. The performance of the proposed authentication and handover scheme is analyzed concerning the existing state-of-the-art authentication schemes. The results of the performance analyses reveal that the proposed authentication scheme is resistant to different types of security attacks. Moreover, the results of analyses show that the proposed authentication scheme outperforms similar state-of-the-art authentication schemes in terms of having lower computational, communication and storage costs. Therefore, the novel authentication and handover scheme has proven practical applicability and represents a valuable contribution to improving the security of communication in IoHT networks.  Due to the growing and aging of the general population, healthcare has been confronted with a number of new issues. The Internet of Health Things (IoHT) is a key component in the Internet of Things (IoT) healthcare applications, where wireless transmission of sensing signals over air serves as a channel for data transmission between entities . The IoHT is an innovative solution that can serve the demands of both local and remote medical applications. In today’s context, the IoHT uses sophisticated sensors and wearable devices in combination with cloud computing, IoT and wireless networking to gather real-time biological data from the patient’s body. The IoHT, as part of a smart healthcare system ,2, can pIn monitoring the health conditions of elderly people or general people with some health problems remotely, the IoHT starts to play an important role. For example, in the IoHT networks, sensor nodes collect health information such as the patient’s pulse, heart rate, blood sugar and other symptoms of possible sickness. For the purpose of monitoring, diagnosis or treatment, such information is transferred to remote servers that are accessible to healthcare specialists via communication technology. Since the first introduction of the IoHT as a concept, there has been a major focus on increasing the security of data transfer, while reducing the IoHT communication and computation costs. Sensing devices in the IoHT transmit information about the human body at any time and from any location. Therefore, the reliable sending of sensing information of the individual is of vital importance. For monitoring health-related data from a remote distance, the information collected from the sensors should be transferred securely by means of a wireless medium. However, in the real-life implementation of the IoHT technology, the confidential data of the patients can be hacked by intruders and this imposes a serious security problem. To overcome such security challenges, in this paper a novel authentication scheme is proposed as an approach for achieving efficient authentication of the patient without the involvement of a trusted entity.in-body communication sensors where the sensors or nodes for establishing IoHT communication are positioned inside the human body. The medical implant communication system is used for this purpose. The second application of sensors is on-body communication sensors, where interaction between wearable devices and the body occurs mostly through sensory components that are implanted in the human body [The IoHT network is generally made up of four parts: the transmitter, the receiver, the battery and the central processing server. Physiological sensors, environmental sensors and biokinetic sensors are types of sensors that are used to monitor real-time data related to human health and well-being. The main goal of the IoHT is to simplify and increase the speed, precision and reliability of sensor/actuator communication within, on or near a human body. The IoHT has the capability to communicate with the Internet as well as other wireless technologies such as ZigBee, wireless sensor networks (WSNs), Bluetooth, video surveillance and mobile cellular networks. There are two different types of sensors used in practical IoHT applications. The first is man body ,9,10.trustability, low transmission latency, security, confidentiality, integrity and availability. Trustability means that medical data of high precision is included in the data transmission chain by IoHT wearable devices or sensors, and the source of this data must be trustable. Transmission latency takes into account that some medical applications that deal with emergency data are not designed to sustain long response times. As a result, assured minimal transmission latency or real-time transmission is required. Security is related to the fact that the system should be capable of handling personal and sensitive data and data security and secrecy must be ensured. Confidentiality assumes that only authorized persons can have access to the data, and they must be validated by some authentication process before accessing it. Furthermore, data secrecy must be guaranteed in any phase of data processing, i.e., during the data transmission and storage phase. Integrity ensures that no unauthorized party should be allowed to alter sensing data or central processing device configurations. Furthermore, the data’s source should be reliable. Availability means that the information and sensing devices must always be available to authorized organizations and an unauthorized person(s) must not be able to interrupt communication or create a negative impact on the equipment. The IoHT must include several required key features such as The IoHT technology is used in both medical and non-medical applications that support health monitoring. Medical applications are characterized by health monitoring devices that are dedicated to monitoring human medical parameters , etc.). Examples of non-medical applications include navigation, time, distance, direction, surrounding temperature, etc., and that information may all be monitored using non-medical sensor devices such as sports sensors. Monitored information is through a concept known as telehealth care used to deliver healthcare over long distances by means of information and communication technology (ICT). Therefore, the IoHT as a technology is legal, affordable and easy to use. There are several advantages of wireless IoT networks over wired networks, including the elimination of lengthy wired communication lines and the threat of the entire system collapsing if parts of the network or specific node fails. Despite the various advantages of wireless IoT networks, the IoHT has some disadvantages such as limited storage capacity, susceptibility to the impact of noise or interference and continuous power supply issues. However, cloud computing arose as a solution to the IoHT technology’s limited storage capacity. Several networking concepts are commonly employed in the healthcare industry to deliver real-time patient monitoring and services. Although the medical expert may access a patient’s cloud-based data from any location on the planet, the patient’s sensitive data are transmitted over insecure cloud-based networks. Since only legitimate users have access to their data and services, there is a need for a strong user authentication system. Due to the fact that the physiological parameters of patients are extremely sensitive in terms of privacy, secure communication in the IoHT networks is of great importance. Additionally, security risks arise as a result of the open nature of cloud computing and wireless connectivity. Secure user authentication is thus required because the patient’s data is sent over insecure Internet networks ,12. TherMoreover, several authentication techniques for the IoHT have been proposed in recent years to improve the security of the IoHT data transmission through securely encrypting patients’ confidential medical data and transmitting it to medical advisors. To contribute to these attempts, this work proposes a lightweight blockchain-based authentication scheme that offers protection against a variety of security risks. More specifically, the main goal of this work is to ensure the efficient transfer of the confidential information of the patient to medical professionals (doctors) and to send the confidential medical prescription from the doctor to the patient through the development of a novel authentication scheme. Furthermore, secure handover authentication is suggested to avoid the re-authentication of patients when they move from one location to another.Development of an authentication scheme that guarantees efficient anonymous authentication for patients and medical staff, where confidential biological information is accessed only by authenticated doctors or patients.Development of an authentication scheme that guarantees integrity and data confidentiality of both the confidential biological information and medical prescription of patients and doctors from attackers.Development of an authentication scheme that guarantees an efficient revoking mechanism for malicious misbehaving of medical staff in the IoHT wireless body area network.Development of an efficient authentication handover that enables avoiding re-authentication of the patients when new doctors start their health monitoring process.Therefore, the main contributions of this work are:The rest of the manuscript is structured as follows. Many authors have concerted on providing an efficient, secure, anonymous protocol to provide security among IoHT users. Identification (ID)-based public key was suggested by Wang et al. in  where thSong in  has deveA new and enhanced smartcard-based authentication system was developed by Islam . His proIn a multi-server context, Ali and Pal in  have recTo overcome different security threats Xu et al. in  suggesteSon et al. in  discuss Peng et al. in  suggesteAlthough presented related works show improvements in terms of the development of authentication schemes, the main research gap is the lack of authentication schemes that offer a combination of secure re-authentication of the patients (adopting a handover mechanism) and revocation of the misbehaving doctors. This paper tends to fill this gap with the introduction of a novel authentication scheme dedicated to improving authentication efficiency and reducing computing costs. In this work, this research gap tends to be fulfilled by proposing a solution that is based on the blockchain concept. Confidential information is stored in the blockchain and only authenticated IoHT users can access this data. If any intruder tries to hack the block, this will have an impact on the subsequent blocks affecting the entire blockchain network. When the patient moves from one location to another location without the involvement of a trusted authority, the new doctor takes the data of the patient from the blockchain. As a result, there is no re-authentication of the patient, which results in a reduction in the authentication time.Moreover, a revocation mechanism is adopted in a way that when the misbehaving doctors (attackers) are identified by the trusted authority, their fake identities are loaded into the blockchain list. Hence, the misbehaving doctor will not be allowed to proceed further in the IoHT network. The results of the performance comparison in terms of computational, communication and storage overhead of the proposed authentication scheme are compared with other known state-of-the-art authentication schemes. The methods on which the development of the proposed authentication scheme is based will be presented in this section and they include elliptic curve cryptography, bilinear pairing and blockchain in the IoHT network. Moreover, in this section, the analyzed system model will be presented.n denotes the private key value. The scalar point addition is denoted as The proposed authentication scheme exploits the concept of ECC. It is the concept of realization of public-key cryptography using the algebraic structure of elliptic curves over finite fields. Let us take an elliptic curve over a finite field demarcated by Another relevant concept for executing the proposed authentication scheme is commonly used to construct and analyzed cryptographic systems. It is based on pairing between elements of two cryptographic groups ((1)Bilinearity: for any (2)Non-degeneracy: for non-identify points (3)Computability: for any two points The developed authentication scheme utilizes the concept of blockchain technology. In blockchain technology, information is stored in the form of blocks that are linked together in a secure way. Any modification of data in the block will affect the subsequent blocks. Thus, the data loaded in the blocks are immutable ,46,47,48In the proposed authentication scheme, the introduction of blockchain technology alleviates these problems. As an outcome, blockchain-integrated IoHT empowers authenticity and integrity, without the involvement of a trusted entity, thus decreasing the computational overhead. The system model used for analyses is composed of three entities. The trusted entity (TE) is a completely trusted authority, and it cannot be compromised by anyone. It is responsible for generating the system parameters and providing the authentication parameters to the authenticated users in the IoHT network . InitialThe mobile control unit (MCU) is provided to both authenticated end users in the IoHT network . The MCUThe end users in the IoHT network are medical staff /experts and patients . To becoEnsuring message integrity and authentication: the confidential biological sensitive data of the patient or the medical prescription of the doctor should be integrity preserved. The possibility of forging or modifying the information by the intruder should be eliminated.Ensuring nonrepudiation: only authenticated end users are allowed to participate in the data transfer over the IoHT network. There must be no possibility for the registered users to deny the message transmission once it is sent.Ensuring anonymity and privacy: the real identity of the end users should be preserved during the transfer of confidential data. Moreover, the private confidential information of the end users should be preserved.Ensuring unlinkability: there should not be any correlation between the subsequent information sent between the end users.Ensuring revocation and traceability: if any mishap occurs in the network and the end user is trying to send fake information, the real identity of the end user should be traced immediately and revoked from the IoHT network.The analyzed IoHT system model presented in For an efficient transfer of confidential biological information between the patients and doctors in the current scenario, a blockchain-based integrity preservation scheme is proposed in this work. This scheme also achieves anonymous authentication between the end users. The notations and their description used in the further analyses are shown in Nomenclature.The important steps that are carried out in the proposed scheme include initialization of the system, registration of both patients and doctors with a trustworthy network, Anonymous authentication, handover authentication, preservation of integrity and revocation. The entire flow diagram of the proposed authentication scheme is shown in Algorithm 1 and Algorithm 2, respectively. Algorithm 1 shows the phases related to the registration, the key generation and authentication of the patient, while Algorithm 2 shows the authentication of the doctor and handover authentication phases.Algorithm 1: Flow diagram of registration, key generation and authentication of patient. part 1: the anonymous authentication of patientInitialization:  1. Elliptic curve of finite field: 2. Points on the curve: 3. Random numbers 4. Public parameter of TE: 5. Authentication parameter of TE: 6. Hash function generation: 7. Public parameters:Patient’s registration:  8. TE choosescalculatecalculatePatient 9. Blockchain where 10. Doctor’s registration: chooses 11. calculatecalculate Doctor 12. Patient’s key generation:  13. secret key is 14. public validation key isDoctor’s key generation: 15. 16. public validation key is Anonymous authentication of Patient: PatientDoctor 17.  18.  19.  20.  21.Verifies 22.. 23Algorithm 2: Anonymous authentication of doctor and handover authentication. part 2: the anonymous authentication of the doctorDoctorPatient1.Reception of parameters: 2.3.4.5.6.7.VerifiesTransfer of biotic information from the patient to the doctorPatientDoctor8.9.10.11.12.13.14.VerifiesTransfer of medical prescription from the doctor to patientDoctorPatient15.16.17.18.19.20.21.VerifiesHandover authenticationCurrent doctorNext doctor(s)22.23.24.where25.26.27.VerifiesIn the phase of system initialization, an elliptic curve of finite field The next phase of the developed authentication algorithm is the patient registration phase (Algorithm 1). Initially, the patients should be registered with the To communicate with everyone, a fake identity is used. Only the fake identity is exposed to other entities during data transfer. Moreover, in the Similar to the patient’s registration, in the next phase of the proposed algorithm, it is mandatory for the doctors to register with the After the doctor’s registration phase, the next algorithm phase that is executed is the patient’s key generation phase. In this phase, the secret key and public key are generated by the authenticated patient device based on the received values of Proof of validation. Similar to the previous phase related to the patient’s key generation, in this phase, the secret key and public key are generated by the authenticated doctor’s device based on the received values from the Proof of validation. The next phase of the proposed algorithm is dedicated to the patient’s anonymous authentication. The process of validating the credentials of patients and doctors in order to ensure security is known as authentication. The anonymous authentication process authenticates doctors and patients without disclosing their true identities. As a result, anonymous authentication protects end users’ privacy. In order to communicate with patients and other doctors, the MCU of the doctors and patients should perform anonymous authentication. The steps described further are carried out in the process of the patient’s authentication phase (Algorithm 1).When the patient reaches the doctor’s spot, the MCU of the patient sends After computing the validation ID of the patient, the doctor’s MCU checks Proof of validation. Finally, the MCU of the doctor picks the fake identity of the patient The doctor provides confidential information such as medical prescriptions, diagnosis data, etc., to the patient in a secure way. Hence, it is necessary for a patient to authenticate the doctor before receiving confidential information from the doctor. Trust between the patient and doctor is mandatory to receive confidential information. The process of the doctor’s anonymous authentication is presented in Algorithm 2. In this procedure, the doctor’s MCU receives the following parameters Proof of validation. In the next phase of the proposed authentication algorithm, the transfer of biotic information from the patient to the doctor starts. To send the confidential biotic information  allowed to participate in the IoHT network communication. Therefore, the end users cannot repudiate after transferring the related data. Either during the transfer of biotic information of the patient to the doctor by the patient’s device or during the transfer of medical prescription prescribed by the doctor to the patient, secret keys of the corresponding entities are used to hide the information. Hence, either the doctor or the patient cannot repudiate data after sending it. The proposed work uses fake identities and signatures provided by the TE for transferring confidential information between the end users. This type of security threat is a sort of man-in-the-middle attack. To communicate with entities in the IoHT, a fake identity is used by the end user. This fake identity is exposed to other entities during data transfer. Moreover, in the A lack of connectivity between the two simultaneous messages that are transferred between the end users is referred to as an unlinkability attack. The suggested scheme achieves unlinkability by the usage of short-time secret key generation during the transfer of information. During the transfer of confidential biological information  may send spurious information regarding their biological data at the same time to the authenticated doctor in the network. As a result, the authenticated doctor becomes busy in receiving this fake information. Moreover, the doctor will not be able to serve the authenticated patient, since it becomes extremely busy. In the case of the proposed authentication scheme, to send fake information by the patient’s device to the doctor, the attacker (fake patient(s)) should crack the values of In the reply attack, the information is captured during the transmission and transmitted after a certain interval of time by an external attacker. To avoid this attack, in the proposed authentication scheme a timestamp is attached during the transfer of information. More specifically, during the handover authentication phase, the current doctor’s MCU sends Here, the The performance of the proposed authentication algorithm for the described IoHT network is analyzed in terms of computational, communication and storage costs. The brief discussion regarding each analysis is explained as follows. Computational overhead refers to the time required to complete the cryptographic operations dedicated to the authentication of the IoHT users . In this work, random computations are performed for 100 simulations and the mean time of all computations is calculated as computational overhead. The performance of the proposed authentication scheme is compared with similar state-of-the-art schemes such as those published by Kumar et al. , Liu et Additionally, Moreover, the results presented in The number of bits exchanged during the transformation of information in the frame of the authentication process between the IoHT users is referred to as communication overhead. Therefore, the entire communication overhead of the proposed authentication scheme is computed and transferred in 2240 bits . When coThe communication overhead of the proposed authentication scheme is 33,33% lower than the communication overhead of the authentication scheme having the second lowest communication overhead. This confirms the superiority of the proposed authentication scheme in terms of communication overhead when compared with other prominent authentication schemes. Storage overhead plays a key role in the performance evaluation of the authentication process. Storage costs account for the number of bits that must be stored in the memory of user devices during the authentication process. In the proposed authentication scheme, the patients are required to store parameters These results present a significant improvement when compared with the storage costs of existing schemes . TherefoIn this manuscript, an efficient certificateless blockchain-based anonymous privacy-preserving authentication scheme is proposed. This work is mainly focused on the reliable and efficient transfer of authentication information between the doctor and patient user device in the IoHT environment. A detailed explanation of the algorithm for performing authentication in the IoHT network is presented. The authentication algorithm is based on the generation of private keys which are used in the authentication process during cipher text validation. In addition, these keys are generated based on the lightweight elliptic curve method. Blockchain technology is used as an approach for achieving efficient authentication of the patient without the involvement of a trusted entity. An efficient authentication handover mechanism is also developed in the frame of the proposed authentication scheme and this mechanism enables the transfer of the patient’s data between the doctors in a secure way. Additionally, an efficient revoking mechanism is suggested to remove the potential misbehaving doctors from the IoHT network. The obtained results for the performance analyses of the proposed authentication scheme prove that the proposed authentication algorithm can withstand different possible security threats. Moreover, a performance comparison with other related state-of-the-art authentication schemes shows that the proposed authentication scheme enables significant improvements in terms of computation, communication and storage overhead.The main limitation of the proposed authentication scheme is the dynamic increase in the patient’s and doctor’s data stored in the trusted authority. Since the bulk of data is stored in a trusted authority, data accessibility can become challenging when the amount of data significantly increases. However, if the fog computing concept is incorporated, patients’ data can be temporarily stored closer to the authenticated doctor for frequent and faster data access. Therefore, performance analyses of this concept based on fog computing will be the main focus of future research.Moreover, the algorithm proposed in this paper can be used in the practical implementations of an efficient mobile control unit for both, patients and doctors. As a result, the computational operations are performed in a faster way, which reduces the transmission delay of the confidential data. Thus, the speed of the authentication process at the devices in the IoHT network can be increased. Moreover, only a minimum number of bits need to be stored in the memory of end devices, which reduces the memory demand and leads to the reduced power consumption of mobile devices.In addition, the location privacy of wireless body area network users will be one of the possible future extensions of this research work. Location privacy and security should be preserved while accessing the wireless body area network from various locations during the user’s movement. Further, an automatic billing scheme for the medical prescriptions provided by the doctor for accessing the patient data can be incorporated into IoHT networks and this is also a research topic of interest. Finally, future work can be extended in different areas of applications such as education, supply chain management, vehicle ad-hoc networks and even government organizations.


Electrochemical micromachining (EMM) is a plausible method for manufacturing high accuracy and precision microscale components in a broad range of materials. EMM is commonly utilized to manufacture turbine blades for automobiles and aircrafts. In this present study, the EMM process was performed with a heat-treated copper tool electrode on aluminum 8011 alloy. The process parameters such as voltage, concentration of electrolyte, frequency, and duty factor were varied to analyze the effect of a heat-treated electrode on material removal rate (MRR), overcut, conicity, and circularity. It was observed that high MRR was obtained with lower overcut with an annealed electrode. The better conicity and circularity were obtained with a quenched electrode compared to other heat-treated and untreated tool electrodes. The artificial bee’s colony (ABC) algorithm was used to identify the optimum parameters and, finally, the confirmation test was carried out to evaluate the error difference on the machining process. The optimum combination of input process parameters found using TOPSIS and ABC algorithm for the EMM process are voltage (14 V), electrolyte concentration (30 g/L), frequency (60 Hz), and duty cycle (33%) for the annealed tool electrode and voltage (14 V), electrolyte concentration (20 g/L), frequency (70 Hz), and duty cycle (33%) for the quenched tool electrode. It was confirmed that 95% of accurate response values were proven under the optimum parameter combination. Due to increased demand for miniaturized and portable equipment, the need for precision parts has severely proliferated; and to fulfill these needs, various advanced machining techniques have been developed. One such technique is electrochemical machining (EMM), which leads to a great development and demand due to its versatile applications and benefits. It offers outstanding machinability, negligible tool wear, featureless surface finish, and economic efficiency. EMM has potential to machine any complicated shape on a workpiece which is capable of conducting electricity ,2. EMM iTo calculate the optimal factors for obtaining better multiple surface quality measures using the ABC technique.To assess the influence of input factors on surface measures.To inspect the surface quality at optimal levels in the process.The detailed survey illustrated that only few multiresponse decision-making (MCDM) were available with the machining of aluminum alloy using the EMM process. It was also found that little attention was given to optimizing the surface quality performance measures related to the EMM process on machining such an alloy. Hence, the present investigation was performed. In the present attempt, the artificial bee colony (ABC) methodology was performed for enhancing the surface performance measures on drilling aluminum 8011 alloy in the EMM process. The important aims of the investigation on machinability using different process factors were as follows:3 was chosen as an electrolyte due to its lower throwing power, high metal removal rate (MRR), and passivity of the alloy [The EMM setup comprises the electrical power unit, the machining chamber, the computer control system, and the electrolyte pumping system. The machining chamber contains the workpiece (anode) and tool (cathode). The workpiece is fixed using a holder in a machining chamber which is airtight and resistant to corrosion. It is equipped with a window to monitor the machining. The tool is made to move near the job with the help of a control panel equipped with press buttons and table lifting arrangement which helps in the interelectrode gap maintenance. A microcontroller governs the progress and maneuvers the tool vertically with the help of a servo motor. A control unit was used to vary the process parameters such as voltage, current, and feed rate. The selection of process factors is described in he alloy ,33,34.MRR is expressed as metal removed per unit time and can be denoted by g/min.Overcut is the space between the tool and the machined hole measured in micrometers.Conicity is the variation between a real and ideal cylindrical surface. It is a blanket tolerance that results in a feature lying between concentric cylinders or coaxial cylinders. It is expressed in percentage as follows:Circularity is the cross-sectional evaluation of the feature to determine if the circular surface lies between the tolerance zone indicated by two concentric circles, which is measured in micrometers.V), electrolyte concentration (EC), frequency (F), and duty cycle (DC) on different response values such as the material removal rate (MRR), overcut (OC), conicity (CC), and circularity (CL) were studied for an annealed and a quenched tool electrode using Taguchi’s L9 orthogonal array. Apart from that, multiple linear regression equations were established for the above responses and the optimum parameters and their corresponding response values have been obtained by implementing the ABC algorithm. Since four different responses/objective values were involved in this work, it was treated as a multiobjective optimization problem. Moreover, the objectives were of both a maximization and a minimization nature and of different magnitudes. The TOPSIS method was proposed in this work to convert multiobjectives into a single objective value. This converted single objective value was considered as the fitness function for the ABC algorithm. The lower and upper limits mentioned below for each parameter were considered as constraints in this algorithm.In this present work, the influence of voltage (Equation (6) represents a linear regression equation (LRE) used in this work which was constructed for the data provided in the above The implementation flow diagram for obtaining the optimum response values is presented in From In the case of the quenched tool electrode, electrolyte concentration showed the most deviation, thus suggesting that it was the most influential parameter because a higher electrolyte concentration leads to the generation of a larger number of ions during electrochemical machining. This leads to a larger ionization which causes high erosion and conductivity for creating larger material removal ,42. It w3− in the solution was increased due to the higher concentration of electrolyte which increases the localization of ions resulting in less overcut. Duty cycle shows the most deviation for the annealed and quenched tool electrodes. It can be seen from the main effect plot that the overcut was high when the duty cycle was high because, as the pulse on time increases, the current flow between the electrode and workpiece increases. A higher current flow leads to a higher dissolution of ions. This limits the magnitude of the current, thereby decreasing the dissolution rate. This leads to achieving a higher overcut owing to a higher side current and lower localization effect [It is apparent from n effect ,44. It iThe electrolyte concentration was observed to be the most influential parameter for the bare and quenched tool electrodes as shown in It is observed from n is the no. of experiment and in is the mean S/N ratioAnalysis of variance is a statistically based decision-making tool used to detect any deviations in the mean performance of a group of items that have been tested. ANOVA compares the mean square against the estimate of the experimental errors at set confidence levels, thus aiding in the identification of significance of the main factors and their interactions in a study ,48.(7)SFrom From From From p-Value of 0.049 that the fitness values obtained by 25 runs were in the normal distribution range; hence, the optimum parameters obtained by ABC algorithms are acceptable. The normality test of 25 runs is represented in The program executed 25 runs and the statistical analysis of the results is shown in V, EC, F, and DC for the maximum value of the MRR and the minimum values of OC, CC, and CL are shown in In this present study, aluminum 8011 was machined by the EMM process using various heat-treated copper tool electrodes and the process parameters were optimized by TOPSIS and ABC algorithm. The input characteristics such as voltage, concentration of electrolyte, frequency, and duty factor were suitably varied to analyse their effect on the response characteristics such as MRR, overcut, circularity, and conicity. From the experiment conducted and the results obtained, the following conclusions were drawn.(i)The annealed tool electrode created a higher MRR than the untreated, normalized, and quenched tool electrodes because the annealed tool electrode has a fine grain structure due to the slower rate of cooling and easily dissolves in the electrolyte.(ii)The annealed tool electrode generated better overcut than the untreated, normalized, and quenched tool electrodes because the annealed tool has a smaller grain structure due to furnace cooling which improves the surface finish of the tool electrode.(iii)Electrolyte concentration was the most influential parameter for the bare tool as it determines the rate of ionization due to the presence of free ions in the electrolyte.(iv)The optimum combination of input process parameters found using TOPSIS and the ABC algorithm for the EMM process are voltage (14 V), electrolyte concentration (30 g/L), frequency (60 Hz), and duty cycle (33%) for the annealed tool electrode and voltage (14 V), electrolyte concentration (20 g/L), frequency (70 Hz), and duty cycle (33%) for the quenched tool electrode.


Social media, an essential source of public access to information regarding the COVID-19 vaccines, has a significant effect on the transmission of information regarding the COVID-19 vaccines and helps the public gain correct insights into the effectiveness and safety of the COVID-19 vaccines. The forwarding behavior of social media users on posts concerned with COVID-19 vaccine topics can rapidly disseminate vaccine information in a short period, which has a significant effect on transmission and helps the public access relevant information. However, the factors of social media users' forwarding posts are still uncertain thus far. In this paper, we investigated the factors of the forwarding COVID-19 vaccines Weibo posts on Chinese social media and verified the correlation between social network characteristics, Weibo textual sentiment characteristics, and post forwarding.This paper used data mining, machine learning, sentiment analysis, social network analysis, and regression analysis. Using “新冠疫苗 (COVID-19 vaccine)” as the keyword, we used data mining to crawl 121,834 Weibo posts on Sina Weibo from 1 January 2021 to 31 May 2021. Weibo posts not closely correlated with the topic of the COVID-19 vaccines were filtered out using machine learning. In the end, 3,158 posts were used for data analysis. The proportions of positive sentiment and negative sentiment in the textual of Weibo posts were calculated through sentiment analysis. On that basis, the sentiment characteristics of Weibo posts were determined. The social network characteristics of information transmission on the COVID-19 vaccine topic were determined through social network analysis. The correlation between social network characteristics, sentiment characteristics of the text, and the forwarding volume of posts was verified through regression analysis.The results suggest that there was a significant positive correlation between the degree of posting users in the social network structure and the amount of forwarding. The relationship between the closeness centrality and the forwarding volume was significantly positive. The betweenness centrality was significantly positively correlated with the forwarding volume. There was no significant relationship between the number of posts containing more positive sentiments and the forwarding volume of posts. There was a significant positive correlation between the number of Weibo posts containing more negative sentiments and the forwarding volume.According to the characteristics of users, COVID-19 vaccine posts from opinion leaders, “gatekeepers,” and users with high-closeness centrality are more likely to be reposted. Users with these characteristics should be valued for their important role in disseminating information about COVID-19 vaccines. In addition, the sentiment contained in the Weibo post is an important factor influencing the public to forward vaccine posts. Special attention should be paid to the negative sentimental tendency contained in this post on Weibo to mitigate the negative impact of the information epidemic and improve the transmission effect of COVID-19 vaccine information. The global pandemic of COVID-19 has been one of the most hazardous public health emergencies over the past few years, arising from its negative effect on all human health. As of 5 January 2022, COVID-19 has caused nearly 290 million infections and over 5 million deaths worldwide . VariousChina has begun to develop the COVID-19 vaccines at a very early stage after the epidemic outbreak. On 31 December 2020, as announced by the Information Office of the State Council of the People's Republic of China, the national vaccines of COVID-19 were approved by the National Medical Products Administration for conditional marketing . To contThere is a wealth of health and medical information on social media , and it Forwarding behavior indicates that the forwarding user (user b) is interested in the specific message posted by the original promulgator (user a) . As indiThis study has three main contributions. The first contribution is that this paper used big data mining and analysis to creatively study the reasons why the public reposts COVID-19 vaccine-related posts, thus contributing to knowledge for research on the effect of information transmission. Second, this paper integrated two variables of post content and user characteristics, providing a valuable perspective for us to comprehensively understand people's information transmission behavior in the social media era. Finally, posts on COVID-19 vaccine-related topics objectively reflect the public's concern about COVID-19 vaccines in China, and COVID-19 vaccine information on social media is crucial for increasing scientific awareness of COVID-19 vaccines and effectively increasing vaccination rates. Thus, this paper also offers advice on how to use social media platforms to increase the spread of COVID-19 vaccine posts.Numerous studies have been conducted to investigate the forwarding behavior of social media users. A primary focus is on finding the rationale for forwarding information on a specific topic. Research on the forwarding behavior of social media users is conducive to revealing the underlying mechanisms of health information transmission. As reported by existing studies, a combination of factors impacts users' forwarding behavior. Specifically, the influencing factors of Weibo posts forwarding can be roughly divided into two categories: user characteristics and information characteristics , 27. ThiAn overriding factor accounting for the forwarding behavior of social media users is the structure of social networks. In social media, users are not isolated from each other, whereas they are connected by disseminating information, which generates a directed social network diagram of information transmission. In the social network relationship, each node in the network represents a user, and users can establish connections by forwarding posts, thus forming a social network structure with a forwarding relationship. The “position” and power can be measured with three metrics, that is, degree, betweenness centrality, and closeness centrality in the network structure .In the social network structure, the degree in the network structure can be analyzed to investigate the scope of users' social activities. The higher the degree of a user is, the more the user is in the core position of the entire social network structure of information transmission, and the more users directly establish contact with it . Thus, tBetweenness centrality is a way of detecting the amount of influence a node has over the flow of information in a graph. It is often used to find nodes that serve as a bridge from one part of a graph to another . In sociCloseness centrality emphasizes the average distance between one node and the others in the social network structure . The cloThe cognitive theory of emotion suggests that the body receives information from the external world into the perceptual system. The body will be organized and compiled by the perceptual and mental systems. Besides, the information will lead to the body's positive or negative sentiment response, thus causing some tendencies to behavior . The theIn brief, despite the research conducted in the literature on the correlation between social network structure, textual sentiment, and user-forwarding behavior, this area still has some researchable space. By reviewing existing studies, we indicated that though similar studies have discussed the effects arising from betweenness centrality and closeness centrality on post forwarding , the resRQ1: What is the relationship between the different social networkcharacteristics of posting users and the forwarding volume of COVID-19vaccines topic?RQ2: What relationship do different sentiment posts and the sum of posts'direct forwarding volume in the COVID-19 vaccines topic network structure?Since the outbreak of COVID-19 in China, topics related to COVID-19 vaccines have been hotly discussed by the public on social media. In particular, vaccination campaigns across China began on 1 January 2021, when Beijing fully launched the COVID-19 vaccination campaign for nine key groups. The safety, efficacy, and side effects of vaccines have been further debated. Sina Weibo has been the largest social media platform in China with 230 million daily active users , 51. On The information of Weibo posts captured by us includes user name, user id, number of fans, post time, post content, post id, forwarding volume of posts, number of likes, and number of comments. Through data cleaning, we deleted Weibo posts with missing user names, repetitive posts, meaningless posts containing only pure emoticons, and posts with zero forwarding volume. A total of 13002 posts were left. To make the data samples more consistent with the requirements of the research topic, we used logistic regression of machine learning and random forest model algorithm combined with manual verification to preprocess the remaining 13002 posts.We divided the data after cleaning into two groups by content: One group is the content-related group which was highly related to the posting content and the research topic; the other group is the content irrelevant group which was unrelated to the research topic. Referring to the study of SAGE Working Group , we defiThrough the method of manual coding, it can provide effective training samples for machine learning. Therefore, we selected 3000 posts from 13002 posts by random sampling method. Three coders familiar with content classification standards were invited to encode the content of 3,000 extracted posts. The coding rule is as follows: If the content of the post is related to the research topic, the code is “1”; if the content of the post is not related to the research topic, the code is “0.” When counting the classification result of the content of a post, the coders' vote of at least two votes (≥2) will be counted as the final classification result of the post. After the coding, we randomly selected 10% of the posts whose coding results had been determined and invited another independent coder to test them. According to Holsti formula , the intThe determined 1000 posts were put into the machine learning algorithm as training samples. The logistic regression ROC curve  and randAfter verifying the availability of the machine learning model, we classified the content of 13002 posts by subject-dependent machine learning. The final results of classification were 3344 posts highly related to the research topic, and 9658 posts irrelevant to the research topic (some posts in the classification result are shown in the Forward). In the social network analysis model, the same user may publish multiple different posts in real network relationships . If the user makes only one post, then Forward = Forward_sum; If the user makes multiple posts, then Forward>Forward_sum.The research model is divided into sentiment analysis model and social network analysis model. In the sentiment analysis model, the dependent variable is the forward volume corresponding to each post in 3158 posts (ionships . Accordipositive), and the score of negative attributes is defined as (negative). The score represents the emotional strength and is put in the regression model as an absolute value.In the sentiment analysis model, the relationship between positive sentiments and negative sentiments contained in the content of posts and the forwarding volume is mainly discussed. Therefore, the independent variable in the sentiment analysis model is the sentiment polarity score to which each post belongs. Since the sentiment analysis model adopts the method of grouping regression, the score of positive attributes in the independent variables is defined as  Sentiment Vocabulary Ontology Database . DLUT isIn the social network analysis model, the influence of users' network relationship on forwarding behavior in the social network constructed in this paper is mainly discussed. On Weibo platform, users have already formed a huge social network through some connections. Therefore, this paper further investigates the influence of social network relation of posting users in the topic on its total forwarding volume and makes a regression analysis of degree, betweenness centrality, and closeness centrality of posting users as independent variables.In the process of building the social network analysis model, we crawled the reposts of 3,158 posts, totaling 62,122 reposts. The main crawl information includes forwarding user id, forwarding user name, forwarding time, forwarding content, and forwarding posts id. On this basis, the posting users of 3158 posts were taken as network nodes, and the forwarding relations between 62,122 posting users and 3158 posting users were taken as edges to establish the initial “posting user-forwarding user” network. The network consists of two types of nodes, one is the posting user, and the other is the forwarding user, which is a two-mode network. It is worth clarifying that the network relationship in “posting user-forwarding user” established in this paper is an unweighted forwarding relations edge. That is, if the posting user has one or more forwarding relations in this network, they are regarded as having a forwarding relation, and the relationship between them is assigned a value of 1; if there are no forwarding relations between the posting user and the forwarding user, the relationship between them is assigned a value of 0. However, this paper focuses on the influence of the social network influence of posting users on the forwarding volume of posts. Since forwarding users may simultaneously forward the posts of multiple posting users, we regarded forwarding users as “Bridges” to establish connections between posting users and then transformed “posting user-forwarding user” network into “posting user-posting user” one model network. Gephi 0.9.5 software was used to construct the social network relationship of this paper, namely “Sina Weibo social network relationship of the topic of COVID-19 vaccines.” At the same time, according to post), the number of pictures contained in the post (pic), the total number of words in the post (word), the number of emojis (emoji) contained in the post, whether there will be external links (url), and the number of fans (fans) of the user.”Existing studies show that posts with rich information form and content  are more likely to attract public transmission, and the forwarding volume of these posts is significantly higher than that of posts with a single form . TherefoIn this paper, we used multiple linear regression to establish grouping regression model  for sentiment analysis and social network analysis model (4-3). Variable selection and measurement of model  are shown in t-value to avoid the impact of heteroscedasticity on the regression model results.In the process of data analysis, two sets of regression model data were analyzed and processed to ensure the interpretability of model results. First, to reduce the existence of extreme values or excessive differences between dependent variable (forwarding volume) data in the model, the forwarding volume in the model was logarithmically processed. To avoid the influence of extreme values on the results, statistical software Stata 17.0 was used to conduct 1% tail reduction. To make the regression coefficient of the negative group easy to understand, this paper takes the absolute value of the sentiment variable (negative score) in the regression of the negative group. To make the regression coefficients between variables more meaningful, Z-score standardization was used on all variables during group regression. In addition, considering the possible dependence between variables, bivariate correlation analysis was also included in the analysis process. Finally, the white heteroscedasticity robust standard error was used to adjust the From the ranking of the retweets of Weibo posts on the topic of “COVID-19 vaccines” , the topSee According to the statistical results , the Weip < 0.05). However, there was no significant regression between the number of fans and the forwarding volume . The number of fans of posting users is positively correlated with the forwarding volume, which is consistent withThe statistical description of user characteristic variables, control variables, and forwarding volume in the social network analysis model is shown in our common cognition, but the coefficient is not significant. This indicates that under the shadow of social network relationship, the influence of users' social network on the forwarding volume is significantly stronger than the number of fans.p = 0.115), and there is a significant positive correlation between posts containing more negative sentiments and the forwarding volume . This indicates that posts containing negative sentiments are more likely to be forwarded, and it is worth paying more attention to the specific reasons.The statistical description of sentiment variables, control variables, and forwarding volume in the sentiment analysis model is shown in The first result of this paper was that the higher the degree of posting users in the social network structure, the higher the forwarding volume. This research result is consistent with previous research conclusions . It indivia self-gating, followed by other users seeing the information to decide whether to forward it or not, which results in a rapid spread of COVID-19 vaccine information. This paper confirmed the vital role of “gatekeeper” users in disseminating COVID-19 vaccine information and found the possible meaningful effect of ordinary users' participation in the gatekeeping of COVID-19 vaccine information.The second result of this paper was that the betweenness centrality of post users was positively correlated with the forwarding volume of posts, consistent with previous findings. As revealed by the findings, posts posted by users with gatekeeper characters are more likely to be reposted. For the traditional media, editors often play the gatekeeper role. However, in social media, the role of gatekeeper is more diversified since some ordinary users can also act as gatekeepers. Users are consumers of information and gatekeepers of information . It is nThe third result of this paper was that the closeness centrality of users was positively correlated with the forwarding volume of posts. In the previous literature review section, we reviewed users' closeness centrality. Previous literature only shows the relationship between closeness centrality and user access to information. Users with high-closeness centrality are relatively independent in the actual complex network structure of information transmission and can obtain useful information through a small number of nodes. Our results further expand the relationship between closeness centrality and forwarding volume. Therefore, we speculate that users with high-closeness centrality have an advantage not only in obtaining useful information, but also in disseminating information. In particular, in the particular social network structure of COVID-19 vaccine, high-closeness centrality users are not only receivers of information, but also important transmitters of information. In other words, the transmission of COVID-19 vaccine information needs to focus on the influence of high-closeness central users.This paper aimed to understand the correlation between different sentiment posts and the sum of posts' direct forwarding volume. This paper showed a positive correlation between negative sentiment posts and sum of posts' direct forwarding volume, while positive sentiment posts were not significantly correlated with sum of posts' direct forwarding volume. This finding extends the correlation between post sentiment and forwarding behavior. It gives us an insight into the correlation between sentiment and forwarding behavior, specifically which is within the COVID-19 vaccine topic. Combined with To be specific, we found posts could be divided into two main types in terms of post content. A post may positively impact vaccination, whereas the other type has a negative effect. The first type refers to the refute rumor posts published by official media accounts and the popularization posts of the knowledge of COVID-19 vaccines by official media accounts. For instance, the Weibo user “CCTV News” posted a post with the tag “Who shouldn't be vaccinated with COVID-19 vaccines,” the content of which provides specific information regarding the people who are not suitable to be vaccinated with the COVID-19 vaccines. The Weibo user, “People's Daily,” posted a post with the tag “10 questions and answers to gain insights into the newest doubts regarding vaccination,” covering various aspects of COVID-19 vaccines vaccination. The Weibo user “Guangzhou Daily” posted a message with the hashtag “False news concerned with the first vaccination stoppage in Guangzhou after June 9” to refute rumors. Although the posts mentioned above were defined as negative posts for containing more negative sentiment words, the actual impact was positive. Another type of Weibo post, mostly by ordinary users and primarily related to the vaccine's side effects, was more negative and had a high number of forwarding volumes. For instance, the Weibo user ordinary users A (3869 forwarding volume) said in a post, “Today I was given a preliminary diagnosis of sudden deafness. I think it's a side effect of the vaccine. My diet, lifestyle, etc., is the same as before the vaccine, which is why I suspect it's the vaccine. Online also a lot of people said that after the vaccine tinnitus ear stuffy hearing decline.” A post tagged “COVID-19 vaccines side effects” was posted by Weibo user ordinary users B (forwarding volume: 2532), and the text content is, “I don't know if it has anything to do with the COVID-19 vaccine, but I developed symptoms nine days after I finished the vaccine. There was nothing wrong with my ears before.” Although posts like the mentioned reflect the true feelings of individuals after receiving the COVID-19 vaccines, whether the COVID-19 vaccines directly cause harm  remains unclear. It has been studied that knowing that a person has experienced the side effects of influenza vaccination is a valid cue to action that affects vaccination behavior and can harm the influenza vaccination program . TherefoBased on social media data, this paper examines the impacts of Weibo text sentiment and users' social network characteristics on post forwarding in the COVID-19 vaccine topic. The results show that posts relating to COVID-19 vaccines with negative sentiment and neutral sentiment are more likely to be forwarded on social media, and posts relating to COVID-19 vaccines by posters with higher betweenness centrality or lower degree are more likely to be forwarded on social media. In view of the above conclusion, this paper puts forward the following recommendations.The first suggestion of this paper is to emphasize opinion leaders, gatekeeper users, and high-closeness centrality users. The research results of this paper show that users with high degrees, betweenness centrality, and closeness centrality are more likely to have their posts forwarded. Therefore, accounts with such characteristics in government, media, and medical institutions should give full play to their advantages in the transmission of COVID-19 vaccine information. On the basis of authentic and scientific information, the number of posts on COVID-19 vaccine knowledge will be increased to effectively improve the spread of COVID-19 vaccine posts. In addition, previous studies have shown that if accounts with high betweenness centrality do not follow a certain information, it is difficult for the information to flow to another transmission field . TherefoThe second recommendation is to mitigate the negative effects of the information epidemic. This paper found that a certain percentage of those users having high betweenness centrality were ordinary users see . This suThe third recommendation is to enhance knowledge of the side effects of the COVID-19 vaccines. As indicated by this paper, more negative posts were positively correlated with the forwarding volume of posts, and the further discussion revealed that the implications of this finding are 2-fold. Though the government, media, and medical institutions have posted on social media about the COVID-19 vaccines and refuted the rumors regarding the COVID-19 vaccines, some posts concerned with the vaccine's side effects were still reposted on social media. Hence, it is necessary to think deeply about the reasons behind this. First, we analyzed the popularization of knowledge about COVID-19 vaccines and found that the content about the adverse reactions to the COVID-19 vaccines accounted for relatively little. Second, when the public experienced adverse reactions, there was a lack of scientific proof from relevant institutions that vaccination was the cause of the adverse reactions. Thus, first, the government needs to strengthen the popularization of knowledge about the side effects of the COVID-19 vaccines. Next, the services offered by the government and medical institutions should be improved in response to adverse reactions in public after vaccination, and the causes of adverse responses should be scientifically determined to mitigate the negative effect of posts about the side effects of the COVID-19 vaccines on social media.Despite this paper analyzing the correlation between social network characteristics, textual sentiment, and forwarding of posts relating to COVID-19 vaccines, however, there are some limitations: First, due to time constraints, although this paper obtained a lot of original data, after data cleaning, there were relatively few data in line with the research topic, so future studies can supplement more data. Second, the mechanism of other factors impacting the forwarding of posts relating to COVID-19 vaccines, besides social network characteristics and textual sentiment, still needs to be further explored. Third, because this paper only studied China's Weibo users, most of them were young adults, with children and elderly groups seldom involved. For this reason, this paper is of limited reference significance for other groups. Lastly, this paper only explored the transmission effect of the COVID-19 vaccine topic from the perspective of transmission scope. However, the actual transmission effect of the COVID-19 vaccines message still needs to be further investigated due to the information epidemic influences it. Accordingly, subsequent studies can more comprehensively discuss and analyze the measurement of relevant variables and the reception of COVID-19 vaccine information among the elderly and children's groups. In addition, further studies on the actual effects of COVID-19 vaccine information transmission can be conducted in future.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Institutional Review Board of Social Sciences and Humanities Training Program, Jinan University. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.KS designed the study and analyzed the data. HW and KS were involved in manuscript writing. JZ revised the manuscript. All authors have read and approved the manuscript.This paper was funded by the National Social Science Foundation of China (Grant No. 15ZDA042).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.


Different feature learning strategies have enhanced performance in recent deep neural network-based salient object detection. Multi-scale strategy and residual learning strategies are two types of multi-scale learning strategies. However, there are still some problems, such as the inability to effectively utilize multi-scale feature information and the lack of fine object boundaries. We propose a feature refined network (FRNet) to overcome the problems mentioned, which includes a novel feature learning strategy that combines the multi-scale and residual learning strategies to generate the final saliency prediction. We introduce the spatial and channel ‘squeeze and excitation’ blocks (scSE) at the side outputs of the backbone. It allows the network to concentrate more on saliency regions at various scales. Then, we propose the adaptive feature fusion module (AFFM), which efficiently fuses multi-scale feature information in order to predict superior saliency maps. Finally, to supervise network learning of more information on object boundaries, we propose a hybrid loss that contains four fundamental losses and combines properties of diverse losses. Comprehensive experiments demonstrate the effectiveness of the FRNet on five datasets, with competitive results when compared to other relevant approaches. Visual saliency can be defined as the most interesting region or object in the human vision system. The detection and segmentation of salient objects in natural scenes is often referred to as salient object detection (SOD). SOD usually serves as an important image pre-processing in many applications, including strengthening the high-resolution satellite image scene classification under unsupervised feature learning , unsuperVGG  and ResNAmulet has  introducAs for our proposed method, which reconsiders the effectiveness of multi-scale feature fusion strategy, and the recently popular attention mechanism , we desiWe introduce an scSE module for pre-processing the outputs at five scales of the backbone. The scSE consists of channel and spatial attention. It improves the representation ability of the features at each scale and enhances the effectiveness of the residual learning strategy.We propose an AFFM module that enables the overall fusion of multi-scale information to compose the final saliency prediction. AFFM combines two kinds of multi-scale feature fusion strategies to improve saliency detection performance.A hybrid loss is proposed for supervision during five scales’ residual learning processes, and for the generation of final saliency maps. It fuses BCE, structural similarity (SSIM) and dice and intersection-over-union (IOU) to train the model in local-level and global-level.Our main contributions are as follows:The remainder of the work is structured as follows: the related SOD works are discussed in Amulet, DSS, R3Net  and the x denotes the initial input, and also can be regarded as prior knowledge. Without using residual learning, the formula is written as The strategy for residual learning is inspired by ResNet , and it Refs. ,14 show It may also be considered as a dynamic selection process in computer vision that which is achieved by adaptive weighted features based on the relevance of the input data. In the saliency areas, it mimics the mechanism of the human visual system. Attention mechanisms provide performance improvements in many computer vision tasks. Some scholars have introduced the attention mechanism into SOD. Liu et al.  proposedWe utilized channel attention and spatial attention to design scSE and weight spatial attention to guide the network to learn more discriminative feature for predicting saliency map. Then, we designed the feature fusion module AFFM with multi-scale features, processing the feature at each scale after ARM, and adaptively integrated them to compose the final saliency prediction.In addition to the discussion of the model architecture, the demand for innovating different loss functions have also become more prominent. In most of the SOD models, the binary cross-entropy (BCE) loss is often used for network training. It is formulated as follows:Luo et al.  introducSSIM and IOU loss to the traditional BCE loss. SSIM loss and IOU loss are formulated as follows:Qin et al.  introducThese loss functions focus on different points. BCE and SSIM focus on local supervision, calculating the gradient of each pixel based on the prediction of limited neighbored regions. Dice and IOU focus on global supervision, reducing the difference between prediction and GT. They enhance the prediction of object contour. Based on that, we propose hybrid loss, which combines these four loss functions to supervise the network learning.In The feature refine network (FRNet) utilizes the full convolutional network to solve the SOD task. The entire framework is illustrated in The original ResNet model is used for the image classification task, so that the spatial resolution of the feature generated by the network is mismatched to the input image resolution. To make it suitable for the SOD task, we have made the following modifications: (1) the full connection layer of the ResNet model for image classification is removed. (2) The stride in ResNet-4 is changed to 1, retaining more feature information because the feature spatial scale has not changed.After the backbone, the outputs from each layer are processed by scSE to guide the feature maps that focus on the saliency region. These maps are fed to the ARM modules for residual learning, to adjust the prediction output gradually from a small scale to a large scale. Finally, five scale outputs after ARM processing are fed to the AFFM module for adaptive fusion. The process generates the final prediction output. The entire network is trained under the supervision of the hybrid loss.The main idea of AFFM is to achieve adaptively the learning of the fusion spatial weights of feature maps in various scales. As shown in Unifying scale. The saliency map of the resolution at scale Adaptive fusing. We use 1 × 1 convolution layers to compute the weight scalar maps Inspired by Roy et al. , we propW denotes the filter kernel weight and GAP denotes the global average pooling. GAP uses the nn.AdaptiveAvgPool2d method for global average pooling operations.The channel attention is formulated as follows:Spatial attention is formulated as follows:scSE is formulated as follows:BCE and SSIM, these are unable to supervise the network to learn fine object boundaries. For global supervision, dice and IOU can detect finer object boundaries. Naturally, we consider the model to achieve better performance when it is training with hybrid loss. The hybrid loss is defined as follows:The common loss functions in the SOD task are divided into two categories. For local supervision, such as BCE and SSIM supervise the network as a local loss to prompt the network learning of the approximate location of the salient object. Dice and IOU supervise the network as a global loss to prompt the network learning of the fine boundary of the salient object. FRNet employs the hybrid loss on the predicted output branch of the ARM blocks at all scales, as well as the final output after AFFM processing, as shown in These loss functions complement each other. More experiments about ablation of the hybrid loss can be found in To validate the FRNet network, we conduct the comparison experiment on five public datasets  for the experiments. At first, each image is resized to 384 × 384 and performed normalization. During the training, epoch is set to 40, batch-size is 16. The momentum is set to 0.9 and weight decay is 0.0005. Then, we set the base learning rate (lr) to 0.0005 and the learning rate multiplies 0.1 every 10 epochs. FRNet employs the Adam optimizer and hybrid loss to optimize the network. The “Kaiming” method initializes the convolutional layers of ResNet. We evaluate the saliency detection performance of FRNet on five benchmark datasets.ECSSD  containsPASCAL-S  has 850 DUT-OMRON  containsHKU-IS  includesDUTS  allocateS is converted into a binary mask M. Precision and recall are calculated by G and M. G denotes ground-truth. PR is formulated as follows:At first, the saliency map Precision and recall cannot fully evaluate the quality of the prediction map, in other words, the high precision and recall are both required. So, F-measure is proposed as the weighted harmonic mean of precision and recall with a non-negative weight When the max-F value is larger, the model performance is better.Sm evaluates the structural details of the prediction map, and combines region-aware and object-aware structural similarity evaluation to obtain the final formulation of structure-measure, which is as follows:n et al. .A larger value of Sm indicates the better performance of the model.S and binary GT. S and M are pre-normalized to the range of The above metrics have not taken the prediction of the non-salient pixels into account, that is, the pixels correctly labeled as non-salient. For this purpose, the MAE is calculated by saliency map A smaller value of MAE indicates the better performance of model.FRNet compares with Amulet , BASNet As shown in We evaluate the prediction maps on PR Curves and F-measures. We carry out experiments on five public datasets to analyze the validity of hybrid loss, AFFM and scSE.To demonstrate the effectiveness of AFFM, we design a set of experiments on AFFM by only adding AFFM modules to the baseline and then comparing results with the baseline. The first and second row result in As shown in Firstly, we conduct ablation experiments for different combinations of loss functions. As shown in Secondly, we conduct ablation experiment on the hybrid loss, as shown in To investigate the role of scSE in the model, we carry out the ablation experiments of scSE. The results are shown in rows 1 and 4 of A novel FRNet for SOD is proposed in this paper. To construct the final prediction, FRNet gradually optimizes the prediction results from a low to a high scale and obtains information from optimized features at all scales, until the results match GT as closely as possible. We propose a hybrid loss supervised method to obtain the object boundary information to solve the problem of the coarse object boundary. In the ablation experiments, we demonstrate the effectiveness of the hybrid loss. The extensive experimental results indicate the efficiency of the proposed strategy and FRNet. However, there are still possibilities to improve our network architecture, and we will continue to investigate the potential of various network architectures in the field of SOD, such as transformers.


Background and Objectives: Osteoporosis is a major risk of fractures, harming patients’ quality of life. Dual-energy X-ray absorptiometry (DXA), which can detect osteoporosis early, is too expensive to be conducted on a regular basis. Therefore, we aimed to evaluate a screening method using chest radiographs developed in Japan applied to another population. Materials and Methods: Fifty-five patients who had a chest radiograph and DXA and applied within three months of each test were recruited from the patient database of Semmelweis University . Graphical analysis of the chest radiographs was conducted to identify the ratio of the cortical bone in the clavicle of each patient. Two researchers performed the analysis, and multiple regression was conducted to determine the bone mineral density of each patient provided by DXA. Results: The Pearson correlation between two examiners’ determinations of the cortical bone ratio was 0.769 (p < 0.001). The multiple regression model proved to be statistically significant in identifying osteoporosis, but the model adopted for the Hungarian population was different compared to the Japanese population. Conclusions: This simple, economic Japanese graphical analysis method for chest radiographs may be feasible in detecting osteoporosis. Further studies with a larger population of patients with greater variety of ethnicity would be of value in improving the accuracy of this model. Osteoporosis is associated with decreased bone mass, associated microarchitectural deterioration, and fragility fractures . It is aThe gold standard for diagnosing osteoporosis is the measurement of bone mineral density (BMD) by dual-energy X-ray absorptiometry (DXA). However, DXA requires specific, expensive equipment, as well as well-trained technicians. Furthermore, Medicare payments have cut DXA checkup for osteoporosis , leadingPreviously, Kumar and Anburajan  reportedThis is a single-centered, retrospective study conducted in Hungary. The study data were derived from patient records and analyzed for secondary use. From the patient database of Semmelweis University , 55 patients who had a chest radiograph and DXA and applied within three months of each test were identified and included in this study. Chest radiographs were performed on the following X-ray devices: 7X PRO 100-HF 650 , 7X Super 750B , GE Discovery XR 656 .Bone mineral density was measured with GE Lunar Prodigy  dual-energy X-ray absorptiometry. As shown in This study protocol was approved by the ethical committee of the Graduate School of Medicine, Osaka University  and the Semmelweis University Regional and Institutional Committee of Science and Research Ethics .Graphical analysis was conducted under the methods developed by Ishikawa et al.  First, the shade of the clavicle was extracted from the chest X-ray. The contrast-limited adaptive histogram equalization conducted by using open source library Fiji v 1.51i  created After the filtering, a region of the proximal clavicle where the clavicle became horizontal to the axis of the radiogram was determined by visual judgement, and the edge pixels were extracted by hand. The procedures for drawing perpendicular lines across the upper and lower margins of the clavicle were decided so that the line was between 90 ± 10 degrees from the lines that were drawn to the lower margin of the clavicle from its origin .The pixels defined on the perpendicular line from the previous step were used to create a pixel value profile, and an eight-order function was used to fit the approximated curve. The gradients of the tangent lines for the approximated curve were defined in the areas between the upper and lower clavicle margins. The first part where the tangent gradient became the minimum after the first local maximal value was defined as the upper margin of the cortical bone and the cancellous bone, and the distance between that point from the upper clavicle margin was defined as the upper clavicle cortical bone length (CL). The point over the local minimal value with the largest tangent gradient was defined as the lower margin between the cortical bone and the cancellous bone, and the distance between the point of the lower clavicle margin was defined as the lower CL. Clavicle cortical bone-length ratio (CLR) was defined by dividing the upper CL and lower CL by the width of the short axis of the clavicle. From the pixel value profile defined from the previous step, the average CLR was adopted from the three lines used for the analysis.t-test was applied to the continuous variables, while a chi-squared test was applied to the categorical variables.We presented each continuous variable with its mean and standard deviation (SD), and each categorical variable is represented by numbers and percentages. A 2].Two independent examiners were assigned to analyze the radiographs. The two examiners conducted their analysis on each side of the clavicle of each patient. Pearson correlation analysis was conducted to validate the results of the CLR between the two examiners. A multiple regression logistics analysis was conducted using the parameters sex, CLR, age [year], body weight [kg], height [cm], BMI (body mass index) [kg/mp-value less than 0.05 was determined as statistically significant.EZR  , a graphp < 0.001).Results of the DXA and Z-scores obtained from the DXA are shown in The results of the logistic regression analysis are shown in Our model achieved statistical significance in all regions of the DXA measurement.This study aimed to develop a method to utilize chest radiographs for the primary screening of osteoporosis. The results of our study may imply that such methods may be feasible in estimating the BMD of patients who have undergone chest X-rays, which is an important factor for the diagnosis of osteoporosis. To the best of our knowledge, no other study has been conducted to evaluate the status of osteoporosis using graphical imaging using computer analysis.Osteoporosis is a major public health problem, affecting hundreds of millions of people worldwide. The main clinical consequence of the disease is bone fractures. It is estimated that one in three women  and one Routine chest radiographs obtained for other reasons in various clinical settings can be applied to identify patients at risk of osteoporosis without additional radiation exposure or cost, which could improve osteoporosis screening. For example, in Japan, the screening rate of osteoporosis for women remains low at 4.6% , and thiIdentifying high-risk groups for osteoporosis using common chest radiographs might increase the disease recognition and prevent osteoporotic fractures. A previous twin study found that BMD is strongly heritable, especially in females in all locations, which highlighted the importance of family history as a risk factor for bone fractures . Public Our study has two strengths that support the feasibility of the method created by Ishikawa et al. . FirstlyThis study has several limitations. Firstly, the nature of the study limits the participants to a relatively osteoporotic population, as the participants were recruited from a selection of hospital patients. This can be seen by the relatively low average of Z-scores (less than zero). Thus, a relatively healthy population may not have been able to participate in our study. However, as our method is thought to be used to screen relatively ill patients, we believe that this aspect of our study may be viewed as a strength, rather than a limitation. Secondly, our model derived from multiple logistic regression could not be verified on a clinical basis, as we were unable to obtain any data that recorded the Z-score of the BMD of the Hungarian population. The results obtained were automatically derived from the measurement machine, and the manufacturer was not able to provide the authors with such data. Thirdly, the sample size of the study remains relatively small, which may have been a reason for reporting models with covariates that were not statistically significant. Fourthly, this study is limited to the Hungarian population. As both genetic and environmental factors are thought to play a role in bone mineral density as well as fractures , future In conclusion, our study revealed that a Japanese graphical analysis method using chest radiographs may be feasible in detecting osteoporosis. This method does not require the use of DXA and would be usable in areas under simple analysis. Further studies with a larger population of patients with greater variety of ethnicity would be of value to improving the accuracy of our model.