Cardiovascular disease (CVD) has become a common health problem of mankind, and the prevalence and mortality of CVD are rising on a year-to-year basis. Blood pressure (BP) is an important physiological parameter of the human body and also an important physiological indicator for the prevention and treatment of CVD. Existing intermittent measurement methods do not fully indicate the real BP status of the human body and cannot get rid of the restraining feeling of a cuff. Accordingly, this study proposed a deep learning network based on the ResNet34 framework for continuous prediction of BP using only the promising PPG signal. The high-quality PPG signals were first passed through a multi-scale feature extraction module after a series of pre-processing to expand the perceptive field and enhance the perception ability on features. Subsequently, useful feature information was then extracted by stacking multiple residual modules with channel attention to increase the accuracy of the model. Lastly, in the training stage, the Huber loss function was adopted to stabilize the iterative process and obtain the optimal solution of the model. On a subset of the MIMIC dataset, the errors of both SBP and DBP predicted by the model met the AAMI standards, while the accuracy of DBP reached Grade A of the BHS standard, and the accuracy of SBP almost reached Grade A of the BHS standard. The proposed method verifies the potential and feasibility of PPG signals combined with deep neural networks in the field of continuous BP monitoring. Furthermore, the method is easy to deploy in portable devices, and it is more consistent with the future trend of wearable blood-pressure-monitoring devices . The prevalence and mortality of cardiovascular disease (CVD) are rising on a year-to-year basis. Hypertension, as the most-prevalent chronic disease, has been confirmed as the main cause of cardiovascular and cerebrovascular diseases. A recent study suggested that the number of people with hypertension worldwide is nearly 1 billion and will increase to 1.56 billion by 2025  Hz.Given the need for the input of the deep learning network, the raw PPG signal should be cut into fixed-length segments through a sliding window after filtering. The fixed-length segmentation mode is simple to operate, preserves signal diversity, and does not need to locate the fiducial points. Lastly, the PPG signals were split into 3-second segments, a length that contains multiple cycles of cardiac activity without imposing a large burden on the network model. The same operation was applied in parallel to the corresponding ABP signals.N denotes the number of samples in the segment.A series of quality screening rules was adopted to exclude unreliable data, so as to obtain high-quality PPG signals and further reduce data noise. The signals with SBP greater than 180 mmHg and DBP less than 50 mmHg were first excluded from the dataset. Second, skewness can be employed to measure the asymmetry regarding the probability distribution of a random variable. Moreover, Krishnan et al. suggested that skewness is correlated with the quality of PPG signals . AccordiMoreover, since a high-quality PPG signal should maintain a good periodicity, the autocorrelation coefficient was adopted to evaluate the signal quality . The autAfter the above pre-processing steps, 47,964 high-quality PPG signal segments were included in the final experiment. The blood pressure distribution of the final dataset is shown in x denotes the input feature; x is directly correlated with the output through shortcut connection, such that information loss can be largely avoided and learning difficulty can be significantly reduced.He et al.  proposedA single-scale feature extraction module can only use fixed-size convolutional kernels, which may lead to insufficient feature extraction and cannot extract deep feature information well. The multi-scale feature extraction module actually samples the signal at different granularities, such that the network model captures different scales of receptive fields, and thus mines the features of different fineness. The structure of the multi-scale feature extraction (MSFE) module designed in this study is shown in The size of the convolutional kernel in regular-sized convolutional branch was set to the commonly used 3, 5, and 7, respectively. In addition, a large-sized convolutional branch was introduced in this study. Inspired by the research of Ding et al. , the sizMoreover, the padding operation was adopted to ensure that the output feature length of each parallel branch was consistent. The results of each branch were merged by the concatenation operation, followed by the convolutional operation to reshape the dimension and then input into the subsequent residual structures.x; W represents the width of the feature map.The squeeze-and-excitation (SE) module refers to an attention module based on the channel dimension . It extrz denotes the global receptive field of c feature channels obtained by the squeeze operation and s denotes the weight coefficient of c feature channels.Second, the excitation operation adopts two fully connected (FC) layers to first reduce the dimension and then increase the dimension, and the ReLU function serves as the activation function between the two FC layers. The output of the last FC layer is activated by the Sigmoid function to determine the attention weight of the channel. The calculation procedure of the excitation operation is expressed in Equation .(5)s=siIn the last step of feature weight calibration, the channel weights calculated by the SE module are multiplied with the respective corresponding channels in the feature map to obtain the effective feature layer with attention information. The calculation procedure is expressed in Equation .(6)x˜c=The mean absolute error (MAE) and mean-squared error (MSE) are commonly used evaluation indexes in regression tasks, and the above two types of losses are commonly used for gradient optimization during the training process of the models. Assuming that Equation .(7)MSE=The MSE calculates the mean of the squared error between the predicted and reference values, so using the MSE loss function is convenient for the gradient descent algorithm and facilitates the convergence of the function. However, if there are outliers in the dataset, the MSE loss function will be significantly affected by the outliers. The MAE loss function is more robust to outlier points, but more complicated to compute the gradient. The Huber loss is calculated as shown in Equation , which iThe experiments were performed on an NVIDIA RTX 3090 GPU, using a software platform based on cuda 11.1, pytorch 1.10, and python 3.8. The training effect of the convolution neural network is closely related to the settings of the model parameter, so the parameters of each model were unified at the training stage. The dataset was divided into a training set, a validation set, and a test set at the ratio of 7:1:2. The batch size was set to 1024 for each iteration. The learning rate was dynamically adjusted using the SGD optimization and cosine annealing decay, with the initial learning rate set to 0.001. Furthermore, 120 epochs were trained for all models to ensure the convergence of the model.In this study, the following improvements were proposed based on ResNet34: using a multi-scale feature extraction module rather than a regular feature extraction module in the baseline network, introducing the channel attention mechanism in the residual module, and adopting the optimized Huber loss function at the training stage. To verify the effectiveness of the above improvements, ablation and comparison experiments were conducted for each of the above improvements, respectively. As depicted in Furthermore, the use of the Huber loss during model training resulted in a decrease of 0.66 and 0.35 mmHg in the estimates of SBP and DBP, respectively. Incorporating all the improved modules can further lead to the enhancement of performance, and the MAEs of the final proposed model for SBP and DBP were 5.98 mmHg and 3.24 mmHg, respectively, as indicated by the experimental results.m is the number of samples.The Association for the Advancement of Medical Instrumentation (AAMI) has established internationally accepted error standards for blood pressure . The preThe Bland–Altman plot is a common method to evaluate the consistency of two continuous variable measures. The two measurement methods used for comparison usually comprise a new method that needs to be investigated and an accepted standard method. The two methods are considered to be in good agreement if 95% of the differences between two measurement results lie within the range of (mean-1.96*SD) and (mean+1.96*SD).Currently, continuous cuff-less blood pressure monitoring is urgently required. Given the potential of the PPG signal in blood pressure estimation, the PPG signal and deep learning network were employed in this study to estimate blood pressure continuously.In this study, a multi-scale feature extraction module was introduced based on the basic framework of ResNet34. The initial module of the novel framework fully explored the features of the input signal by activating the multi-scale receptive field. The multi-scale feature extraction module contained regular-sized convolutional branches. Moreover, it added a large-sized convolutional branch. In the large-sized convolutional branch, a combination of depthwise separable convolution with a kernel size of 13 and pointwise convolution was used to reduce the number of parameters while increasing the effective receptive field. As depicted in Each channel of the feature map is equally important by default in the conventional convolution and pooling processes. In contrast, the importance of different channels is not the same in actual problems. The SE attention module facilitates the feature extraction of the previous layer by reassigning channel features. Moreover, short connections in the residual module are capable of significantly alleviating the problem of gradient disappearance and facilitating feature propagation. The result indicated that the embedded attention mechanism module contributed well to the prediction of SBP and DBP, suggesting that the SE attention mechanism can obtain a more discriminative feature representation, thus increasing the prediction accuracy of the model.The derivative of the MAE loss function is constant, thus hindering gradient calculation. If the learning rate is constant, the loss function will fluctuate around the stable value, and the model may obtain a local optimal solution. The MSE loss function is susceptible to outliers. Moreover, if the outliers are damaged abnormal samples, this will affect the convergence trend of the model. The Huber loss function improves the shortcomings of the above two loss functions and is more robust to outliers, and it is easier to obtain the global optimal solution. Probably because the original PPG segments were screened during the dataset pre-processing, the quality of the dataset was improved. Accordingly, as revealed by the experimental results, we found that the performance of the model was slightly enhanced by using the Huber loss function for training.Furthermore, as indicated by the experimental results, DBP exerted a better prediction effect than SBP. The reason for this result is that the fluctuation range of SBP was significantly larger than that of DBP, thus leading to a higher prediction error.Although a large number of studies have emerged in the field of continuous BP prediction, it is difficult to directly compare our experimental results with related work due to differences in the dataset size, input signals used, and evaluation metrics. Many studies adopted PPG signals combined with ECG signals, which can introduce more physiological information and increase the accuracy of the model. However, such methods also have several limitations. For instance, the above methods require two types of sensors, so they are difficult to deploy on mobile devices such as a smartphone because it is difficult to make further modifications to the hardware of a smartphone that has already been produced. Moreover, there is also difficulty in the alignment of the two signals. There are also some studies that have used features extracted from PPG signals as the inputs, which rely on strong prior knowledge. Thus, for a better comparison, we compared the proposed method with the latest studies based on the MIMIC public dataset, using only the raw PPG signals as the input. From In this study, the PPG records in the MIMIC dataset were all collected from ICU patients with severe symptoms, whose blood pressure may be affected by disease, medications, and other factors. On that basis, the above PPG signals are not representative of the signal characteristics of most people. Besides, by a comprehensive analysis of Besides, the computational complexity is the primary issue that must be considered in practical applications. Resorting to a cloud server can be a proposed solution. Developers can deploy the proven models on cloud servers. The signal is acquired and initially preprocessed on the mobile side, then the data are transmitted to the cloud server for prediction, and the results are returned to the mobile side. With the communication between cloud servers and wearable devices, the problem of the insufficient computing power of wearable devices can be solved. A deep learning network for continuous blood pressure prediction using only PPG signals was proposed in this study. Under the ResNet34 framework, the proposed network replaced the initial feature extraction module with a multi-scale feature extraction module and introduced the channel attention mechanism in the subsequent residual module. Moreover, a comprehensive and robust Huber loss function was adopted in the training stage. The proposed method yielded competitive prediction accuracy on the UCI dataset. The prediction errors of SBP and DBP conformed to the AAMI standard, and the accuracy of DBP reached Grade A of the BHS standard, while the accuracy of SBP almost reached Grade A. The proposed method only used PPG signals which is feasible and promising. It did not require the simultaneous acquisition of two signals or complex feature engineering. Thus, a single-channel PPG signal combined with an end-to-end deep learning network for continuous blood pressure prediction serves as a simple and effective solution for blood pressure prediction on portable wearable devices in the future.


Geodetic-grade Global Navigation Satellite System (GNSS) receivers designed to implement permanent stations represent the most complex and costly technology in the field of GNSS instrumentation. On the other hand, a large number of innovative applications, highly demanding in terms of positioning precision and accuracy, is pushing the implementation of networks of permanent stations with a higher and higher spatial density. In this scenario, the development of brand new GNSS reference stations, which combine the most advanced technologies in the field of data availability and integrity together with reduced costs  is becoming of paramount importance. For this reason, in 2019 the EU Agency for the Space Programme (EUSPA) has financed a research project, called “next Generation gnss REference stATion—GREAT”, aimed at developing and demonstrating the potentiality of a brand new GNSS receiver suitable to implement permanent stations. This paper describes the solution developed by the project consortium, composed of four Small or Medium Enterprises (SMEs) based in Italy, France and Belgium, and the preliminary results achieved in the field tests. Currently, the permanent networks of Global Navigation Satellite System (GNSS) reference stations are complex infrastructures based on specialized instrumentation and costly software tools. Moreover, installing, setting up and maintaining a reference station implies relevant costs that prevent the wide spread of this technology. As a result, most of the public and private GNSS networks are not very dense in the European territory and much less worldwide.At the same time, a large number of applications, highly demanding in terms of positioning accuracy, would benefit from the availability of real-time differential corrections from reference stations. It is the case of devices or systems based on the well-known real-time-kinematic (RTK)  techniquIn the very last few years, some manufactures started delivering multi-constellation multi-frequency GNSS chipsets, which are low-cost with respect to the standards for high-end GNSS instrumentation but with performance allowing millimetric to centimetric level accuracy, respectively, in static-differential and RTK, therefore similar to the state-of-the art professional GNSS receivers. Besides very low-cost chipsets mostly suitable for mass market applications (as in the case of Broadcom BCM47755 ), chipsewww.spaceexe.com, accessed on 28 June 2023—and YetItMoves Srl—www.yetitmoves.it, accessed on 28 June 2023), France  and Belgium . Its main goal is the development, test and demonstration of an innovative GNSS reference station, capable of offering performance levels similar to the ones of the current geodetic grade stations but with the following distinguishing features:-costs  up to a quarter of the present standard.-single integrated device including on-board cellular LTE modem and solar panel charger, in order to simplify the installation as much as possible.-low power consumption, including all the aforementioned components, respect to the standard (6–8 Watts), in order to allow the receiver to be easily powered with solar panels and small backup batteries when installed in remote areas.The concurrent need for higher density GNSS networks and the availability of new multi-constellation multi-frequency GNSS chipsets has created the opportunity for a research project named GREAT (next generation Gnss REference stATion), funded by the European Agency for the Space Programme (EUSPA) as part of the “Fundamental Elements” call 2019 (grant. N. GSA/GRANT/04/2019/GREAT). The project has been carried out by a consortium of four SMEs based in Italy .-Near-real-time spoofing and jamming detection.-raw GNSS data quality measurement using third party software like GNUT-ANUBIS Free 2.3 .-Computation of periodic  station displacement based on a network adjustment approach.-Generation of alerts in case of anomalies in telemetry, GNSS data quality and abnormal displacements of the antenna .-Generation of hourly RINEX 3 or 4 files (Hatanaka compressed and zipped) containing the observables of each receiver part of the network, and their publication through HTTPs or FTPS protocols toward the final users.-Computation of the hash string of each hourly RINEX file  and its storage on an external blockchain implementation. In this way, every final user at every time can compare the hash string saved on the blockchain with the one that he/she can compute from the RINEX file downloaded by the server, in order to be sure that the RINEX file was not modified after its creation.In order to simplify the receiver architecture as much as possible , in the GREAT system several functionalities are moved from the receiver itself to a software tool for real-time remote data acquisition and processing, which can be installed on a processing server, and that implements the following functionalities:This paper aims at summarizing the main outcomes of the project, which has reached its conclusion in May 2023. We present the architecture of the developed system, with special focus on its innovative and distinguishing features; moreover, we provide a description of the field test campaign which has been realized in the last months of the project and the main achieved results.Currently, geodetic grade GNSS receivers exploited in the realization of permanent stations are mainly COTS products commercialized by large global suppliers, such as Leica Geosystems, Trimble, Topcon or Septentrio, just to mention the most important ones. The reason is related to the need to have high performance and reliable instrumentation suitable to work continuously, possibly for several years, with the minimum maintenance possible. However, in the last few years new players have entered the market, both from Europe (companies such as Stonex) and the Far East , offering advanced products at relatively lower prices with respect to the standard.Besides such commercial products, it is worth mentioning that several research projects, mainly financed by European agencies, were dedicated in the last few years to the development of innovative GNSS receivers. Among the others, we can mention here the eMAPs project , financeWhen dealing specifically with GNSS reference stations, it is important to mention the RIMS V2 Breadboard (R3B) project , financeHowever, among all mentioned projects, GREAT presents several distinctive features, such as the integration on a single electronic board of all components for power supply and data transmission (which is probably unique in the panorama of GNSS reference stations), and the attention paid to the minimization of power consumption, which makes the system suitable for installation in remote areas. This section reports a description of the GREAT GNSS system, including its hardware and software components. Indeed, the goal of GREAT is not only to develop a GNSS receiver but a comprehensive system, including both hardware and software modules. The following subsections describe in detail each part.The GREAT GNSS receiver is designed to integrate all the functionalities needed to operate a GNSS reference station, without the need for external devices or components, such as battery chargers or telecommunication devices. Moreover, it includes a number of external interfaces, useful to be easily integrated in existing or future systems.-power control and battery charging via photovoltaic panels.-wireless communication (4G + ISM 868 MHz).-monitoring grade accelerometer.-analog input channels for external sensors (standard 0–20 mA).-data storage (SD + Flash memory).In particular, the following functions are integrated:The hardware architecture is shown in The Micro-Controller Unit (MCU) is a 32-bit ARM Cortex M3 based architecture. It combines low power consumption and several internal peripherals and interfaces. It is an engineering trade-off between other more powerful and energy consuming architectures  and ultralow power MCUs.The GNSS core is a Septentrio Mosaic X5 chipset , which wThe power distribution and control unit are a key feature of the GREAT receiver. It integrates in the same PCB the power distribution and the module to charge an external 12 V lead acid battery, using a maximum-power-point-tracking (MPPT) battery charger powered by a photovoltaic (PV) panel. The lead acid battery is the main source of power of the GREAT receiver, even during nighttime; the PV panel is used to recharge (and/or maintain charged) the battery during daytime. In the most energy consuming case  measured average power consumption is about 2.5 W. As demonstrated by the field tests described in the following sections of this paper, the device can work with a 12 V/36 Ah lead acid battery and a 100 Wp PV panel. The autonomy of this configuration, in case of fully charged battery and PV panel failure is (12 V × 36 Ah)/2.5 W Besides standard physical interfaces (RS232 and USB), the board hosts integrated components for wireless data transmission, among which an ISM modem working on the 868 MHz band  plus an LTE modem, which represents the most mature technology for cellular data transmission at the time of design of the system. The front-end of the ISM modem integrates a narrow band SAW filter for certification and intra-board EMI reduction, so that the second harmonic on the 868 MHz band power amplifier does not interfere with the L1 (1575 MHz) GNSS band. For what concerns the cellular connectivity, among the different competitors, a Telit LT910-WW modem  was seleThe board integrates a tri-axial digital MEMS accelerometer , which The GREAT receiver is equipped with an industrial grade 16 GB micro-SD card, used to log a copy of all acquired data. The system can track several telemetry parameters related to the storage, such as the average write time or the number of cyclic redundancy check (CRC) errors that occurred during writing operations.Finally, the board integrates eight analog inputs used to easily integrate any third party 4–20 mA standard sensor  and periodically transmit these data in the same telemetry packet. The GREAT SW platform can show and use these data for post-analysis. The PCB dimensions are 19 × 9.5 × 1.5 cm and external GREAT receiver dimensions are 22 × 10.5 × 4.5 cm (excluding mounting brackets/flanges and connectors). The total weight of the GREAT receiver is about 0.6 kg.According to the general architecture of GREAT, several functionalities of the system are not implemented at hardware level by they are demanded to software components designed to run on a remote “acquisition and processing server”. Such server module is mainly dedicated to real-time data acquisition and validation , to their archiving and publication both as real-time (RTCM 3.2 corrections) or post-processing (RINEX 3 or 4) products. The server software also includes modules for user alerting through email and SMS. From a functional point of view, the main modules of the software tool are the “real-time acquisition and processing” (RTAP) and the “periodic data processor” (PDP) components. At each software startup, an instance of RTAP is executed for each GREAT station part of the controlled permanent network, and it implements the following actions, summarized in graphical style in -○If the connection is established, then it starts getting all acquired data in real-time (raw GNSS observables plus telemetry), and to interpret the GREAT binary protocol, in order to separate the different data types.○If a connection is not successful or if during the acquisition the connection is lost with the receiver, a warning message is promptly generated and sent to the “email/SMS sender” in order to warn the user in almost-real-time.It tries to establish a connection with the GREAT receiver:-○If data pass the check, then they are published in real-time through the integrated NTRIP caster and are saved into the temporary “raw data archive”.○In case of spoofing or tampering detection, then data are discarded, and an alert is raised and transmitted in almost-real-time to the “email/SMS sender”.GNSS data acquired by the previous module are passed to the “real-time spoofing detector”, which verifies the authenticity of the acquired data:The spoofing detection procedure is based on the computation of several quality indexes on raw GNSS data  as on the detection of anomalous displacements. The routine for raw GNSS data control implemented here has been adapted from the algorithms presented in . The con-It converts the binary files containing the raw GNSS observables of all stations part of the network into hourly RINEX files with observables sampled at 1 Hz  and archives them in the filesystem. Such an archive can then be published to possible final users with an FTP implementation. The module warns the user with email/SMS in case a specific conversion process fails or in case of unavailability of an expected binary file.-It computes the SHA-512 hash string  of each -It computes a set of quality parameters related to the raw GNSS data acquired in the last hour, such as percentage of acquired over expected GNSS epochs and observables, percentage of observables with cycle slips, average multipath and carrier to noise ratio. All parameters are computed for each frequency of each tracked satellite system. In order to generate trustable results, quality indexes are computed exploiting an instance of the G-NUT Anubis Free software , which i-It computes the average telemetry parameters  belonging to data acquired in the last hour.-It generates possible warning messages in case of detection of anomalous values on GNSS quality and telemetry. The software compares the last updates of all computed variables with a set of thresholds defined by the user. If any threshold is exceeded, then a message is generated and transmitted to the user by email.-○the exploitation of the ionospheric-free linear combinations of GNSS observables, which are computed on the input L1, L2 and L5 observables and used in the positioning process.○the exploitation of solid tide and ocean tide loading (OTL) models, the latter exploiting the OTL parameters computed for each specific location by the Onsala Ocean Tide Loading provider .○the possibility to perform a simple “network adjustment” strategy on the results of baseline processing, that is to compute the differential displacements of each GREAT station with respect to two or more reference stations, whose a priori coordinates are known with an high degree of confidence , and then to estimate the absolute coordinates of the station with a least square approach .It computes the accurate and precise antenna phase center displacement in the last period. Such a computation is based on a static-differential approach working with double differenced carrier phases observables ,30. The A single instance of the PDP module manages the whole network of GREAT receivers. Every hour, it executes in sequence the tasks shown in All periodic tasks are repeated indefinitely until closing the software or interrupting the acquisition.The GREAT client application is the third component of the system described in this paper and it represents the front end of the software tool that manages the network of permanent stations. It allows the user both to monitor the status of the stations and to modify their configuration. More in detail, it allows showing all computed variables  in graphs and table format for each station part of a monitored network. Moreover, it allows the user to set all the thresholds exploited by the server-side software to raise the alerts described in the previous section.It is designed as a web application composed of a set of graphical interfaces, accessible only by authenticated users. Since it does not implement relevant scientific or technical innovative elements, it is not described in detail in this work. We just mention that all figures of maps, graphs, etc. reported in the chapter about field validation are screenshots of the GREAT client application.According to the project schedule, fourteen GREAT GNSS receiver prototypes were assembled and used in a series of laboratory and field tests. Lab tests are aimed at assessing the hardware performance in a controlled environment, in terms of tracking capabilities, GNSS data quality and spoofing/jamming detection. On the other hand, field tests aimed at demonstrating the actual feasibility of using the GREAT GNSS receivers for the implementation of a network of permanent stations. For this reason, two networks of GREAT receivers have been installed in the Île-de-France (France) and Wallonia (Belgium) regions in April 2023. In this chapter we describe the setups realized in the two testbeds. Chapter 5 summarizes the most important achieved results.A network of four GREAT receivers has been installed in the Île-de-France region in France, in the locations listed in The installation setup is identical for each site. A dedicated task of the project was aimed at selecting the most suitable antenna for the GNSS reference station implementation. A Tallysman VSP6337L  has beenhttps://rgp.ign.fr/STATIONS/#chdy, accessed on 28 June 2023). The consortium is aware that such a monumentation solution does not meet the strict IGS Monumentation Design and Implementation Recommendations ; anyway, we considered relevant for the purpose of the project  to investigate the possibility to exploit this kind of monumentation type and to quantify the achievable performance in terms of antenna stability and quality of the generated GNSS data. This solution has the advantage of being extremely low-budget, quick and easy to install. In detail, the structure used for the monumentation consisted in:-a roof pallet with a steel structure, 1 m mast with 60 mm diameter, two force arms to support the mast on the steel structure and serrated jaws. The structure has been custom built for Teria by a local manufacturer.-six concrete slabs.-two triangular plates with three screws to ensure the levelling of the antenna.-two horizontal steel racks to support the cabinet on the mast.The antenna is monumented to the ground using a “roof pallet” structure, a solution already exploited by Teria (part of the GREAT consortium and responsible for the field tests) in its operational installations of permanent GNSS stations  coaxial cable.The GREAT receivers are hosted inside the buildings and they are powered directly by the 220 V AC grid with a standard grade AC/DC converter. Such setup allows to measure possible issues on the acquired GNSS data that can be caused by ripples and disturbances of the power supply.Similarly to the testbed in France, the network is completed by three external higher-order reference stations, part of the EUREF network and used for the computation of the precise coordinates of the GREAT stations. Details about such external stations are available in The aim of the field validation is to assess the performance of the entire system  in terms of continuous station operation and of achieved GNSS data quality. It must be noted that, at the time of writing this document, only preliminary results can be reported, given that the hardware has been installed only for a few months and a complete assessment of the system should require at least one year of continuous operation, in order to detect all possible long-term issues or misbehaviors.Nevertheless, in this paper we would like to present an assessment methodology which will be extended to a longer period. In detail, the following key performance indicators (KPIs) are considered to quantify the performance of the system.-Number of gaps in real-time data transmission with duration longer than 120 s.-Average and maximum length of data gaps.-Minimum battery voltage.-Average and minimum cellular signal strength (as recorded by the embedded LTE modem).KPIs related to the station operation continuity:-Average and minimum percentage of acquired/expected epochs computed on hourly basis.-Average and minimum percentage of acquired/expected observables computed on hourly basis and for each frequency of each satellite system.-Average and maximum percentage of cycle slips computed on hourly basis, for each frequency of each satellite system.-Average and maximum multipath on code-pseudo-ranges computed on hourly basis, for each frequency and satellite system.-Average and minimum C/N0 computed on hourly basis, for each frequency of each satellite system.-Root mean square (RMS) of the daily 3D displacements of the station computed with the network adjustment process described in KPIs related to the GNSS data quality:GNSS data acquisition at 1 Hz  and their remote real-time transmission to the processing server using the internal LTE modem .GNSS data acquisition disabled with LTE module powered on (idle mode).GREAT mode with disabled remote transmission (LTE module powered off).Idle mode with the LTE module powered off.Moreover, we have tested the hardware prototype power consumption in the following operating conditions:-The maximum current found multiplied by the maximum voltage.-The maximum current found multiplied by the minimum voltage.-The minimum current found multiplied by the maximum voltage.-The minimum current found multiplied by the minimum voltage.and using the following KPIs: A specific device has been set up to automatically detect the maximum and minimum current consumed within ten minutes, whilst, for voltage, an AVOmeter has been used and the maximum and the minimum voltage has been found by inspection methodology. This section summarizes the results achieved in the experimentation at the two testbeds in France and Belgium, in terms of the KPIs listed in For what concerns the GNSS data quality, the following The following The previous For what concerns the test of the hardware power consumption, as expected the functioning modes a–d described at the end of -Telemetry data acquired in the first month after installation demonstrate that all stations were able to work with a high degree of continuity: on average, the stations transmitted data for more than 96.5% of the time (worse case of VIT200FRA) and there was only a reduced number of interruptions: apart from VIT200FRA, the other five stations had an average interruption less than 2 min and the number of interruptions per day longer than 2 min is limited to less than one, on average. In all cases, the maximum interruption time is less than 30 min. This evidence proves that there is no interference of GNSS toward the LTE module, which is mounted on the same electronic board. Moreover, the choice of using an omni-directional LTE antenna placed inside the protective cabinets guaranteed enough signal strength to avoid relevant interruptions in data transmission.-For what concerns the power supply subsystem based on photovoltaic panels and backup batteries (in the first testbed), the minimum measured value of the battery voltage (12.23 Volts measured by STC200FRA) proves that it is correctly dimensioned given the device power consumption and the installation site.By analyzing the results achieved in the two testbeds in terms of telemetry  or electromagnetic or physical disturbances in the environment near the installation site (both factors affecting the continuous tracking of the satellite). This is not the case in both test sites, featuring different power supply subsystems (photovoltaic panels in France and AC/DC converters in Belgium). Moreover, this result demonstrates that the LTE modem  does not interfere with the GNSS receiver.-The average C/N0 is always higher than 39.5 dBHz and commonly higher than 43 dBHz: this is proof of the correct functioning of the GNSS antenna and of the adequacy of the selected coaxial cables.-Finally, the detected multipath is acceptable on all sites , which is proof of the suitability of the environment near the selected installation sites. Moreover, the low multipath detected over long periods of time and on all tracked frequencies is proof of the adequate performance of the selected antenna models, despite their low-cost. In general, the comparison between the results achieved with the two antenna models exploited in the two testbeds, with identical receivers points out that, even with a very low-cost GNSS antenna like the ArduSimple ANT3B-CAL, the quality of the results is good and comparable with the one of a medium range antenna like the Tallysman VSP-6337L.-Data reported in For what concerns the performance of the system in terms of GNSS data quality, we can underline the following:The third aspect that was investigated in this field validation is the repeatability of the displacement measures  plus a software component, which implements real-time data acquisition, quality and integrity checks, storage and real-time transmission of the received raw GNSS data to external software used to provide RTCM corrections to the users. The prototypes developed during the project were used to realize two networks installed in France and Belgium, with the objective of quantifying the performance of the entire system, composed by GNSS receiver, cost-effective multi-frequency antenna and low budget monumentation solutions. One of the tasks of the project was to understand if alternative  monumentation solutions are suitable for a certain range of applications and in particular for the densification of existing geodetic networks. The performance of the custom developed acquisition and processing software tool was assessed too.Even if the consortium is aware that an exhaustive assessment of the system will require at least one year of continuous functioning in operational conditions , the results achieved in the field validation (from April to May 2023), as summarized in the previous section, can allow to draw the first relevant conclusions.The field validation will continue in the coming months in order to investigate elements such as the power supply adequacy during the winter period at relatively high latitudes and the long-term repeatability of the measures  as the reliability of the data transmission means.In particular, it is important to note that the GREAT stations installed in the French testbed are co-located with existing reference stations part of a commercial network. Such stations are realized with geodetic-grade instrumentation, monumentation compliant with the IGS standards and their data are processed with state-of-the-art software tools, such as Bernese. In this scenario, we foresee to realize a “long-term” comparison between the results achieved with the GREAT system and a benchmark, aimed at assessing the achieved performance in the same environmental conditions.


The traditional eight arts include film and dance. Dance is often included in the creation of films. With the progress of the times, dance has shown unprecedented vitality in film. This also puts forward higher requirements for shooting technology in film creation. To solve the contradiction between high performance of equipment and energy sensing, a new energy aware scheduling framework is proposed based on Cyber Physical System, which utilizes the balance between performance and energy consumption optimization, and uses allocation technology and list scheduling to ensure energy constraints. Besides, a highly energy-efficient and stable scheduling algorithm for film creation is constructed. The algorithm problems are mainly divided into functional safety requirements, verification problems, and energy consumption optimization problems under functional safety. The experimental results show that the system can obtain better schedulability at a lower time complexity and reasonably reflect the dynamic and static energy constraints ratio. The basic framework system based on dynamic step size also achieves better time performance than other step sizes. According to the experiment’s findings, the energy consumption of all scheduling components is relatively low and can be maintained within a specific range. The research and analysis of this study can provide a theoretical reference for the equipment algorithm of film dance creation practice, promote interaction with technical practice, and assist in promoting the development process of film dance creation. The most memorable achievements of the transformation and evolution of modern human civilization are found in works of art . Since mBased on the above background, aiming at the contradiction between equipment high performance and energy awareness, this study studies the film creation scheduling algorithm with high stability and high efficiency. Firstly, the CPS is introduced. Secondly, the safety requirements verification and energy optimization problems under functional safety conditions are modeled and analyzed. A new energy aware scheduling (EAS) framework is innovatively proposed for energy constraints. Finally, the schedulability and time performance are experimentally analyzed. The study is divided into the following parts. Section 1 is the introduction, which introduces the background, purpose, and significance of this study; Section 2 is related work, through the review of other related studies, summarizes the deficiencies in the current research, and leads to the main problems and innovation points of this study; Section 3 is materials and methods. The relevant theories of CPS are expounded, the energy consumption of the algorithm is optimized, and a new EAS framework is proposed to ensure energy constraint. Section 4 is the results and discussion. The results of the study are presented and explored in sections. The conclusions are summarized and compared with other similar studies to compare the similarities and differences between this study and other studies. Section 5 is the conclusion, which summarizes the main contributions and conclusions, and points out the shortcomings of the study and the prospects for the future.In recent years, low-energy parallel scheduling algorithms have also become the main research point. Maghsoud et al. (2021) considered the energy-delay product as a trade-off between energy savings and performance improvement. They proposed a technique for performing work-stealing scheduling in the operating system kernel without modifying user-space programs. The proposed scheduling used a predictive model to determine the optimal number of active cores and clock frequency of the processor as the optimal configuration for any running program at runtime to achieve the minimum energy-delay product value . Lu et aThe above study is either from the operating system kernel, from the energy and cost factors, or from the perspective of dynamic voltage and frequency, to reduce energy consumption and improve performance. These studies focused on balancing energy consumption and performance by building different systems, but did not ensure energy constraints through the EAS framework. As such, based on the CPS, the safety requirement verification problem and energy consumption optimization problem under functional safety are studied and modeled, and a new energy constraint evolution algorithm framework is innovatively put forward.The energy consumption of embedded systems is mainly due to processors, memory, interface network cards, and external circuit systems. The processor’s energy consumption is the most concerning part of the low-energy scheduling field . At presCurrently, the main challenges in applying CPS to the creative practice of film dance are the system’s real-time, robustness, safety, and energy consumption. It is necessary to solve the problems of functional safety requirement verification and energy consumption optimization under functional safety to implement a highly stable and energy-efficient scheduling algorithm in CPS. Functional safety requirements verification is primarily for transient and permanent hardware failures . TransieIn 1, Task2, Task3, Task4, Task5, and Task6 represent the tasks of the application. The dashed line on the right represents the resulting response time of t1. The solid line on the right represents the response time requirement of the application with t2. When the response time of the egress task is less than or equal to the response time requirement of the application, the entire end-to-end node from the egress task to the ingress task can be redistributed, thereby maximizing the reliability of the application [lication , as demo6 and n5. If the actual reliability value obtained is greater than or equal to the reliability requirement when the reliability requirement provided to the application is known, the functional safety requirement verification is satisfied. Otherwise, it will not be passed, and the process will be closed. In this way, the application’s response time requirements are converted to each task’s response time requirements. The SIL decomposition scheme with the largest reliability value is selected in multiple schemes for each task, thereby enhancing the reliability of the application and ensuring its functional safety requirements [As outlined in irements .The pre-allocation technology ensures the SIL decomposition scheme for all tasks in the current application. Maximum reliability can be achieved under the premise of ensuring the response time requirements of the application. Based on this, the system energy consumption is optimized. The main way is to optimize the SIL scheme for each task in the pre-allocation phase, thereby reducing the energy consumption of the system application . The spe5 in the figure determines the current task’s response time and reliability requirements and assigns the various solutions obtained. The final practical application’s reliability, response time, and energy consumption are calculated. Next, the priority sequence is performed. Finally, the lowest energy consumption of all SIL decomposition schemes is chosen to meet functional safety requirements [5, and the SIL decomposition scheme with the lowest energy consumption is selected.irements . The resAfter solving the above problems, the problem of low-energy parallel scheduling in the filming equipment for film and dance creation is analyzed. The essence is to optimize the response time of the joint constraint of dynamic and static energy under uncontrollable static energy consumption . TherefoThe new EAS framework process is divided into four parts in The operating system used in this study is Windows10 64-bit system, the Central processing unit (CPU) is Intel(R)Core(TM)i7-7700, the CPU frequency is 3.60GHz, the memory is 16GB, and the core is 16GB. The graphics card is NVIDIA GeForce GTX 1080 x 4, and the storage disk is 5.2TB with 8GB of video memory.Here, the schedulability and time performance of the basic framework are used as the selection criteria for the optimal step size of each scheduling component. The Fast Fourier Transform (FFT) and Gaussian elimination structure are applied. The instance count of all output steps based on schedulability is demonstrated in In Experiments and analyses of time performance are performed. The total energy constraint is set to a fixed 0.5× actual total energy consumption in all 1,000 experiments. The step size of a basic framework instance that achieves the minimum response time is output. After 1000 repeats, the counting results for all output steps are recorded, as illustrated in The theoretical energy consumption analysis is carried out on the simulation platform. The theoretical energy consumption results of the application of the FFT structure under the change of task number are shown in The two dashed lines in In conclusion, the proposed film creation scheduling algorithm based on CPS with high stability and energy efficiency has better time performance and energy consumption constraints. Additionally, it was compared with other similar studies. Qin et al. (2020) proposed an energy-aware multi-objective reinforcement learning (RL) algorithm based on the RL of the Chebyshev function, and compared the proposed algorithm with two state-of-the-art multi-objective meta-heuristic methods for four different workflows. The results indicated that their proposed algorithm was superior to these existing methods . CompareInnovation is the core driving force of social development. Cross-border cooperation in artistic innovation is the most common way of creative innovation. This study addresses the conflicting problem of high performance and energy awareness of equipment in film and dance creation. Firstly, the high-efficiency functional safety issues in the CPS are explored. Secondly, the verification analysis of functional safety requirements and the optimization of energy consumption to meet functional safety requirements are carried out. Finally, a low-energy parallel scheduling algorithm for industrial equipment is proposed. A four-stage integrated process and design ensure that its basic framework guarantees dynamic and static energy constraints for parallel applications. From the experimental results of the framework optimization and simulation platform, the scheduling algorithm has advantages in optimizing energy consumption. It can shorten the development life cycle of CPS parallel applications. From an industrial point of view, the proposed energy-efficient functional safety scheduling algorithm has practical significance for the energy-sensitive and environmentally-friendly film industry. However, this study only conducts experimental analysis on the simulation platform and does not apply the proposed algorithm to film equipment. Moreover, the analysis of the algorithm is not deep enough. Therefore, in the future, it is necessary to deeply combine the research results with the actual equipment system with a complex hardware environment and customize appropriate optimization algorithms according to each hardware feature. Besides, advanced algorithms such as machine learning should be introduced to break through the optimization bottleneck of the CPS. Thus, the advantages of film and dance can be combined to create works of art that conform to the aesthetics of modern society.


This article not only tested the feasibility of a “self-powered” cardiac pacemaker but also brings hope for the future of next-generation pacemakers, which could potentially co-exist with the patients. The major benefits of this new technology are that we can potentially reduce the size of current generators and there is no need to replace the generator at the end of battery life.Since the first electronic pacemaker was implanted in human in 1958, electronic pacemakers have undergone continuous refinement including miniaturization of the devices all the way to a standalone leadless pacemaker capable of right ventricular pacing ,3. Despiet al. tested the feasibility of durable symbiotic pacemaker in a porcine model of sinus node dysfunction. The symbiotic cardiac pacemaker consists of three units: energy harvest unit, power management unit, and pacemaker unit. The triboelectric nanogenerator has many advantages: flexibility, biocompatibility, implantability and light weight. Superior energy output, biocompatibility and stability are the vital characteristic of the energy harvester. The energy harvested by the unit from cardiac motion was stored in a capacitor to drive the pacemaker. In the present work, the authors used adult male Yorkshire porcines and created transient sinus node dysfunction by hypothermia. The implanted symbiotic pacemaker succeeded in correcting sinus bradycardia by pacing the animals when needed. The premise behind the successful experiments of the authors was that the energy harvested from each cardiac motion (0.495 μJ) was greater than that required for endocardial pacing threshold (0.377 μJ). This interesting technology has the potential to apply to many medical devices (other than cardiac pacemakers) such as implantable cardiac defibrillators, deep brain stimulators, etc. This new technique provides a promising method to harvest, store, and discharge energy to pace the heart with the advantages of a wide choice of materials, high output, flexibility, and decreased size of the generator.By using a nanogenerator, which can harvest the native energy generated by cardiac motion, Ouyang A couple of important issues should merit further clarification. First of all, although this technique is promising, it has limited applicability to pacemaker-dependent patients. If the patient is 100% pacemaker dependent, since the generator can only save a portion of the energy generated (limited by the capacitor), the pacemaker will not be able to store enough energy to pace the patient for the rest of his/her life. Also, pacemakers need additional energy to analyze the underlying rhythm, check sensitivity and change pacing thresholds as well as sending data to the remote monitoring systems. All of these functions will increase energy consumption and it is unclear how much more energy will be required to keep up with functionality of current pacemakers. Second, because of the concern that the nanogenerator does not harvest enough energy to pace, the pacemaker may need a back-up battery to store energy. This can increase the size of the generator, which can potentially increase complications and limit the benefit of this technology. Third, this new technique still does not protect electronic pacemakers from infectious complications and lack of autonomic nervous system response, issues that could only be solved if a biological pacemaker  ever advances to the clinic. Lastly, the main benefit of this technology is limited to avoiding multiple generator changes. As battery technologies continue to advance, battery life will likely extend and most patients may not require frequent generator changes. The concept of self-powered pacemaker is novel but with the current prototypes the advantages are marginal.Nevertheless, the concept of a self-powered pacemaker represents an important advance in device technology, and the electrophysiology community (and our patients) look forward to using our own energy to keep the pace.


Reinforcement learning (RL) methods for energy saving and greening have recently appeared in the field of autonomous driving. In inter-vehicle communication (IVC), a feasible and increasingly popular research direction of RL is to obtain the optimal action decision of agents in a special environment. This paper presents the application of reinforcement learning in the vehicle communication simulation framework (Veins). In this research, we explore the application of reinforcement learning algorithms in a green cooperative adaptive cruise control (CACC) platoon. Our aim is to train member vehicles to react appropriately in the event of a severe collision involving the leading vehicle. We seek to reduce collision damage and optimize energy consumption by encouraging behavior that conforms to the platoon’s environmentally friendly aim. Our study provides insight into the potential benefits of using reinforcement learning algorithms to improve the safety and efficiency of CACC platoons while promoting sustainable transportation. The policy gradient algorithm used in this paper has good convergence in the calculation of the minimum energy consumption problem and the optimal solution of vehicle behavior. In terms of energy consumption metrics, the policy gradient algorithm is used first in the IVC field for training the proposed platoon problem. It is a feasible training decision-planning algorithm for solving the minimization of energy consumption caused by decision making in platoon avoidance behavior. The aim of green autonomous driving is to enable a vehicle to navigate and make decisions based on its surroundings without human intervention while adhering to environmental protection standards. A critical component of achieving this goal is developing driving strategies that can automatically output control signals such as steering, throttle, and brake in response to the observed environment. The behavioral decision-making methods of automatic driving are divided into traditional methods and reinforcement learning methods. Traditionally, the decision control software system of an automatic driving system includes environmental prediction, behavior decision, action planning, path planning, and other functional modules. Traditional methods are often rule-based state control algorithms, including fuzzy logic , PID BayVeins  is an opThe connection established by Max Schettler between Veins tools and reinforcement learning by coupling Veins with OpenAI Gym provides a bridge for researchers who possess expertise in either field to leverage their knowledge in the other. This interface enables VANET researchers to access a compatible platform based on the generic RL framework . Researc2 emissions is extensive and encompasses a wide range of studies , where x and v denote the distance and speed, respectively, and the labels 1, 2, and 3 denote the physical quantities with the car in front, the car behind, and the car in front of the next lane, respectively. The behavior space comprises , and their elements are Boolean values.The fleet collision loss function is utilized to consider the environment space key points. The reward in the next moment within the current lane is dependent on the state space, where any behavior The convergent process of each loss function value in the whole training process is compared under different learning and exploration rates. The energy loss function and the collision loss function are slightly different. The two are not strongly correlated. When the energy loss is low, the collision loss may be larger; sometimes, the opposite result is produced. The selection of super parameters is extremely important. The training system is chaotic, and any small change in the parameter value leads to great changes in the convergence characteristics, even in the non-convergence situation. The value of the learning rate parameter used for the constraint training convergence curve is set to . The exploration rate parameters used to explore more decisions have values of .Considering the complexity of the scenario, it is reasonable to assume that there is no need to dynamically adjust the learning rate. In the simulation scenarios and algorithm models of Veins-Gym, the vehicle under test continuously tests and trains the deep neural network. Sensor-based vehicle distance decision algorithms need no training. The decision of CACC is determined by the headway, min-Gap (the distance between the front bumper and the rear bumper of the vehicle in the queue), and the reaction time τ. The optimal headway = 1.5 s, min-Gap = 2.5 m, and τ = 1 s are adopted. Comparing the traditional algorithm with the proposed algorithm, the following is obtained.In one thousand training sessions, a target vehicle exhibits a pattern of both overall convergence and local oscillation in the collision loss generated by the fleet and the reward value it receives. The proposed method differs from the traditional approach in that lane changes occur between vehicles instead of all vehicles changing lanes. The loss convergence process of the agent, which is highly correlated with the reward function, can be evaluated using multiple metrics. When evaluating a single intelligent entity, the most crucial factor to consider is the trend of collision loss and reward value changes.There is no strong correlation between energy loss and collision loss, which is particularly obvious in the traditional algorithm; that is, all CACCs of the team members may adopt the same lane change strategy at the same time, which makes the decision without safety significance and increases energy consumption. According to the In the three-lane experiment, the parameters and the design of the model were different compared to those for the two-lane experiment. According to The operation loss parameter of the reward function is set to a larger value, that is, the reward value is more affected by the operation loss. The vehicle trajectories over a period of time are shown in the Examining the relationship between the sequence of fleet members and important physical quantities over time is of great interest. Even though vehicles make many steering movements during high-speed driving, the results of experiments conducted in a reinforcement learning agent simulation environment are worth investigating. Even if the directional change resulting from this movement is very small, typically less than 10 degrees, it can have catastrophic consequences. For instance, in rainy or snowy weather, the friction between the tire and the ground in the vertical direction to the direction of travel can cause rolling friction which transforms into sliding friction. Once this occurs, the vehicle’s state becomes uncontrollable, leading to serious traffic accidents. In this three-lane experiment, the behavior of each member is intrinsically linked to the entire system. Due to communication delay and uncontrollable hardware control random delay, the behavior of each vehicle has a reasonable lag and delay in response to the previous vehicle’s actions.The function that describes the change in the minimum distance between a vehicle and its leading vehicle as a function of time is always monotonically decreasing, but for vehicles with different indices, the curves exhibit reasonable differences. In general, vehicles with higher indices exhibit greater negative acceleration, i.e., they tend to maintain a greater distance from their leading vehicle. Acceleration, as the second derivative of distance, must have a sufficiently large integral to increase the distance between vehicles; therefore, the acceleration of rear vehicles must be larger and initiated earlier to obtain a larger reward for the agent. To increase the distance between vehicles under loose conditions, vehicles can gain greater distance by making free turns and agents will do whatever it takes, including changing lanes continuously, to achieve this goal. When the vehicle that continuously changes lanes reaches the front of the road and no longer detects a leading vehicle, it is not motivated to change lanes or decelerate. Although the vehicle in this situation should accelerate and overtake surrounding vehicles to leave the accident area as quickly as possible, the simulation environment does not have parameters or behaviors that are less related to obstacle avoidance, minimal energy loss, and minimal safety cost. Therefore, the acceleration of the vehicle is always non-positive, sometimes negative, and sometimes zero.In this paper, we propose a policy gradient algorithm for computing the minimum energy consumption for autonomous driving decisions in the context of a green economy. The approach utilizes the Veins-Gym reinforcement learning and the Telematics training platform. Two experiments were designed to train the proposed algorithm for obstacle avoidance strategies in two-lane and three-lane highway situations when the team’s lead vehicle is involved in a major traffic accident. By training the optimal decision, the vehicles perform better in terms of obstacle avoidance and energy loss performance and achieve minimized cost loss. Due to different parameter settings, the vehicles’ obstacle avoidance strategy can be switched between conservative and aggressive operations. In the future deployment of a large number of self-driving vehicles, reinforcement learning has great promise for some decisions, such as environmental prediction and behavioral decisions. This study used short-range communication networks only for small-scale vehicle communication, and when more vehicles and more network types (such as base stations) are added, how reinforcement learning can cope with them should be specifically analyzed.When the road environment is more complex, reinforcement learning intelligences should be multi-agents and consideration should be given to whether to use distributed or centralized agents.The crash environment in this study is only one of many small probability situations; a more generalized decision algorithm should be sought to minimize loss.There is endogeneity in the road passage, traffic calming methods, and crash behavior decisions, and their correlation should be studied.Future research should address the following:


Great earthquakes are one of the major threats to modern society due to their great destructive power and unpredictability. The maximum credible earthquake (MCE) for a specific fault, i.e., the largest magnitude earthquake that may occur there, has numerous potential scenarios with different source processes, making the future seismic hazard highly uncertain. We propose a full-scenario analysis method to evaluate the MCE hazards with deterministic broadband simulations of numerous scenarios. The full-scenario analysis is achieved by considering all uncertainties of potential future earthquakes with sufficient scenarios. Here we show an application of this method in the seismic hazard analysis for the Xiluodu dam in China by simulating 22,000,000 MCE scenarios in 0–10 Hz. The proposed method can provide arbitrary intensity measures, ground-motion time series, and spatial ground-motion fields for all hazard levels, which enables more realistic and accurate MCE hazard evaluations, and thus has great application potential in earthquake engineering. Deterministic numerical simulations are employed to study the maximum credible earthquake hazard for a specific fault. The method is then applied for seismic hazard analysis at the Xiluodu dam in China, and its potential for earthquake engineering is evaluated. Great earthquakes occurring near urban areas or major projects like nuclear power stations or high dams can lead to catastrophic damage, such as the 1906 Mw 7.9 San Francisco Earthquake2 and the 2008 Mw 7.9 Wenchuan earthquake3. However, the earthquake hazards are not determined by their magnitude alone, and moderate earthquakes may also cause severe disasters under specific circumstances, e.g., the 1994 Mw 6.7 Northridge earthquake4 and the 2014 Mw 6.2 Ludian earthquake5. How to evaluate the seismic hazard for specific sites accurately is still an essential issue for disaster risk reduction1. In the past few decades, seismic hazard analysis methods based on the empirical ground-motion prediction equations (GMPEs), e.g., probabilistic seismic hazard analysis (PSHA) or deterministic seismic hazard analysis (DSHA), have been widely used in the design of major projects and the planning of land-use for the aim of seismic risk mitigation7. However, the empirical GMPEs are usually constrained by the lack of proper ground-motion records, especially the near-fault records from large earthquakes. They cannot accurately account for the complex rupture process and specific site conditions either8, and their estimates of seismic hazard may have an unexpected upward bias9. Additionally, performance-based seismic design and analysis require ground-motion time series10, but the empirical GMPEs can only give estimates of the ground-motion intensity measures (IMs).Earthquakes are one of the major natural hazards that threaten human society due to their severely destructive nature and the occurrence of uncertainty in both time and space14. Compared with the empirical GMPEs that are widely used in the traditional seismic hazard analysis methods, physics-based ground-motion simulation methods can comprehensively consider the source mechanism, the propagation path, and the effect of local conditions and thus have vast application prospects in the field of earthquake engineering. Recently, several physics-based seismic hazard analysis approaches have been developed using deterministic ground-motion prediction methods and show great potential to accurately evaluate the seismic hazard17. However, those physics-based seismic hazard analysis approaches are usually constrained in the low-frequency range. In fact, high-frequency ground motions are of great importance in the seismic design of engineering structures. Moreover, the complex physical process of earthquakes is not comprehensively taken into account in these methods for two reasons. First, the number of considered earthquake scenarios in these methods is too small compared to the hundreds of thousands of variables in kinematic source models for generating broadband ground motions. Second, the kinematic parameters of the source process, including the fault location, the hypocenter, and the distribution of slip, rupture time, rise time, and rake, are not fully taken into account in these methods. Therefore, the obtained seismic hazard results may not adequately reflect the hazard of potential earthquakes that may attack the target site in the future.Deterministic broadband ground-motion simulations have been validated by the records of historical earthquakes and the well-recognized empirical ground-motion prediction models18. Since there may be several significant active faults with different upper magnitude limits in the vicinity, the target site may have multiple MCEs. Due to the complexity and computational cost of implementation, the proposed method is more suitable for evaluating the seismic hazard of major engineering projects subject to extreme earthquakes occurring in the near field of the target site. Given that the seismic design of major engineering projects, such as high dams and nuclear power plants, particularly emphasizes their safety under extreme seismic conditions, the proposed method is currently intended for evaluating the seismic hazard of major engineering projects under MCEs. The MCE hazards, i.e., the hazards for the target site caused by the largest magnitude earthquakes at all considered active faults, are analyzed using comprehensive MCE scenarios at the significant faults near the target site. The newly proposed multidimension source model is used to describe the complex source process of earthquake scenarios. The multidimension source model, composed of multiscale and self-similar subsources, can generate broadband ground motions while considering specific rupture processes and has been validated by the records of historical earthquakes and the empirical GMPEs19. Moreover, the variable space dimension of the seismic source is greatly lowered by applying the self-similarity feature of subsource parameters in the multidimension source model20. In this way, the full-scenario analysis for the maximum credible earthquakes can be realized by a holistic consideration of the uncertainties in all kinematic parameters of the source process with comprehensive potential earthquake scenarios. Next, broadband ground motions (0–10 Hz) of up to tens of millions of earthquake scenarios are generated using the adjoint simulation method. Finally, the seismic hazard results of the target site can be obtained by statistically analyzing the IMs of all generated ground motions. In this method, as broadband ground motions at the target site are explicitly generated for all earthquake scenarios, the seismic hazards of arbitrary IMs can be obtained, not just spectral accelerations. Therefore, for specific major engineering structures, the proposed method can provide personalized seismic hazard results by using the optimal IMs of them. Moreover, this method can give earthquake scenarios with the specified seismic hazard levels and the corresponding broadband ground motions, which can be directly used in performance-based seismic design and analysis. The spatial ground-motion field around the target site can also be generated using the earthquake scenarios, which is particularly important in the seismic design for large-span structures such as dams and bridges.In this study, we are committed to developing a full-scenario seismic hazard analysis method for the maximum credible earthquakes (MCEs) based on fully deterministic broadband ground-motion simulations. Herein, the term MCE refers to the earthquake with the largest magnitude that can reasonably be expected to be generated by a specific source on the basis of seismological and geological evidence21. Therefore, the seismic safety of this dam, especially its seismic performance subject to destructive earthquakes, e.g., MCEs, is a severe concern in the whole cycle of construction and operation.We apply this method to analyze the MCE hazard of the Xiluodu dam in China. The Xiluodu dam is located in southwest China with a height of 285.5 m, and its reservoir capacity can reach 12.67 billion cubic meters. The dam site is at the junction of the active tectonic blocks with a high seismic riskTo evaluate the seismic safety under MCEs for the Xiluodu arch dam, potential faults where MCEs may occur are identified based on the exploration results of fault structures and historical earthquakes around the target site. There are two important fault structures in the near field of the Xiluodu dam site: the Yaziba fault, with a potential magnitude limit of 7.5, and the Leibo fault, with a potential magnitude limit of 7.0 Fig. . It shou24 and the geological exploration information of the Xiluodu site, the 3D numerical model is established to simulate the ground motions. A well-recognized software package based on the spectral element method26, SPECFEM3D, is used to simulate the seismic wave propagation in the model domain. The minimum shear wave velocity at the surface of the model domain is 2000 m/s, and the shear wave velocity gradually increases to 4400 m/s at depth. To reduce the computational amount, the average spacing of the grid points at the model surface is set to 50 m, and the grid size is doubled at the depth to match the high velocity there. Considering that the spectral element method requires five points for each wavelength of seismic waves when simulating the seismic wave field27, the effective frequency of the simulated ground motions is up to 10 Hz in this study.The topography in the model domain is considered using the digital elevation model data with a resolution of 30 m. Based on the 3D wave velocity structure of East Asia EARA2014Based on the 3D numerical model, the strain Green’s tensors from the Xiluodu dam site to all possible source locations in the potential faults are calculated by three independent numerical simulations, and then the strain Green’s tensors are post-processed and stored. In the seismic hazard analysis for the Xiluodu dam site, 22,000,000 scenarios of MCE are generated for the Yaziba fault and the Leibo fault, i.e., 1,000,000 earthquake scenarios are generated for each seismic fault in the potential seismic zones. The Green’s functions of subfaults for each seismic fault are calculated using the pre-computed strain Green’s tensors. For all earthquake scenarios, the ground motions at the Xiluodu dam site are directly synthesized using the Green’s functions of subfaults. Ground-motion IMs, e.g., the spectral accelerations, for all earthquake scenarios are calculated to obtain the seismic hazard results of the target site.Additionally, it is worth emphasizing that our method is capable of incorporating all uncertainties related to potential future earthquakes. In this study, uncertainties of the fault location, hypocenter, and rupture process of earthquakes are considered in the seismic hazard evaluations for the Xiluodu dam site, while the earthquake magnitude is fixed to the maximum magnitude of surrounding faults for the consideration of MCEs, and fault dips are determined based on fault explorations. However, our method is flexible enough to incorporate other variables of earthquakes, such as earthquake magnitude and fault dip, if necessary.The exceedance probability corresponding to the IM is regarded as the seismic hazards for the target site, as presented in Fig. Mw7.5) is obviously larger than that of the Leibo fault (Mw7.0), the seismic hazard  of the Yaziba fault is comparable to that of the Leibo fault for the Xiluodu dam site. Meanwhile, the MCE hazards for the Xiluodu dam site are further analyzed with four representative IMs , root-mean-square of velocity (vRMS), Arias intensity (Ia), and cumulative absolute velocity (CAV). The four IMs at the river-parallel direction for the Yaziba seismic zone are obviously higher than those for the Leibo seismic zone, indicating that the seismic hazards represented by different IMs may have significant differences for the same site. Therefore, with the optimal IM of specific engineering structures, this study can provide personalized seismic hazards for them, enabling more accurate and reasonable evaluations of the MCE hazards.Besides, it can be found that the spectral accelerations of ground motions generated by earthquake scenarios of the Leibo fault are similar to that of the Yaziba fault at the same seismic hazard level. For instance, PGA at the exceedance probability of 50% is 0.268 g in the river-parallel direction for the Yaziba fault, while PGA at the same hazard level is 0.254 g in the river-parallel direction for the Leibo fault. It is surprising that although the MCE magnitude of the Yaziba fault  generated by forward simulations for the earthquake scenarios at the Yaziba fault and Leibo fault, as shown in Fig. 32. For comparison purposes, the seismic hazards from our study and the empirical GMPEs are obtained based on the seismic fault located in the center of the seismic zones. As shown in Fig. 33.The seismic hazards are compared with four well-recognized empirical ground-motion prediction equations (GMPEs)34.This study proposes a seismic hazard analysis method based on broadband ground-motion simulations. In this method, the rupture process of earthquakes, the propagation path, and the local site conditions are all determinately considered. Furthermore, based on the self-similar feature of the multidimension source model, MCE scenarios that may attach to the target site are fully analyzed by considering all uncertainties of potential future earthquakes. Nevertheless, the possible nonlinear effects of local sediments during strong earthquakes are not taken into account in this study. Our method may overestimate the MCE hazard to some degree due to ignoring the nonlinear material behaviorsMw7.0) is significantly less than that at the Yaziba fault (Mw7.5), earthquake scenarios at the Leibo fault can cause similar seismic risk  to the Xiluodu dam site. It is demonstrated that the seismic hazard of specific sites is closely related to the complex physical background of earthquakes, e.g., the rupture process and propagation path, and cannot be accurately evaluated by simple parameters like magnitude and epicentral distance.The proposed method is used to evaluate the seismic hazard of the Xiluodu dam in China. We find that the ground-motion intensity of earthquakes occurring at the specific fault is closely related to their physics background. IMs of ground motions generated by earthquake scenarios with the same magnitude and fault location can vary greatly for different rupture processes. Besides, although the MCE magnitude at the Leibo fault ,M0 is assigned to different layers according toRi and Rk is the subsource size for Layer i and Layer k, respectively. Besides, the kinematic parameters of subsources, including slip, rupture time, rise time, and rake, on different layers are derived from the specified rupture process. Specifically, the slip, the rupture time, and the rake of subsources on different layers are all consistent with the specified rupture process, while the rise time of subsources on different layers is scaled byj on Layer i.To evaluate the seismic hazard of MCE with deterministic broadband ground-motion simulations, the multidimension source model is adopted to consider all possible scenarios of MCE. In the multidimension source model, the rupture process on the seismic fault is described by several superimposed layers with different subsource scales to generate realistic broadband ground motions, as shown in Fig. uj, is represented asijk is the Green’s function between the site and the kth subsource on the jth subfault of the ith layer, Sijk is the source time function of the kth subsource on the jth subfault of the ith layer, and tijk, Tijk, Dijk, λijk are the rupture time, rise time, slip amount, and rake angle of the kth subsource on the jth subfault of the ith layer, respectively. uj is used as the Green’s function of the jth subfault to generate broadband ground motions of the earthquake scenario. In this way, the number of variables to be considered is significantly reduced, and then the Monte Carlo method is used to generate the scenario sets of MCE by considering all kinematic parameters of the source process.To realize full-scenario analysis of MCE, the dimension of variable space of the source process is reduced by applying the self-similar feature of the multidimension source model so that scenarios of MCE can be comprehensively considered with the Monte Carlo method. Specifically, as the kinematic parameters of subsources on different layers of the same area, i.e., the subfault, as shown in Fig. 35, and the average rise time is specified according to the empirical relation for the rise time36. According to the existing research, the hypocenter of an earthquake may occur at any position of the seismic fault38. However, due to the very limited number of earthquakes with accurate fault information derived from sufficient studies, as well as the significant randomness of the hypocenter locations, there is no well-recognized conclusion regarding the spatial pattern of epicenters. Therefore, in this study, we simply assume that the hypocenters of earthquake scenarios occur randomly at any position of the seismic fault. Furthermore, it is worth emphasizing that our method is highly adaptable and can be updated to incorporate advancements in the understanding of earthquake nature, such as improved scaling laws for rupture parameters, as well as refined exploration information of faults and regional Earth model. By incorporating these advancements, our method can yield more accurate evaluations of the seismic hazard at the target site. Details of source parameters of the generated earthquake scenarios are provided in the Supplementary Information.In this study, to generate the earthquake scenarios with the Monte Carlo method, all kinematic parameters of the source process  are randomly generated in certain ranges with necessary constraints. For the source process of earthquake scenarios with, the average slip and rise time are constrained. Specifically, the average slip is determined by the empirical earthquake source-scaling laws41. The adjoint methods can generate all needed strain Green’s tensors with only three numerical simulations. The Green’s function of the subfault uj is then obtained by convoluting with the pre-obtained strain Green’s tensors with the rupture process of all layers of the subfault. Once completed, broadband ground motions at the target site of all considered earthquake scenarios can be easily and quickly synthesized with the Green’s functions of subfaults. Broadband ground motions of the MCE scenarios are then statistically analyzed to get the seismic hazards of the target site. By convention, the seismic hazards are presented using the exceedance probability curves of the spectral accelerations. However, as broadband ground motions are explicitly obtained for all considered earthquake scenarios, any IM can be adopted for the seismic hazard analysis in our method.After the scenario sets of MCE that may attack the target site are generated, broadband ground motions of these earthquake scenarios at the target site are used to evaluate the seismic hazard there. To solve the expensive computation of simulating many earthquakes, we obtain the ground motions of all earthquake scenarios using the adjoint method by applying the reciprocity of the strain Green’s tensorsOur seismic hazard analysis method starts with some basic seismic information, including the historical earthquakes and the fault structures near the target site, which are used to determine the magnitude and the potential seismic zones of the maximum credible earthquakes. Based on the specified magnitude and the potential seismic zones, the scenario sets of MCE are generated with the Monte Carlo method by considering all kinematic parameters of the rupture process, e.g., the hypocenter, the distribution of slip, rupture time, rise time, and rake on the seismic fault. After the Green’s functions of subfaults of the multidimension source model are obtained with the pre-computed strain Green’s tensors, broadband ground motions at the target site are directly synthesized for all earthquake scenarios. Finally, the seismic hazards are obtained by statistically analyzing the broadband ground motions of all scenarios of MCE.Supplementary InformationPeer Review File


Since the fourth industrial revolution, intelligent software and applications that attempt to mimic human behavior have become increasingly common. The chatbot is an example of an artificial intelligence-based computer program that simulates human behavior by having a conversation and interacting with users using natural language. The implementation of chatbot technology in the educational context is still in its nascent stage, and further investigation into measuring its effectiveness in supporting learning and teaching processes is required, particularly in the context of higher education. Thus, this study presents the design and implementation of a task-oriented chatbot, that is embedded into the WhatsApp application, called Bashayer. It aims at supporting postgraduate students' motivation and learning strategies in Saudi Arabia. A quasi-experimental design with a single-subject experimental approach was adopted with a sample of 60 Saudi postgraduate students. The descriptive analysis of the collected data showed promising results of postgraduate students utilized the Bashayer chatbot system. Participants in the experimental group that used Bashayer were more motivated to learn than those in the control group. Participants also practiced more cognitive and metacognitive learning strategies while utilizing the chatbot compared to the control group. The results of this study are encouraging for the development of chatbot systems similar to Bashayer to support postgraduate students' successful learning. These results contribute to bridging the research gap and adding to the literature on chatbots use in postgraduate educational contexts. The use of artificial intelligence (AI) technologies in the educational context is increasing. Chatbot technology is an AI application promoted to improve teaching and learning practices  and learning strategies (cognitive and metacognitive self-regulation). These results will contribute to bridging the research gap and adding to the pool of existing literature on chatbot use among postgraduate students. These findings will shed light on the potential of such intelligent tools in increasing learners' motivation and facilitating the practice of learning strategies both cognitively and metacognitively.Chatbots rely on a variety of frameworks that govern their operations. For example, chatbots developed by Microsoft differ from those developed by Facebook Manaswi, . AlthougHwang and Chang  identifiIn the current study, the proposed Bashayer chatbot system employs the retrieval model to provide increased flexibility and support in the educational services it provides to postgraduate students. It is also a task-oriented chatbot built to attain a set of learning goals through interactions with postgraduate students in their courses.Chatbots integration into e-learning environments over the past decade reflects an increasing interest in their utility in teaching–learning modalities  and female (N = 55) students was selected. The participants' ages ranged from 21 to 30 years, and all were enrolled in the first semester of the 2022–2023 academic year. For the purpose of this study, the sample was divided into 10 postgraduate students in the pilot study, 30 postgraduate students in the experimental group (who were taught via online mode using the Bashayer chatbot system), and 30 postgraduate students in the control group . The participants had to provide informed consent to participate in this study and submit responses to the questionnaires, which ensured their voluntary participation, privacy, and data confidentiality. All their information was used for scientific research purposes only.The study sample consisted of male and female Saudi postgraduate students enrolled in the Master of Educational Technologies program at the College of Education at King Faisal University. Participants were enrolled in two courses: Reading in Educational Technologies in English Language and Dissertation. A purposeful random sample of 70 male  was utilized  completed the MLSQ survey questionnaire as a pre-test. Once the application of the Bashayer chatbot system with the experimental group ended at week 13, its participants completed the post-test.To conduct the current study, approval was obtained from the Scientific Research Ethics Committee at King Faisal University under the number KFU-REC-2022-SEP-ETHICS184. To implement the Bashayer chatbot in two master's degree courses, the researchers developed an integrated teaching plan and review for each course. Then, the weekly lesson plans were disseminated at the beginning of semester one of the academic year 2022–2023. An integrated assessment plan was also developed, including weekly assignments and final projects. To assess the homogeneity between the two sample groups, at the beginning of the course, all participants . Then, all assignments were provided to students in the experimental group as external links to the Blackboard, due to the limited download space provided by the Freshdesk free version that was used for the experimental group. When students clicked the assignment's external link, it downloaded directly without displaying the Blackboard environment. Therefore, students interacted only with the chatbot learning environment. Students then uploaded their responses to the chatbot, which was stored on the Freshdesk platform. Managing the process of learning for the experimental group was done in isolation from the Blackboard environment.The eighth function was the “submit assignment” function. Postgraduate students could upload their assignments for the teachers to review and evaluate through Freshdesk. This made it possible for instructors to display the list of students who completed their weekly duties and the means of communication by which they chose to receive feedback. Ninth was the “schedule online test” function. The students were given the opportunity to choose appropriate dates and times to hold midterm exams from several available days through Bashayer. Tenth was the “download completion certificate” function. This allowed the students to download the course-completion certificate after taking the final exam. Eleventh was the “cancel course subscription” function. The postgraduate students were given the opportunity to cancel their course registration within the first 2 weeks of the first term.Finally, if any data was entered by the students, and there was no appropriate response registered in the system database for it, the system issued the message, “Sorry, I can't fulfill your request now.” The student was then either transferred to the main menu to start again or a ticket was left for the course instructor. The instructors could log in to the Freshdesk platform at their own convenience to respond to the inquiries, as all student data was available on the platform.t-test on both groups' pre-test responses. No statistically significant difference  was found between the control group  and experimental group . This confirms the homogeneity of the study sample. Furthermore, in terms of the age variable, p > 0.05. Therefore, the two groups were homogeneous before the experiment began and follow normal distribution of data.To measure the homogeneity of the study sample, we calculated the independent samples t-test were performed to measure the statistical differences between the mean scores of the two groups. The two research questions and their associated findings are discussed below.To carry out the statistical analysis of the current study, data collected from the post-test, which was conducted after the experiment, were tabulated and entered in IBM SPSS v.26 software. The statistical analysis followed two steps. First the descriptive statistics  of the two MSLQ scales (motivation and learning strategies) and their four subscales  were calculated. Second, the independent samples The first research question is as follows: does the use of the Bashayer chatbot system enhance graduate students' learning motivation? t-test, as shown in t = 6.64, p < 0.05) and self-efficacy for learning and performance  questions of the MSLQ motivation scale , which favored the experimental group. This means that postgraduate participants in the experimental group (who used the Bashayer chatbot system) were more motivated to accomplish their learning tasks than those in the control group. These results confirm the positive effect that using the Bashayer chatbot has on postgraduate students' learning motivations.The result from the independent samples The second research question is as follows: does the use of the Bashayer chatbot system enhance graduate students' learning motivation? t-test, as shown in t = 7.18, p < 0.05) and metacognitive self-regulation learning strategies  of the MSLQ learning strategies scale . This favored the experimental group. This means that postgraduate participants using the Bashayer chatbot system and its functionalities were able to better cognitively practice learning and metacognitively regulate their learning strategies. This confirmed that Bashayer chatbot use positively influenced postgraduate participants' learning strategies.Furthermore, the result from the independent samples The focus of this study was on understanding the effect of a developed Bashayer chatbot system on learning motivation and learning strategies among postgraduate students in Saudi higher education. The study findings are discussed in the following section, and its several implications are suggested accordingly.The results of the study indicated that postgraduate students in the experimental group demonstrated higher levels of motivational orientation toward learning when using the Bashayer chatbot system than their peers in the control group. Postgraduate students' motivational orientation was assessed using two elements: task value and self-efficacy for learning and performance. In terms of task value, postgraduate students viewed their learning experience using the Bashayer chatbot system as being more motivating, meaningful, convenient, and beneficial as compared to the traditional learning environment. These results align with previous research studies on chatbot systems' potential to support learning motivation , understanding (paraphrasing and summarizing), and organizing (clustering and outlining) were enhanced by the learning environment created by the Bashayer chatbot. Despite recent studies  that simulates the instructor's personality and provides support and feedback to students. Furthermore, for future designs, the chatbot systems can include functions that analyse students' facial features, personal expressions, and communication skills and generate appropriate responses to provide a more personal learning experience. Moreover, these future design could incorporate smart strategies to classify students according to either their cognitive styles or previous experiences that are necessary for new learning.The adoption of AI-based tools, such as chatbots, to support teaching and learning has proliferated. This study's main goal was to determine the influence of a chatbot system named Bashayer on postgraduate students' learning motivation and learning strategies. A quasi-experimental design was implemented with a sample of 60 Saudi postgraduate students divided into experimental and control groups. The MSLQ survey questionnaire . The patients/participants provided their written informed consent to participate in this study.AAl-A, AAl-D, and AD contributed to conception and design of the study and implemented the experimental procedures and collected data. AAl-A obtained the ethics and funding of the study and wrote the first draft of the manuscript. AAl-D and AD performed the statistical analysis and wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.