Confronted with unmanned surface vessel (USV) operations where GNSS signals are unavailable due to obscuration and other factors, a LiDAR SLAM-assisted fusion positioning method for USVs is proposed to combine GNSS/INS positioning with LiDAR-SLAM. When the USV works in wide-open water, the carrier phase differential GNSS/INS loosely coupled integration strategy is applied to fuse and calibrate the positioning data, and the positioning information of the USV is obtained through the coordinate conversion process. The system uses a dynamic switching strategy to enter to LiDAR-SLAM positioning when GNSS signals are not available, compensating the LiDAR data with precise angle information to ensure accurate and stable positioning. The experiments show that compared with the traditional Kalman filter and adaptive Kalman filter fusion algorithms, the positioning error is reduced by 55.4% and 43.5%. The velocity error is also limited by 78.2% and 57.9%. The standard deviation and the root mean square error are stable within 0.1 m, indicating that our method has better data stability, while the probability of positioning anomaly is effectively controlled. An unmanned surface vessel (USV) is an intelligent platform on water equipped with a control system, communication system, and sensor system, which minimizes navigation risk and is highly valuable for research and application in facing the complex and changing water operation environment ,2. USV aThe most popular way is GNSS/INS combination navigation. GNSS has a stable signal and high positioning accuracy in the outdoor open environment, but under vegetation blockage in inland waters, the satellite cannot solve the fixed solution, resulting in signal loss of lock and data loss. Severe multipath effects  can alsoLiDAR is used for operation in areas with obvious environmental features, such as indoor or dense buildings. Tang  proposesTo satisfy the USV positioning needs in the positioning satellite signal obscured areas, such as under a dock or bridge or in a tunnel, we propose a LiDAR SLAM-assisted unmanned surface vessel fusion positioning method ‘Navigation of USV’, abbreviated as NavUSV, which adopts a carrier-based phase-difference separation based GNSS/INS loosely coupled integration strategy to obtain the position information when working in outdoor open water. When entering an environment with weak satellite signals, the system switches to LiDAR-SLAM positioning and compensates the LiDAR data using precise angle information to ensure accurate and stable positioning.A method named NavUSV is proposed for the complicated and changing positioning environment of USVs, based on the self-developed USV platform, equipped with a variety of environmental sensing and navigation and positioning sensors, using different sensor information fusion in different environments, and fully utilizing the advantages of GNSS, INS and LiDAR sensors. Thus, achieving the purpose of dynamic switching of indoor and outdoor navigation and positioning of USVs. The technical roadmap is shown in The carrier phase differential GNSS system includes a reference station and a mobile station. The land reference station calculates the differential data based on the known fixed latitude and longitude as well as its own measured real-time positioning, which is sent to the mobile station carried by the USV via broadcasting. The mobile station receives the differential data and its own measurement of real-time positioning data for differential processing to obtain high-precision positioning data .In the loosely coupled structure, both carrier phase differential GNSS and INS work independently and provide the results of navigation parameters separately. The INS is a type of MEMS-INS, whose data errors mainly consider gyroscope and accelerometer errors. Through INS long-term static data analysis, the first-order Markov process is chosen to describe the random drift of the gyroscope, and the specific parameters are shown in Handling noise using the error covariance prediction equation:The Kalman gain is calculated to assign weights between the states predicted by the model and the states measured by the sensors:Further updating of the state based on the obtained Kalman gain and measurements:In the last, the error covariance matrix is updated to be used as The system inputs the position and velocity information provided by GNSS and the position, velocity, and attitude provided by INS into the extended Kalman filter ,15,16,17Because the Bayesian filter-based Slam algorithm can not easily eliminate the cumulative error, such an algorithm is only suitable for interior small-area maps. At the same time, the graph optimization-based Slam can optimize the global robot poses by loopback to eliminate the cumulative error, so it has an advantage over the filter-based Slam. The Cartographer algorithm is an open-source algorithm introduced by Google in 2016 , which iConsidering that the USVs need to operate in a GNSS-challenged environment, characterized by few feature points and many linear structures or repetitive structures, we have combined MEMS-INS and 2D LiDAR-SLAM by EKF and used Cartographer to interpolate the poses together with scan matching in local SLAM to construct maps in a GNSS-challenged environment. Each combined filtering process includes a system state and observation update, specifically referring to the prediction update of the INS error state and observation update based on 2D LiDAR plane alignment results in the combined navigation system.The GNSS positioning system based on carrier phase differential is suitable for open inland rivers and lakes, etc. Combined with MEMS-INS, it can obtain high-precision positioning data, but the accuracy decreases in indoor or GNSS-challenged environments. The 2D LiDAR-SLAM-based positioning system is ineffective for outdoor positioning due to laser ranging limitations and sparse map-building feature points, whereas it is suitable for indoor relatively narrow and fixed environments. These two navigation and positioning strategies are complementary, and the proposed NavUSV method combines the two systems and dynamically switches between them in the transition region to achieve compatibility with both indoor and outdoor environment positioning requirements.When USVs operate in open and unobstructed waters, the GNSS system is used as the dominant navigation method. The WGS84 geodetic coordinate system gives the geodetic latitude, geodetic longitude, and geodetic elevation of a point and tells the position of the point in the Earth more intuitively, so it is also called the latitude, longitude, and elevation coordinate system (LLA). Therefore, it is necessary to convert LLA coordinate system data output from the GNSS system into the navigation coordinate system applied to USV navigation and positioning, and the east-north up coordinate system (ENU) is based on the user’s location P as the origin, with the X-axis pointing east, the Y-axis pointing north, and the Z-axis pointing to the zenith. ENU coordinate system in the geographic coordinate system is generally used as the navigation coordinate system in inertial navigation, as shown in (A) Finding the rotation matrix between the WGS84 coordinate system and the Earth coordinate systemIn The radius of the meridian circle at height h is (B) Finding the rotation matrix of the coordinates between the Earth coordinate system and the ENU coordinate systemThe rotation relationship between the Earth coordinate system and the geographic coordinate system can be represented by the direction cosine array. When the geographic coordinate system is chosen as the ENU coordinate system, its coordinate transformation matrix can be expressed as (C) 2D LiDAR-SLAM coordinate system matchingTo ensure data stability and consistency when the two systems are dynamically switched, it is necessary to use the same coordinate system to represent the data information of the USV navigating in different system combinations. Firstly, the 2D LiDAR-SLAM navigation coordinate system is rotated in the same direction as the GNSS navigation coordinate system axes, and the current attitude angle of the USV is obtained in the transition region (where both systems exist), and the difference is found to obtain the corrected rotation angle . SupposeAfter unifying the coordinate systems of the two navigation systems, the navigation information (1) To achieve continuous and stable navigation of the USV navigation system, real-time monitoring of the output positioning information and attitude data is required when passing between the scenarios to which each of the two combined navigation methods is adapted. The monitoring content mainly includes the reliability of the navigation information and the environmental monitoring status information of each of the two combined navigation modes. The monitoring method is to subscribe to the position data and environmental status data of the GNSS and LiDAR positioning system and then analyze the reliability, according to the current position of the USV, to determine whether it is necessary to switch to another navigation mode, as shown in (2) Each observable sensor in the loosely coupled architecture is relatively independent of each other, so the sensor switching strategy can be described as monitoring the performance of the positioning system in terms of the total system error (TSE) confidence, alerting the sensor node when the performance metric of the working sensor exceeds a specified threshold ,21, and (3) When the USV drives into the GNSS-challenged environment, the GNSS signal generates a lot of fluctuations and positioning anomalies. The LiDAR also changes from being heavily affected by water reflections in open water to receiving obvious obstacle reflection signals. At this point, the TSE exceeds the preset threshold. The GNSS node issues an alarm, and the USV control layer determines the need to switch to the LiDAR-SLAM positioning information source. It retraces the position information of the USV in the combined GNSS/INS system 3s ago, inputs and adopts it as the initial position of the combined LiDAR system, and the coordinate system transformation is carried out.(4) When the USV enters a GNSS signal stabilization environment, the GNSS signal availability improves significantly and smooths out. At this time, the performance of the LiDAR positioning system falls out of the threshold, the availability decreases, the USV control layer judges that the node status of the combined GNSS/INS system returns to normal, and the USV’s positional information before 3s in the LiDAR-SLAM system is inputted into the coordinate system of the combined GNSS/INS system accordingly. According to the experimental test, the error of positioning data before and after switching between the two positioning systems is less than 5cm, and the fluctuation of the heading angle is less than 1°, as shown in This research is based on the self-developed multi-module intelligent catamaran unmanned boat platform, which contains a control module, a navigation and positioning module, and an operation module. The hull contains a homemade control box with multiple ports containing GNSS signal input port, 485 electronic compass communication, left and right motors, and power supply, which can realize the functions of external manual control, internal autonomous cruise, and navigation security data acquisition and processing. The USV is equipped with carrier phase differential GNSS/INS and 2D LiDAR-SLAM navigation and positioning systems, both rigidly connected to the USV operating platform, as shown in The GNSS positioning system adopts the WTRTK-WL module, the reference station is erected on the shore of the operating waters of the USVs, and the mobile station is erected on the working navigation platform of the USVs. The INS module adopts WTGAHRS3 3D motion attitude measurement system based on MEMS technology, which contains a 3-axis gyroscope, 3-axis accelerometer, and other motion sensors. The parameters are shown in 0 | 0 = , and P0 | 0 = diag2. The base station and antenna we used in the differential GNSS system is Southern Satellite Navigation’s Galaxy 1 RTK, with a sampling rate of 1Hz to 20Hz. We use a patch antenna from ublox to collect data as a set of reference datasets. The proposed algorithm and existing algorithms are all carried out by ROS and Matlab 2016 on a computer with an Intel core i5-4200H CPU at 2.80 GHz, 8 GB memory, and Windows 10 operating system.To verify the reliability and accuracy of the USV positioning system, 2 validation experiments were conducted on the campus of Shanghai Ocean University. In this research, the sample rates of IMU and GNSS are 200 Hz and 10 Hz, respectively, and the parameters of LiDAR can be obtained from Experiment IThe system feasibility experiment was carried out in a building on campus, and the test path is shown in X, AY, and AZ are the longitudinal acceleration, lateral acceleration, and vertical acceleration in the navigation coordinate system, respectively. It can be seen that through sensor information fusion and feedback correction, the white noise and zero offset generated by the system have been effectively removed, and the acceleration variation is stabilized.Experiment IIFurther USV crossing tests were conducted on campus lake, where GNSS signals were severely obscured under the bridge. The navigation path and the acceleration performance of the INS are shown in x, Ay, and Az are all stable within 0.2 m/s2, with relatively stable and controllable variations.As can be seen in We conducted the performance analysis and accuracy verification of the USVs positioning data collected in Experiment II. In the global combined GNSS/INS and LiDAR/INS positioning system, we compared the position error and velocity error of the sensor information under different fusion algorithms. It can be seen from The results of this experiment are further analyzed quantitatively by comparing the root mean square error (RMSE) and the maximum error (MAX) of the information fusion results of the Kalman filter (KF), the adaptive Kalman filter (AKF), and the EKF algorithm in NavUSV to verify the superiority of NavUSV in the navigation and positioning of USVs. The root mean square error (RMSE) is the square root of the ratio of the square of the deviation of the predicted value from the true value to the number of samples m. By comparing the RMSE, we can find the difference in the error size of different methods. Usually, the RMSE of stable algorithms is stable and tends to be close to 0, and the standard deviation (SD) reflects the dispersion of each error indicator. The comparison results are shown in In comparison, the RMSE of the NavUSV method proposed in this research is significantly better than the other two fusion algorithms, and the positioning error is reduced by 55.4% and 43.5% compared with the KF and AKF algorithms, respectively, while the velocity error is reduced by 78.2% and 57.9%. The 95% confidence interval can be described as the point estimate of the overall proportion and the marginal error ε describing the precision of the estimated quantity; the smaller the ε, the more precise the estimate. The results show that the localization accuracy is higher using the NavUSV method within a given 95% confidence level. The standard deviation and the root mean square error are stable within 0.1m, which shows that NavUSV has better data stability than the other two fusion algorithms. In addition, the peak value of MAX for each index error of NavUSV is also smaller, indicating that the probability of outliers in the positioning process is reduced. In summary, the superiority and accuracy of the NavUSV system are guaranteed.The use of single-sensor positioning in the water operation scenario of USVs cannot meet the required accuracy requirements. The mainstream approach is to adopt multiple sensors for information fusion and data feedback correction, fully utilizing the respective advantages of each sensor to achieve the purpose of improving navigation and positioning accuracy ,23. The (1) A LiDAR SLAM-assisted multi-source information fusion positioning method for USVs is proposed in this study, which innovatively integrates combined GNSS/INS positioning with a 2D LiDAR-SLAM positioning method on a USV platform. A carrier-phase differential GNSS/INS loosely coupled integration strategy is applied when the USV works in open water. Fusion correction of positioning data is performed using extended Kalman filtering, as well as coordinate conversion to obtain USV positioning information.(2) When the USV enters the environment with a weak satellite signal, the working sensor’s performance indicator exceeds the specified threshold and raises an alarm. The USV control system responds quickly by switching from the current sensor to the set LiDAR-SLAM positioning information source. The outdoor location data with the local coordinate system as the origin are used as the initial location for building the indoor operation environment, combines the INS position data with the 2D LiDAR-SLAM method, and performs data fusion via the Cartographer algorithm to get the accurate angle information and compensates the LiDAR data to improve the stability of positioning.(3) The feasibility of the NavUSV system is verified through experiments. Compared with other positioning methods, this research considers the positioning requirements of the USV in real operational scenarios. It utilizes an organic combination of two integrated systems so that the USV can still obtain high-precision positioning information when working in complex scenarios. In terms of accuracy, compared with the most widely used KF and AKF fusion algorithms, NavUSV reduces the positioning error by 55.4% and 43.5%, respectively, while the velocity error is reduced by 78.2% and 57.9%. The standard deviation and the root mean square error are stable within 0.1 m, showing that NavUSV has better data stability than the other two fusion algorithms. The possibility of positioning anomaly is also controlled.(4) At present, there are two main methods of weakening multipath errors: hardware processing and post-processing. The hardware processing method is solved by new antennas and modified signal tracking loops. The method of using SNR to weaken the multipath effect is one of the post-processing methods, which analyzes the signal-to-noise ratio SNR of GPS signals and uses the frequency characteristics to weaken the multipath effect. Our solution is to use complementary GNSS/INS loosely coupled features to perform adaptive estimation of measurement noise. Then choose a properly shaped and well-shielded antenna, such as a choke antenna, and use multiple GNSS receivers in close proximity for positioning. The multipath parameters can be corrected using spatio-temporal processing to reduce the effect of multipath. (5) Subsequent research will try to introduce sensor data such as 3D LiDAR-SLAM and Doppler velocity log (DVL) to calculate the position and attitude of USVs with higher accuracy ,27. In a


The recognition of serious pathologies affecting the musculoskeletal (MSK) system, especially in the early stage of a disease, is an important but challenging task. The prevalence of such serious pathologies is currently low. However, in our progressing aging population, it is anticipated that serious pathologies affecting the MSK system will be on the rise. Physiotherapists, as part of a wider health care team, can play a valuable role in the recognition of serious pathologies. It is at present unknown how accurately Austrian qualified physiotherapists can detect the presence of serious pathologies affecting the MSK system and therefore determine whether physiotherapy management is indicated (keep patients) or not .We will explore the current ability of Austrian qualified physiotherapists to recognize serious pathologies by using validated clinical vignettes.As part of an electronic web-based survey, these vignettes will be distributed among a convenience sample of qualified Austrian physiotherapists working in a hospital or private setting. The survey will consist of four sections: (1) demographics and general information, (2) the clinical vignettes, (3) questions concerning the clinical vignettes, and (4) self-perceived knowledge gaps and learning preferences from the perspective of study participants. Results will further be used for (1) international comparison with similar studies from the existing literature and (2) gaining insight into the participants’ self-perceived knowledge gaps and learning preferences for increasing their knowledge level about keep-refer decision-making and detecting serious pathologies.Data collection took place between May 2022 and June 2022. As of June 2022, a total of 479 Austrian physiotherapists completed the survey. Data analysis has started, and we aim to publish the results in 2023.The results of this survey will provide insights into the ability of Austrian physiotherapists to make accurate keep-refer decisions and to recognize the presence of serious pathologies using clinical vignettes. The results of this survey are expected to serve as a basis for future training in this area.DERR1-10.2196/43028 We live in an aging society. The forecasted increase in the number of people older than 65 years from currently 34.4% to 59.2% by 2070 for the entire area of the European Union will pose great challenges for the health care systems of the European Union member states . A very MSK conditions that often present with pain and restricted mobility are highly prevalent within the general population . In 2016Recent data from Denmark demonstrated that the overall prevalence of serious pathologies affecting the MSK system is at present comparatively low (2.3%) . For insThe recognition of serious pathologies affecting the MSK system especially in the early stage of a disease is a challenging task . HoweverTo analyze clinical decision-making abilities of medical and other health professionals, researchers make use of clinical vignettes that are concise paper-based or electronic descriptions of actual clinical situations . VignettPrevious cross-sectional studies on qualified physiotherapists in the United States -26, GermThe ability of Austrian qualified physiotherapists to accurately detect serious pathologies and to determine if a patient is suitable for physiotherapy, or rather needs a more comprehensive medical workup, has not yet been explored. Considering the above-outlined changes to the Austrian health care sector and challenges of an increasingly aging society, this knowledge gap needs to be addressed. To fill this knowledge gap, we propose a cross-sectional web-based survey using validated clinical vignettes .The overall aim of this study is to assess the ability of Austrian qualified physiotherapists to make accurate keep-refer decisions and their ability to detect serious pathologies affecting the MSK system based on 12 clinical vignettes. In addition, we want to explore potential knowledge gaps and learning preferences to acquire more expertise in making keep-refer decisions from the perspective of study participants.The Methods, Results, and Discussion sections will adhere to the CHERRIES (Checklist for Reporting Results of Internet E-Surveys) statement .The project was formally examined by the Commission for Scientific Integrity and Ethics of the Karl Landsteiner Private University, and it was found that in accordance with the set criteria, a further review by the commission was not required . There were no medical ethical concerns about the conduct of the project.To be included in this study, prospective participants need to (1) be registered as qualified physiotherapists with the Austrian Health Professions Registry and (2) work in a hospital or private setting in Austria. Physiotherapists who have not actively treated patients during the last 12 months will not be eligible for this study.The email addresses of physiotherapists registered on the Austrian Health Professions Registry and with a publicly available email address have been collected. The recruitment process will be divided into the recruitment of physiotherapists working in a private setting and physiotherapists working in a health institution.In the first part, physiotherapists who are working as private physiotherapists will be sent an email with an explanation of the study and a link to take part in the survey. If needed, after 2 weeks, the email will be re-sent to remind physiotherapists of the study.In the second part, the multidisciplinary team leaders (n=44) of each health institution in Austria will be sent an email with information about the study and will be asked to provide information on the number of physiotherapists currently working for the institution and indicate if they are interested in taking part in the study. If interested, a new email will be sent to the multidisciplinary team leaders containing a link to forward to the physiotherapists to take part in the study.When the link is activated, the physiotherapists will be taken to a website on the Unipark platform. Information regarding the research aim, eligibility criteria, and the anonymous nature of the study will be available. Consent will be given when participants accept the consent form and click on the “next” button.On March 15, 2022, a total of 16,991 physiotherapists were registered on the Austrian Health Professions Registry. Given this population, 376 physiotherapists need to be recruited to retain a 95% CI with a margin of error of 5% .The survey will be constructed on the internet using the web-based survey tool Unipark. It will take 15 to 20 minutes to complete the whole survey. A copy of the survey, except the 12 translated vignettes, is provided in The survey consists of four sections:Demographic features of participants, for example, age, sex, working experience, and educational level.Twelve vignettes, translated from English to German. After reading each clinical vignette, participants will be asked to decide if this is (a) an MSK condition, which does not need referral to a medical doctor (keep); (b) a noncritical medical condition, which needs referral to a medical doctor, while the patient can be treated by a physiotherapist (keep-refer); and (c) a critical medical condition, which needs immediate referral to a medical doctor and treatment by the physiotherapist should be stopped (refer). The vignettes (used with permission) have been validated by a panel of medical doctors and expert physiotherapists .Feedback will be sought from participants on the 12 vignettes. Questions will be asked onhow difficult  it is to make keep-refer decisions based on the information presented in the vignettes,the relevance of the vignettes for everyday work , andpossible missing information within the vignettes for making accurate keep-refer decisions (open-ended question).Exploration of knowledge gaps and learning preferences to acquire more expertise in making keep-refer decisions and detecting serious pathologies from the perspective of study participants. Questions will be posed onthe confidence of participants to conduct clinical examination procedures if participants are interested in learning more about keep-refer decision-makingsuggestions for content and format of future training sessions to acquire more expertise in keep-refer decision-making any further suggestions and comments (open-ended question).Pilot TestingThe first draft of this survey was sent to 5 physiotherapists and 4 medical doctors. Participants were asked to comment on their general understanding of the questionnaire and the appropriateness, comprehensibility, and proper sequencing of individual questions. In addition, the participants in the pilot could suggest additional questions that they deemed valuable. For an example, one participant suggested adding a question where future participants will be asked about their confidence in conducting clinical examination procedures  that might be relevant for clinical and keep-refer decision-making. Another suggestion was to add a question that could aid with the inclusion and exclusion criteria. Participants were therefore, right at the beginning of the survey, asked if they have treated patients during the last 12 months. If the participants answer this question with “no,” they will be thanked for their interest and then will automatically be prevented from continuing with the survey. The validity of some of the vignettes in the Austrian health care system was also questioned; therefore, after elaborate discussions, the originally envisioned vignettes by Jette et al  were repThe survey will be constructed online, and progression through the 12 vignettes will be mandatory so that an answer must be entered before one being able to continue. This will allow only completed clinical vignettes to be included in the analysis. Completed surveys will be automatically sent back to the online survey tool Unipark. The data will be stored at the QuestBack server park in Bremen, Germany. After the data collection is completed, the raw quantitative data will then be downloaded onto an SPSS file (IBM SPSS Statistics 28.0). The qualitative data will be exported to a Word document and then imported to a MAXQDA project (MAXQDA 2020). All data will be stored on a secure OneDrive folder to which only the researchers have access through their password protected laptops. The survey will be designed to be completely anonymous; however, there is a small risk that participants will share personal data in the open-ended question in the last section of the survey. If this happens, these data will be anonymized by a member of the research team.Individual participants’ responses for each of the 12 vignettes will be classified as either being correct (Yes) or incorrect (No). Replicating previously used methodology ,25,27-30For the MSK vignettes: treat the patient without the need for medical referral (keep) or treat the patient with additional medical checkup .For the medical noncritical vignettes: choose to start physiotherapy with additional medical evaluation (keep and refer) or refer the patient without physiotherapy management (refer).The sole correct answer for medical critical vignettes is sent the patient for medical evaluation without physiotherapy management (refer).Once the data collection period is finished, the quantitative data will be checked for completeness and outliers. Missing data will be labeled. The Shapiro-Wilk test will be used to examine if the data are normally distributed. If values are normally distributed, the mean (with SD) will be calculated; if not, the median (with IQR) will be calculated. All descriptive statistics, such as age, sex, years of experience as a physiotherapist, and type of expertise, will be collected as categorical data, and the percentage for each category will be calculated.In the clinical vignettes, the mean percentages (plus SD) of correct keep-refer decisions and actual numbers as well as percentages of participating physiotherapists who manage to accurately answer all vignettes from a specific category will be calculated  ,25,27-30The questions concerning the feedback from study participants on the 12 vignettes, such as “how sure the participants were when answering the clinical vignettes?” and “how relevant the vignettes were for the participants?” will be calculated as percentages for each category.The questions concerning learning about red flags, such as interest for red flags training, medium of training, and interest of specific assessment techniques, will also be listed as percentages for each category.The 2 open-ended questions concerning missing information in the clinical vignettes and any other remarks will be analyzed deductively using framework analysis  in MAXQDThe distribution of the survey took place between May 2022 and June 2022. As of June 2022, a total of 479 Austrian physiotherapists completed the survey. It is anticipated that data collection, analysis, and writing up for a potential publication in a peer-reviewed journal will take 4 to 6 months.A major strength is that our methodology is in line with previously published studies ,25,27-30To the best of our knowledge, this is the first study that examines the ability of Austrian physiotherapists to make accurate keep-refer decisions and to recognize the presence of serious pathologies using clinical vignettes. Moreover, this is the first attempt to explore potential knowledge gaps and learning preferences to acquire more expertise in making keep-refer decisions and recognizing the presence of serious pathologies from the perspective of Austrian qualified physiotherapists. These results will be used to inform future training in this field and should help advance patient safety and interdisciplinary collaboration within the Austrian health care system.During the preparation of the study the aim was to collect the email addresses of all physiotherapists currently registered to work in Austria. However, from the private physiotherapists not all email addresses were retrievable on the internet, and 50% of the population will not be contacted. This could have implications on the generalizability of the study.The limitations of clinical vignettes as a sole instrument for examining clinical decision-making strategies of health care professionals have previously been highlighted -39. Howe


Many developing countries are facing the difficulty of choosing between economic growth and energy conservation and emission reduction (ECER). China has strengthened the implementation of ECER by setting environmental accountability as the development goal of local governments, hoping to have better governance effects. To evaluate the actual intervention effect of this approach, this paper constructs panel data covering 46 countries from 1995 to 2014 and uses the difference-in-differences (DID) method and the composite control method to quantitatively analyse the policy effect. The results show that China can effectively curb energy consumption and carbon emission intensity per unit of GDP by adding ECER targets to the government’s five-year plan, which has significant effects on ECER. Furthermore, we use an intermediary mechanism to test and identify low-carbon alternatives and an ECER promotion mechanism for technological advancement. The conclusion shows that economic development is compatible with low carbon and energy consumption. Combined with China’s long-term goals for ECER, it can be considered that on the road to achieving carbon peaking and carbon neutrality in the future, the economy and tertiary industry should be rationally developed, the degree of urbanization should receive more attention, and the proportion of thermal power generation should be reduced. As the main producers of energy emissions in the current period, developing countries are different from developed economies. They face the contradiction between economic development and ECER constraints3. As the largest developing country, China has also become the economy with the largest carbon emissions due to its booming economy. Currently, it is actively responding to the above problems through its own efforts. Clarifying the main responsibilities of each local regime and including the ECER target in local governments’ economic development plan are an important measure that China has implemented for a long time to strengthen ECER work and achieve phased emission standards.Global warming and the worsening of carbon emissions have seriously challenged the future situation of human survival and development. Since the beginning of the twenty-first century, the impact of climate change on human activities has become increasingly obvious, and major countries around the world are taking active measures to deal with these changes4. In the 11th Five-Year Plan, the local regimes arranged the ECER target accountability system from the central government to replace the original GDP-oriented system, forming solid incentives for local bureaucrats and strengthening the implementation of existing ECER measures. This kind of target accountability system was included in the institutional innovation of government work objectives, which is obviously different from the existing ECER policy implementation mechanism in other countries around the world. Therefore, academics, policy-makers and environmentalists have paid much attention to the policy effects of this practice. However, the results of existing research on the policy effect of the ECER target accountability system are still very limited5, and no empirical study has analysed the policy effect of the ECER target responsibility system in China from the perspective of cross-country comparison. Therefore, this article employs cross-country counterfactual analysis to tackle this problem. The findings show that compared with other countries, China's unique policy accountability system for ECER has a remarkable effect on the enforcement of both energy conservation and emission reduction levels significantly after implementation. Thus, this effect can occur through the optimization of the energy power generation industrial structure.The characteristics of governance in China have mandated local regimes with strong authority, which is matched by competition to realize the target accountability system across the countryChina approved its accession to the Kyoto Protocol in 2008, clarifying its own ECER obligations and working with the international community to meet the enormous challenges posed by climate change. The Kyoto Protocol came into force in February 2005 as a supplementary clause to the United Nations Framework Convention on Climate Change (UNFCCC). As a developing country, China’s per capita carbon emissions are lower than the world average. Although there has been no restriction on absolute carbon emissions since its approval of the Kyoto Protocol, China has taken seven measures to address climate change issues through a series of ECER policies. However, the compliance level of these policies depends on the implementation of government responsibilities.6. At that time, the government’s environmental regulation had the problem of soft policy constraints. Due to the accountability system based on GDP growth targets, local officials were obliged to ease environmental regulations to ensure economic growth. Based on the characteristics of China’s energy resources, the structure of energy use is still dominated by coal. In the historical period of the single GDP target accountability system, the consumption of fossil energies not only increases the agglomeration of local GDP but also causes environmental pollution, reducing the possibility of future sustainable development7. Therefore, many places have avoided ECER responsibility while pursuing economic growth.Before local governments’ ECER responsibilities were clarified, the government’s main responsibility for GDP growth, resulting in ECER compliance being limited to the environmental protection department’s responsibility as well as a lack of attention8. However, regions outside of China have rarely implemented explicit ECER objectives through targeted accountability. This political uniqueness provides support for this paper and the subsequent selection of identification strategies.In the Eleventh Five-Year Plan (2006–2010), China determined for the first time the binding indicators that governments at all levels need to achieve for ECER. Doing so was a major step forward in the implementation of ECER policy. The five-year plan is the economic development plan of the Chinese government. The government goals written into the five-year plan have become the focus of the work of government departments. Officials also rely on these goals to evaluate work performance. The policy practices of developing countries show that target accountability is an effective tool for local officials to achieve the central government’s policy goals5 has suppressed the deterioration of the environment unrestrainedly in various regions. If the local environment does not meet the corresponding goals, the promotion of local officials will also be restricted, aligning the orientation of officials’ personal interest and the public’s environmental interests, thus realizing the common development of the economy and the environment and changing the previous situation, which was oriented only towards economic development. This shift has realized the internalization of the externalities of environmental regulations. Third, the five-year plan is consistent. Consistency means that environmental protection policies will continue to play a role in the future for a long time.In the Eleventh Five-Year Plan, the government’s economic development goals had to achieve ECER compliance. The compliance requirements for this emission reduction target were implemented in the "Notice of the State Council on Approving and Transmitting Implementation Plans and Measures for Energy-Saving and Emission Reduction Statistical Monitoring and Assessment" (hereinafter referred to as the "Notice") issued in 2007. The central government clearly stipulated that the completion of emission reduction targets would be regarded as an important basis for the comprehensive assessment of the performance of local governments and officials at all levels, and the accountability system for officials who did not meet the ECER standards and the "one-vote veto" system was implemented. The implementation of this "Notice" has greatly increased the ECER enthusiasm of officials everywhere, and many places have even relinquished some economic growth results to achieve emission reduction targets. To date, China has begun to form a scientific and systematic ECER effectiveness statistics and evaluation system, strengthening the role of pollution control compliance in officials’ performance and having a milestone effect on tightening pollution control. First, the Chinese government changed its overall development goals. From the single goal of realizing GDP growth to the dual goal of realizing the common development of the economy and the environment, economic development cannot occur at the expense of the environment. Environmental governance has become a hard constraint on growth. Economic growth is achieved under environmental constraints. The two are mutually tolerant. Second, environmental protection has become an obligation for the government as the main body through official accountability. The attribution of responsibility to achieve goals and standardsBefore incorporating ECER targets into the five-year plan, China had issued corresponding laws and regulations to restrict environmental development. As shown in Table For China, the five-year plan holds great significance. In the plan, binding indicators are set to promote the realization of energy saving and emission reduction targets. From the beginning of the Eleventh Five-Year Plan to the present, each successive Five-Year planning government has set specific binding targets.9. The implied increase in energy consumption in exports is due to the expansion of the export scale11. Therefore, the coordination of the relationship between China’s economic development and environmental pollution also warrants attention. The Porter hypothesis12 states that ECER will not inhibit economic development; rather, appropriate environmental control policies will promote technological progress, thereby increasing the production capacity of enterprises. In China, the Chinese government can implement conservative energy policies and carbon emission policies without affecting economic growth13. The research of Wang et al.14 also supports the Porter hypothesis and argues that differentiated energy saving and emission reduction policies will further promote the green economy.After China’s accession to the World Trade Organization, the degree of openness to the outside world and the degree of trade further increased, resulting in the problem of carbon transfer. Approximately 20% of China’s domestic emissions are due to consumption in developed countries. Many developed countries have transferred their own emissions to trade partners from which they import goods18. However, the energy structure, trade openness and urbanization have a two-way causal relationship with carbon dioxide emissions19. The energy structure accounts for the largest proportion in terms of the factors that affect carbon emission intensity20. The regional equilibrium of emission intensity21 is followed by the influence of enterprise equilibrium23. China promises to peak its carbon emissions by 2030. Only when the constraint intensity of environmental governance policies gradually increases can energy structure optimization and carbon emission intensity be forced to ease, while the peak in fossil energy consumption and carbon emissions can jointly be achieved in advance24. The continuous promulgation of environmental legislation and environmental constraint policies attempts to strengthen such government administration pressure25, but the difference between the strength and weakness of policy implementation is ignored26.Most research results indicate that the energy structure, the industrial structure and urbanization have an important impact on the effectiveness of ECER27. Current studies focus on the fact that this enormous change has continued through the 13th Five-Year Plan period. At present, analysis based on government targeted accountability focuses on environmental protection29, and some studies have found differences in national development caused by environmental technology progress30, including the differences in growth caused by the adoption of renewable energy31, but a cross-country comparison of ECER effectiveness between China and other countries in the same period is lacking.Similar research has shown that, compared with the past period, China’s energy saving and emission reduction policies and plans formulated during the Eleventh Five-Year Plan period have made significant progress, and many plans that even exceeded their energy saving targets have been completed. However, with the deepening of policy implementation, during the 13th Five-Year Plan period, China’s economic development goals are easily achieved, but the level of development in various regions is uneven, causing most regions’ own economic goals and ECER goals to be mismatched, resulting in unsatisfactory energy saving and emission reduction effects32. However, there are limited studies evaluating the effectiveness of officials’ accountability for environmental constraint goals33. To better realize the sustainable development goals of the UN, this paper evaluates the innovation effect on institutional tools when the central government adopts a target accountability system to strengthen the intensity of ECER policy. If we regard China's local regime undertaking the target responsibility system of ECER in the five-year plan as a quasi-natural experiment, the effect of the government's policies on ECER can be evaluated from different aspects through two observation variables: energy consumption per unit GDP and carbon emission intensity. Based on these assumptions, this paper employs the DID method and the SCM to conduct counterfactual estimation. Compared with ordinary regression, the counterfactual estimation method can capture the impact of policy implementation in full probability events, which can avoid the overidentification of policy effects caused by other common factors, such as legislation on environmental protection and the signing of the Paris Climate Agreement. To ensure that the results are not accidental, we also use sensitivity analysis and permutation tests to prove that the estimation results are less sensitive and are robust.In summary, energy consumption and emissions are the focus of many studies on ECER, and there are enough research results to show the changing relationship between China’s economic development and ECER. There are also sufficient achievements to show the effectiveness of ECER-related policies in ChinaCompared with existing similar studies, this paper makes the following marginal contributions: (1) Taking the accountability system of ECER targets as a variable affecting policy impacts, this paper empirically discusses the actual effect of local officials’ efforts to achieve ECER goals from the perspective of the government's accountability for the implementation of existing policies, creating a new dimension in research. (2) This paper conducts a horizontal comparison of ECER implementation effects across countries with a long time span, reflecting the implementation results of China's unique policy tools and adding new empirical evidence to recent ECER country studies. It differs from existing studies that focus on conducting a vertical comparison of ECER policy effects in China. (3) This research finds that the mechanism of the target accountability system implementing ECER policy is increasing the proportion of clean power generation, providing a new path explanation for exploring the transmission mechanism of ECER policy.4. There was no corresponding mechanism for local governments to undertake their due obligations with regard to environmental protection and ECER problems. Thus, before 2012, there was statistical manipulation of ECER, which empirical evidence subsequently eliminated34. The enhancement of this promotion mechanism has been deeply understood, convincing people with experience of economic construction in the past 30 years. When the economic growth target gave way to the environmental target, institutional inertia formed a strong binding force on local governance. Local governments explicitly established ECER targets in the five-year plan to initiate "promotion tournament" competition under a new accountability orientation. Thus, ECER policies and regulations have been implemented effectively. In the successive five-year plans after the Eleventh Five-Year Plan, ECER objectives have been continuously promoted, forming a long-term consistency of environmental policy constraints, actively promoting the management of the demand side, and reducing emissions by improving energy efficiency35, leading to sustained ECER effects.The environmental accountability system for officials has been implemented since the Eleventh Five-Year Plan. The ECER target has been widely written into the work outline of local governments and has become one of the key guidelines in evaluating the performance of major officials. Previously, since local government economic development goals have long been set based on GDP growth, there was a "tournament" mechanism to compete for the rate of economic increase in ChinaTherefore, this paper proposes Hypothesis 1: The environmental target accountability system implemented in the Eleventh Five-Year Plan reduces energy consumption per unit production. Furthermore, it proposes Hypothesis 2: The environmental target accountability system also reduces the intensity of carbon emissions.36. Energy consumption increases gradually with economic growth. Although the use of market mechanisms and institutional supply can continuously reduce the energy consumption per unit of output value to gradually decouple energy consumption from the process of economic growth37, the overall trend of total energy consumption expanding with economic output will not be reversed. Therefore, improving the primary energy structure and gradually replacing fossil energy with renewable energy and low-carbon energy has become a technical path for reducing carbon emission intensity38. All countries have made continuous efforts in regard to the energy structure of power generation, continuously reducing the proportion of fossil fuel power generation and increasing the installed proportion of renewable energy power generation to achieve cleaner production39. China's environmental accountability system has accelerated the pace of the coal-removal process in power generators by local governments. Due to the requirements of the carbon emission mitigation target of the five-year plan, local governments have actively fulfilled their environmental protection responsibilities, made efforts to adjust the structure of primary energy power generation, vigorously installed clean energy generating units such as hydropower, wind power and photovoltaic power generation, and shut down existing thermal power units or replaced them with natural gas low-carbon power generation40, which popularizes clean power generation technology by reducing the proportion of thermal power generation to effectively reduce carbon emission intensity41.The increase in the scale of carbon emissions comes directly from the energy consumption in the production process. Therefore, reducing carbon emission intensity depends on continuous ECER efforts, which technically reduce the energy consumption per unit of output valueTherefore, this paper proposes Hypothesis 3: The environmental accountability system implemented in the Eleventh Five-Year Plan promotes a reduction in carbon emission intensity by reducing the proportion of thermal power generation.In this paper, the BP Energy Yearbook is selected to build a cross-country database of energy consumption and carbon emissions, and the data source of this study is the economic and social development data of the World Bank’s World Development Indicators (WDI). While the Chinese government is pushing for ECER accountability, other countries are not implementing similar policies. Therefore, causal inferences about the effects of environmental accountability policies rely on country comparisons between China and other countries that have not implemented environmental accountability policies, thus constituting counterfactual estimates. Based on the availability of data, this paper excluded the samples of economies with a large amount of long-term missing data, as well as individual samples with large significant differences. Ultimately, it recorded data on the energy consumption, carbon emissions and economic and social development of 46 countries, and these data constitute the research database of this paper.42.By constructing panel data covering 46 countries from 1995 to 2014, this article explores the impact of China’s transformation of the policy adjustment method to achieve ECER targets on carbon emission intensity and energy consumption per unit of GDP. We try to limit the time node to 2014 because the ECER accountability system for county mayors was made stricter and upgraded to that for local communist party secretaries in 2015. In addition, policy shocks, such as “Article 10 on the atmosphere in northern provinces”, using gas instead of coal for winter heating, and the “low-carbon city pilot zone”, might lead to confusion and distort the real effect of the accountability policy effect. A series of new ECER-concerned policies was provided in China after 2015, and these environmental policies with Chinese characteristics modified the single target to multiple targets in regard to the accountability of local bureaucracies. The general rule revealed in this paper is that the policy effect brought by ECER accountability is significant. The latest literature has already illustrated similar applications by using the same period until 2014 for local official accountability studies in China43, who argued that population size, wealth and the technology level are the main factors affecting the environment. Due to the limitations of the IPAT model, Dietz and Rosa44 established the STIRPAT model on the basis of the IPAT model, and many scholars have also expanded the model to make it more suitable for their own research45. Therefore, this article follows the methods of previous scholars to select the control variables from the above-mentioned aspects.The key observation variables for the transformation of environmental regulation and adjustment methods are energy consumption and emissions. Energy consumption and carbon emission intensity per unit GDP are selected as outcome variables because they serve as the essential observation variables for the transformation of the mode of environmental regulation. In the environmental field, scholars often apply the IPAT model, proposed first by Ehrlich and Holdren46. Energy consumption and carbon emissions are directly affected by a country's economic aggregate; thus, gross domestic product (GDP) is used as a proxy variable5. The development level of the tertiary industry is adopted to reflect the characteristics of the industrial structure to optimize the industrial structure and reduce energy consumption and total carbon emissions47. The replacement of clean energy will effectively reduce carbon emissions48. In this paper, the proportion of clean power generation is used as a proxy variable for the optimization of the energy utilization structure. Except for ratio data, all other data are processed in logarithmic form. Table Referring to previous studies, the control variable set of this paper is shown as follows: Urbanization leads to the aggregation of human activities, increasing the volume of energy consumption and carbon emissions. Therefore, the urban population is selected as the proxy variable for the country's population size49. In this paper, a quasi-natural experiment is formed by incorporating the ECER index into provincial government accountability as a policy impact variable in China's 11th Five-Year Plan in 2006. The net effect of the policy is evaluated by comparing the significant observed differences in ECER characteristics between China and other control countries after 2006. The specific model settings are as follows:To analyse the effects of ECER after China’s transformation of environmental regulations, this paper adopts the DID method, which has been a commonly used approach for the causal inference of policy effects since David Card (1993) By passing the parallel trend test, the horizontal changes in energy consumption and emissions for all sample groups and the vertical changes in China's temporal factors can be differentiated to show the impact of policy implementation. In Eqs.  and 2),,2), and However, the DID method also has limitations. First, it is easy to produce differences between the treatment group and the control group, and it is difficult to avoid policy endogeneity. Therefore, this paper further uses the synthetic control method for analysis and generates the weight of each control group through data driving, which reduces the possible selection bias and endogeneity problems of the control group and makes the conclusion more reliable.The basic idea of the synthetic control method is that it fits other control groups with corresponding weights to fit the situation of the research object without policy. Then, it compares this situation with the actual situation to obtain the policy effect.Suppose that there is a country. The first country is the intervention group, and the remaining countries are the control group; Then,Driven by the data, a linear combination of different weights can be given to the control group to form a counterfactual result:Only by obtaining the If there is a weight vector set When 50 proved that under normal circumstances, the above formula is close to 0, and Abadie51.In this study, we choose the urbanization level, GDP scale, tertiary industry development level and primary energy structure as prediction variables to improve the fitting effect of the policy pre-period, and some period-lagged values of the outcome variables are added as the predictor variables. However, the zero weights are always occupied by employing all of the past values of the outcome variables as the predictor variablesBased on panel data covering 46 countries from 1995 to 2014, this paper studies the promoting effects of China’s environmental regulatory policies in 2006 on ECER target accountability. Table GDP, URB and SER are added to represent the interaction term ECER*Year of the policy effects. TIME is significant at the 1% level, the explanatory power of the model has become stronger, the coefficient has also become larger, and the coefficient increases from − 0.192 to − 0.208. This result shows that the transformation of environmental regulatory policies has a positive impact on energy consumption per unit of GDP and a negative impact on carbon emission intensity. The study of Wang and Liu14 also shows that ECER policies can achieve a win‒win situation for the economy and the environment.Based on the model setting, the output of the DID method is shown in Table Clearly, the regression result of energy consumption per unit of GDP is not in line with expectations. The main reason is that, compared with the synthetic control method, one of the shortcomings of the DID method is that it is difficult to separate the policy, and it may misidentify the result due to policy proliferation. We found that in December 2001, China joined the World Trade Organization and gradually formed the world factory development model, expanded the degree of openness to the outside world, exported a large number of industrial products to the world market, and achieved structural changes in production. Production energy consumption greatly increased, and the impact of joining the World Trade Organization on energy consumption per unit of GDP is greater than the impact of changing policy adjustment methods. Therefore, the regression results of energy consumption per unit of GDP using the DID method are inaccurate.20. Under the same production level, an improvement in technology can reduce the intensity of carbon emissions, and there is no structural change in the development of technology.For carbon emission intensity, we have reason to use the DID method for estimation. The reason is as follows: Although China’s accession to the World Trade Organization led to structural changes in production, carbon emission intensity is mainly affected by a country’s technology level, and the contribution rate of technological energy savings can reach 56%In summary, the regression results obtained by using the DID strategy show that energy saving and emission reduction policies have significant effects on emission reduction, while energy-saving aspects need to be further analysed. Therefore, Hypothesis 2 is validated, while Hypothesis 1 is not.(1) Energy consumption per unit of GDPIn the next stage, the SCM is adopted in this paper to further identify the policy effect after adding the ECER indicator to the accountability of local regimes. Through the calculation and output of Stata, using the predictive variable matrix, linear programming generates the weight vector matrix, thereby fitting China, which is unobserved. Among the 45 control groups, there are five countries in the control group with non-zero weights, namely, Ireland, Kazakhstan, the United States, Mexico, and Indonesia, which have weights of 0.038, 0.002, 0.764, 0.080, and 0.116, respectively. The true values of the predictors in the Table Based on the weights of the countries mentioned above, China under the counterfactual framework is obtained. It can be seen that the difference between the true value and the composite value is very small, and the root mean square percentage error is only 0.081. Both of these results indicate that the fitted China well captures the characteristics of the actual China. Thus, the synthetic China can better fit the change path of energy consumption per unit of GDP and obtain a higher-precision estimate  Carbon emission intensityThe analysis of carbon emission intensity is as follows: Among the weights of the control group, there are four countries with non-zero weights, namely, Finland, Kazakhstan, Luxembourg and South Africa; their weights are 0.071, 0.578, 0.049 and 0.302, respectively. The sum of the values adds up to 1 , Kazakhstan (0.002), the U.S. (0.764), Mexico (0.080), and Indonesia (0.116) are combined to implement energy saving and reduction. For ranked China, in the sensitivity analysis, a control group is eliminated in the order of weight from largest to smallest. The result of each iteration is represented by the light grey line in the figure, and the solid line represents the trend of unobserved China. We see that the solid line in Fig. 8, KazakhBefore 2006, the mean square prediction error indicated the degree of fit with the actual Chinese characteristics, so the smaller the earlier mean square prediction error is, the better the degree of fit. After the policy intervention in 2006, the mean square prediction error indicated that it was affected by the policy. Regarding the degree of intervention, the greater the mean square prediction error is, the greater the impact of the policy. Therefore, the larger the ratio of the mean square prediction error between the post-policy and pre-policy is, the more significant the policy impact. Thus, we can test the significance of the impact of ECER policies by calculating the ratio of the mean square prediction error after 2006 and before 2006.During the policy window period, Denmark, the Netherlands, and Italy in the control group also implemented energy saving and emission reduction policies. To avoid their impact, after excluding these three countries, the results of the ranking test are shown in the Fig. 54. These studies indicate that the energy structure has an impact on energy consumption and carbon emissions. Thus, the thermal power generation rate is used to characterize the energy structure, and it is discussed as an intermediary variable.In summary, this article argues that China has a significant inhibitory effect on ECER after changing its policy methods. Furthermore, this article analyses its impact mechanism based on previous research56, to test the mediating effect, the first step is to regress energy consumption per unit of GDP and carbon emission intensity to test whether the energy saving and emission reduction policies affect it. If the result is significant, the second step is to test whether the policy has a significant impact on the energy structure. If the coefficient of the interaction term is significant, it indicates that the policy has a significant impact on the energy structure of the intermediary variable, and carbon emission intensity is regressed. If the effect of the intermediary variable is significant and the coefficient of the interaction term decreases or is not significant, this result means that the policy affects energy consumption per unit of GDP and carbon emission intensity by affecting the energy structure.According to Wen et al. (2004) and He et al. (2019)The regression results are shown in Table In the empirical analysis, two counterfactual estimation methods, the DID method and the SCM, are used to identify the environmental accountability effect of ECER incorporated into the objectives of the five-year plan. The research shows that by including the five-year plan from 2006 into the ECER action objectives, the implementation of the official accountability system has strengthened the existing environmental protection restraint effect, formed a major incentive for actual ECER work under the existing environmental protection legislation and administrative measures, promoted the general trend of a reduction in energy consumption per unit of output value in China's economic development, and attenuated carbon dioxide emission intensity in the long term.29, but only China has effectively assessed the environmental performance of officials through ECER target accountability33. China's local governments have a strong administrative capacity. Under the performance evaluation path of the "promotion tournament", major officials have a strong motivation to meet standards by using environmental governance ability42, and governments can also bear the enormous economic costs for ECER.The DID method and the SCM are used to verify the impact of ECER target accountability on the decline in actual energy consumption intensity. Different estimation methods show the same conclusion. China's ECER target responsibility system makes the country’s energy consumption intensity significantly lower than that of the other 45 countries. This decline is more prominent than the counterfactual China formed by other control groups in the comparative study of countries, as shown in Fig. 57. Enterprises with high energy consumption and high emissions will gradually move out of areas with more stringent ECER requirements due to policy competition and pour into areas with weak environmental constraints. They will also reduce their energy consumption and carbon emissions through technological transformation to obtain rewards from the government28.First, local ECER is incorporated into the target responsibility system of the five-year plan, which has a significant "demonstration effect". The regions that take the lead in large-scale energy conservation efforts have excellent performance evaluations and promotions of officials, which plays a strong exemplary role in other regions that fail to meet the energy conservation goal58. In relatively developed regions, environmental governance and energy consumption emissions have higher social voices and stronger transparency requirements for environmental emission supervision33. Local regimes have both the popular support and the economic clout to keep energy consumption down, and they can afford not to pursue the absolute size of economic output.Second, under the existing technical conditions, there are short-term technical obstacles to reducing the carbon emission intensity per unit energy consumption. However, reducing energy consumption in economic activities and, thus, reducing total emissions are a suboptimal choice, which could work in the short term and can be economically borne by the government59. In addition, the energy factor endowment level between western energy-exporting provinces and eastern energy-importing provinces differs greatly, and there are regional differences in terms of energy prices. The common trends in DID estimation could not identify differences in the unobserved variables in China, but the SCM could indirectly synthesize China without ECER accountability through country comparison. Therefore, the research takes the SCM as an improvement on DID estimation.The study shows the policy effect of carbon emission intensity through Table In addition, for local governments, policy-based emission reduction and power rationing to reduce production are aggregate control methods with obvious short-term effects, which are applicable to energy intensity. However, reducing carbon emission intensity is a long-term process of technology application and diffusion in which policy implementation takes a long time, and the effect is not easy to detect. As reflected in this study, the effect of energy saving is significant, but the effect of emission reduction is insufficient. Therefore, the long-term goal of carbon peaking can be achieved only through the unremitting promotion and popularization of emission reduction technologies and the gradual development of clean production. China cannot be better than other countries in terms of technology and economic stimulus, while other countries around the world actively put into practice the Kyoto Protocol and Paris Climate Agreement to attain emission reduction targets simultaneously. Nevertheless, ECER target accountability system improvement could reinforce ECER regulation in China, bringing a unique advantage that would be hard for others to obtain.60. FDI triggered the migration of high-carbon production links from developed countries to China, making China the world factory. Over the years, FDI has formed a point-to-area industrial agglomeration belt with high energy consumption and high carbon emissions, posing a direct challenge for local regimes to achieve the goal of ECER. To balance economic development and ECER goals, China has promoted an increase in the proportion of clean power generation in the power generation energy mix and substantially has alleviated the situation of high carbon emission intensity by implementing the ECER target accountability system for local officials61 and comprehensively addressing the problem of burning too much coal in domestic socio-economic production. On the other hand, a large amount of fossil energy is used for power generation; as long as the effective proportion of coal-fired units in the power generation energy structure is reduced, the situation of high carbon emission intensity can be greatly alleviated62.After China's accession to the WTO, trade liberalization objectively exacerbated the overall rise of the country's carbon emission level40. At the beginning of the Eleventh Five-Year Plan period, coal-fired power generation accounted for 88% of China's primary energy structure. Through continuous efforts to transform the stock of coal-fired power and introduce incremental clean power generation, the proportion of coal-fired power has been reduced to slightly under 65% in 2020. Local power generation enterprises are SOEs or administratively binding enterprises that are closely related to regimes. In the process of performing energy-saving tasks, local officials have sufficient ability to mobilize power generation enterprises to actively adjust the power generation structure and not only consider current profits. The accountability system for ECER drives local officials to actively carry out the practice of institutional innovation through the carbon emission trading of power generation enterprises and clean power generation trading in the green card market to accelerate the decrease in the coal power share of power generation enterprises.To fulfil ECER's stipulated goals, local governments arrange state-owned power generation enterprises to reduce the proportion of coal power and carry out continuous adjustment and optimization of the clean power generation structureThis article studies the changes in China’s ECER after the target accountability system was implemented in local regimes. In the practice of ECER, China has shifted its new approach by implementing the ECER accountability of local regimes as an enhancing institutional mechanism. The paper observes the special method for strengthening the effect of existing ECER policies and employs DID and SCM models to estimate the policy effect of ECER accountability implementation. The research results show that changes in environmental regulation and policy adjustment have a depressing effect on energy consumption and emissions. The government has also incorporated energy conservation and emission reduction targets into its five-year plans. Therefore, emerging forms of ECER policies can be applied with local regimes’ responsibility. Bureaucracies are always paying attention to the promotion indicators listed by the central government. Their intention of promotion would facilitate the achievement of the ECER target under the guidance of accountability.This paper finds that the implementation of ECER policies strongly depends on the alignment of targets set by the accountability baton of each local regime. As economic development is the primary goal, local officials will pursue increases in GDP; when ECER indicators are included in the assessment of the target accountability system, the incentive for officials to implement emission reduction responsibility is more significant. This performance tournament features the following suggestions for further promoting ECER work:a) Authoritarian governments can decentralize ECER targets to incentivize local officials to fulfil their responsibilities rather than frequently promulgating restrictive rules and decrees. By driving officials' performance target orientation, all departments are encouraged to implement existing ECER measures and tighten restrictions to achieve the goals of ECER. Through long-term practice, China has found medium- and long-term effects of the ECER target responsibility system. Therefore, in 2015, the mayor responsibility system was upgraded to the party secretary responsibility system, which further strengthened the incentive role of local officials in the implementation of ECER. Only when the local bureaucratic system can keep its promotions consistent with the ECER goals can the positive externality effect of ECER be internalized by institutional innovation, forming political incentives to optimize methods to facilitate the achievement of ECER targets.b) The focus of promoting a further deepening of ECER in the next stage is to realize the transformation of the energy consumption structure and promote the effective replacement of the stock of traditional fossil energy with incremental clean energy. The total energy consumption level and unit energy intensity level are subject to the technical conditions in a certain period, and their decreasing trend is weaker than that of the total energy consumption level and emission intensity. Therefore, the focus of further ECER should be on reducing emissions rather than reducing total energy consumption. Many countries have seen renewable energy generation as a major opportunity to drive the carbon decoupling of economic activity. In China, clean generation is replacing the coal-fired power generation stock at a rate of approximately 1% per year. In the face of the current ratio of nearly 65% coal-fired power generation, there is still a gap between achieving a carbon peak in 2030 and carbon neutrality in 2060, and the speed of clean power generation replacement needs to be significantly increased.c) There is convergence in the setting of the periodic indicators of the ECER target accountability system. Both the overall and intensity indicators need to be adjusted based on the actual emission reduction of local conditions. To ensure the achievement of ECER targets, local officials have resorted to power rationing to avoid reaching the upper limit of annual carbon emission targets, which affects local economic development and people’s livelihoods. To avert overcorrection, local accountability systems need to set scientific and reasonable phased targets for ECER and reduce the substantial damage to the sustainability of economic growth caused by over-aggressive targets.


Twitter's popularity has exploded in the previous few years, making it one of the most widely used social media sites. As a result of this development, the strategies described in this study are now more beneficial. Additionally, there has been an increase in the number of people who express their views in demeaning ways to others. As a result, hate speech has piqued interest in the subject of sentiment analysis, which has developed various algorithms for detecting emotions in social networks using intuitive means. This paper proposes the deep learning model to classify the sentiments in two separate analyses. In the first analysis, the tweets are classified based on the hate speech against the migrants and the women. In the second analysis, the detection is performed using a deep learning model to organise whether the hate speech is performed by a single or a group of users. During the text analysis, word embedding is implemented using the combination of deep learning models such as BiLSTM, CNN, and MLP. These models are integrated with word embedding methods such as inverse glove , document frequency (TF-IDF), and transformer-based embedding. Academic literature and political debates continue to focus on the question of free speech. Hate speech is tolerated in some form or another in many countries . While hDeep learning has done a significant work in the area of sentiment analysis. So, this paper has presented the use of deep learning for analysing the hate speech against migrants and the woman. The application of this work is to identify the people or the users who are posting the messages against the woman and the migrants.The organisation of the paper is as follows: The second Global Summit on Religion, Peace and Security was conducted from April 29 to May 1, 2019, by the United Nations (UN). The summit's goal was to produce a Plan of Action to oppose hate speech and protect religious minorities and migrants  . Adama DInternational human rights treaties and soft law instruments are being used to combat hate speech directed towards refugees and migrants. Concerned about this new problem, the UN launched a comprehensive initiative that culminated in July 2018 with UN member states presenting their renewed commitment to human rights and fundamental values of international law in the form of the Global Compact for Migration. This bolstered the UN's agreement to combat xenophobia and other types of prejudice. Even though 152 nations signed the compact, far-right leaders and parties overwhelmingly rejected it, demonstrating the centrality of antimigrant sentiment in their schedule. No international treaty or convention defines hate speech, but it can be found in human rights treaties and soft laws that limit freedom of expression in general. When construed according to international law, domestic laws should give protection against hate speech to refugees, even while hate speech rules are denied domestically. International law provides a clear outline for the concept of prohibited hate speech. To substantiate this claim, this paper will demonstrate that antihate speech legislation complies with international standards on the limits of freedom of expression while also providing sufficient justification for these laws to protect migrants and refugees under international law.There are many articles based on hate speech detection, but the novelty of this work is to analyse the hate speech against the woman and the migrants using the deep learning model .Researchers employ neural networks, which are similar to the human brain in that they connect nodes that process and organise information. As a result of the usage of insults, phrases, and other disparaging statements as training data, an intelligent system can “learn” the patterns and structure of language to forecast incoming tweets and identify objectionable ones. Essential pronouns and other factors can fundamentally alter the meaning of a statement in some sentences. “According to a researcher at the University of Jaén, “with our technology and the support of language resources, we can identify expressions associated with hate speech .” A studPreviously hate speech was analyzed through machine learning algorithms. Later on, deep learning algorithms are widely used for performing the analysis. This article is also based on a deep learning approach to perform a better analysis in the hate speech analysis. In the first analysis, hate speech is classified against the woman using deep learning models and in the second analysis is to detect whether the hate speech is performed by the individual or the group of people. To perform the implementation, two different datasets are used, i.e., English dataset based on English text, and the next one is Spanish dataset based on Spanish text . The deeThe dataset split into two parts, i.e., training dataset and the testing dataset. In the training dataset, there are 31,963 records, and the testing dataset consists of 17,198 records. These are further split separately into English dataset and the Spanish dataset. The training dataset is used for building the model, and the testing dataset is used for the validation of the model.In this method, the text dataset based on English and Spanish language is classified using the deep learning model for the analysis of hate speech against woman and migrants. The word embedding is done through the glove model for performing distributed word representation In this model, firstly, the word embedding model is applied, i.e., glove . Glove eAn input layer with 600 neuronsA hidden layer with 1,600 neurons and 100 neurons activated by ReLUAn output layer with the rest of the neurons (a single neuron with sigmoid activation multilayer per function)Between each pair of layers, dropout units have been inserted, each with a probability of 0.8%. To avoid overfitting, the dropout units provide a possibility of deletion to each input neuron during trainingAll of our models have been built using the Keras libraryTwo hidden layers of a multilayer perceptron (MLP) integrate the LSTM with the MLP . The LST(i)TF-IDF (term frequency-inverse document frequency). Documents are distinct from each other based on the terms they use. Classifications are analyzed using the TF-IDF approach to determine the importance of terms. The TF-IDF score of each term or word in the document is used instead of frequency in this method. Similar to the bag of word algorithm, the TF-IDF score of each term replaces the word count.TF represents the term frequency and I  DF defines the inverse document frequency. t, d  is showing the number of terms t appears in a document d. N denotes the number of documents.In the above equation, If you want to calculate the TF-IDF score of an individual phrase inside an entire document, you can do so by multiplying the total number of documents in the document by the frequency of that term (DF) .(ii)Multilayer. Multilayer perceptron is a feedforward artificial neural network (ANN) that includes input and hidden layers and output and feedback layers. Backpropagation is used to update the weights of all nodes in an MLP. During training, nonlinear mapping is learned by utilising nonlinear activation functions and numerous layers. Nonlinear activation is used to generate the label in MLP .(iii)Support vector machine. One of the most common classification and regression algorithms is the Support Vector Machine (SVM), a supervised technique for classification and regression issues. To locate the decision border between two classes, it uses a vector space model that is as far away from the data points as possible, and the support vectors are data points near the hyperplane that divides classes , 23.(iv)XGBoost classifier. In addition to tree-based models, another sort of an ensemble model is a “boosting model.” For example, machine learning ensemble meta-algorithms for minimising bias and variance in supervised learning are known as “boosts.” They are a class of machine learning algorithms that turn weak learners into strong ones. For example, a classifier with a slender correlation with the actual categorization is said to be a weak learner (it can label samples better than random guessing).In this model, the word embedding TF-IDF model is integrated with multilayer perceptron, support vector machine, and XGBoost (extreme gradient boosting) classifier.In this proposed model, the word embedding is done through transformer model; i.e., electra and the classification are performed by using the ensemble convolutional neural network and the multilayer perceptron model.The electra model is possible to corrupt the input by replacing some tokens with (MASK) and then train a model to recreate them using pretraining approaches such as BERT. To be effective, they typically demand a considerable amount of computing power to perform well in downstream NLP tasks . A more Given the same model size, data, and computing power, the contextual representations learnt this way beat those trained by BERT. On the GLUE natural language understanding benchmark, an algorithm trained on one GPU for four days outperforms the state-of-the-art GPT (learned using 30 times more CPU) . RegardiTo perform the implementation, a python programming language is used. The evaluation parameters used for detecting the models are accuracy, precision, and the F1 score. All the models are implemented separately, and the results are compared. The model implemented using glove and the LSTM has performed better than the other states-of-the-art algorithms. In Tables Above Tables 12This paper focuses on text categorization in which two datasets are based on English and Spanish languages. These datasets are used for performing the hate speech classification against women and migrants. In the first analysis, three different types of deep learning models based on artificial neural networks are applied to the English dataset for performing the hate speech analysis, and in the second analysis, the same deep learning models are applied to the Spanish dataset. The parameters used for evaluating the model are accuracy, precision, and the F1 score. The model implemented with the transformer word embedding and the hybrid approach of the convolutional neural network and multilayer perceptron has achieved more than 95% accuracy, which is better than the other state-of-the-art algorithms. In the future work, to enhance the classification performance some more algorithms based on convolutional neural networks, capsule networks will be implemented.