Skin cancer is one of the most common cancers in humans. This study aims to create a system for recognizing pigmented skin lesions by analyzing heterogeneous data based on a multimodal neural network. Fusing patient statistics and multidimensional visual data allows for finding additional links between dermoscopic images and medical diagnostic results, significantly improving neural network classification accuracy. The use by specialists of the proposed system of neural network recognition of pigmented skin lesions will enhance the efficiency of diagnosis compared to visual diagnostic methods.Today, skin cancer is one of the most common malignant neoplasms in the human body. Diagnosis of pigmented lesions is challenging even for experienced dermatologists due to the wide range of morphological manifestations. Artificial intelligence technologies are capable of equaling and even surpassing the capabilities of a dermatologist in terms of efficiency. The main problem of implementing intellectual analysis systems is low accuracy. One of the possible ways to increase this indicator is using stages of preliminary processing of visual data and the use of heterogeneous data. The article proposes a multimodal neural network system for identifying pigmented skin lesions with a preliminary identification, and removing hair from dermatoscopic images. The novelty of the proposed system lies in the joint use of the stage of preliminary cleaning of hair structures and a multimodal neural network system for the analysis of heterogeneous data. The accuracy of pigmented skin lesions recognition in 10 diagnostically significant categories in the proposed system was 83.6%. The use of the proposed system by dermatologists as an auxiliary diagnostic method will minimize the impact of the human factor, assist in making medical decisions, and expand the possibilities of early detection of skin cancer. According to World Health Organization statistics, non-melanoma and melanoma skin cancer incidence has significantly increased over the past decade . Up to tRapid and highly accurate early diagnosis of skin cancer can reduce patients’ risk of death . When deToday medicine is considered one of the strategic and promising areas for the effective implementation of systems based on artificial intelligence . There iThere are many methods for pre-processing dermoscopic images to improve and visually highlight diagnostically significant features. One of these methods is segmentation to highlight pigmented skin lesions’ contours. Segmentation can be performed using a biorthogonal two-dimensional wavelet transform and the Otsu algorithm . Edge exThe presence of hair in dermatoscopic images can drastically change the size, shape, color, and texture of the lesion, which significantly affects the automatic analysis of the neural network . RemovinAnother way to improve the accuracy of intelligent classification systems is to combine heterogeneous data and further analyze them to find additional relationships. In database dermatology, heterogeneous data mining makes it possible to combine patient statistical metadata and dermoscopic images, greatly improving the recognition of pigmented skin lesions. The use of multimodal neural network systems ,35,36,37Despite significant progress in implementing artificial intelligence technologies to analyze dermatological data, developing neural network systems of varying complexity is relevant to achieving higher recognition accuracy. The main hypothesis of the manuscript is a potential increase in the quality of neural network systems for analyzing medical data due to the emerging synergy when using various methods to improve recognition accuracy together. This study aims to develop and model a multimodal neural network system for analyzing dermatological data through the preliminary cleaning of hair structures from images. The proposed system makes it possible to achieve higher recognition accuracy levels than similar neural network systems due to the preliminary cleaning of hair structures from dermoscopic images. The use of the proposed system by dermatologists as an auxiliary diagnostic method will minimize the impact of the human factor in making medical decisions.The rest of the work is structured as follows. The paper proposes a multimodal neural network system for recognizing pigmented skin lesions with a stage of preliminary processing of dermatoscopic images. The proposed multimodal neural network system for analysis and classification combines heterogeneous diagnostic data represented by multivariate visual data and patient statistics. The scheme of a multimodal neural network system for the classification of dermatoscopic images of pigmented skin lesions with preliminary processing of heterogeneous data is shown in The multidimensional visual data undergoes a pre-processing stage, which identifies and cleans hair structures from dermatoscopic images of pigmented skin lesions. Patient statistics also undergo a one-hot encoding process to generate a feature vector. The multimodal neural network system for recognizing pigmented lesions in the skin consists of two neural network architectures. Dermatoscopic images are processed using the specified Convolutional Neural Network (CNN) architecture. Statistical metadata is processed using a linear multilayer neural network. The resulting feature vector at the CNN output and the output signal of the linear neural network are combined on the concatenation layer. The combined signal is fed to the layer for classification. The output signal from the proposed multimodal neural network system for recognizing pigmented skin lesions is the percentage of 10 diagnostically significant categories, including a recognized dermatoscopic image.The main diagnostic method in the field of dermatology is visual analysis. Today, many imaging approaches have been developed to help dermatologists overcome the problems caused by the apperception of tiny skin lesions. The most widely used imaging technique in dermatology is dermatoscopy, a non-invasive technique for imaging the skin surface using a light magnifying device and immersion fluid . StatistThe presence of such noisy structures as hair significantly complicates the work of dermatologists and specialists. It can also cause errors in recognizing pigmented skin lesions in automatic analysis systems. Hair violates the geometric properties of the pigmented lesion areas, which negatively affects the diagnostic accuracy . Figure The most common way to solve the occlusion problem of pigmented skin lesions is to remove the visible part of the hair with a cutting instrument before performing a dermatoscopic examination. However, this approach leads to skin irritation. Also, it causes diffuse changes in the color of the entire pigmented lesion, which distorts diagnostically significant signs to a greater extent than the presence of hair itself. An alternative solution is digitalizing dermatoscopic visual data to remove hair structures. The essence of the hair pre-cleaning methods is to identify each pixel of the image as a pixel-hair or pixel-skin and then replace the pixels of the hair structures with skin pixels . PrelimiThis paper proposes a method for digital pre-processing dermoscopic images using morphological operations on multidimensional visual data. A step-by-step scheme of the proposed method is shown in Image processing of pigmented skin lesions consists of four main stages. At the first stage, the RGB image is decomposed into color components. The second step is to locate the locations of the hair structures. At the third stage, the hair pixels are replaced with neighboring pixels. The fourth step is to reverse engineer an RGB color dermatoscopic image.The input of the proposed method is RGB dermatoscopic images of pigmented neoplasms of the skin At the next stage, the original image The operator of zeroing the pixels After the operation of threshold zeroing of pixels, a morphological operation of dilatation with the The next step is to replace the pixels of the hair structure with neighboring pixels. Using the Laplace equation, pixels are interpolated from the area’s border of the selected hair structures. In this case, the pixels from the border of the hair structures cannot be changed. The last step is the reverse construction of the RGB color image from the extracted color components. For this, the color channels An example of the step-by-step work of the proposed method for identifying and cleaning hair structures from dermatoscopic images of pigmented skin lesions is shown in Today, in medicine, there is an increase in the volume of digital information due to the accumulation of data from electronic medical records, the results of laboratory and instrumental studies, mobile devices for monitoring human physiological functions, and others . PatientMetadata pre-processing is converting statistical data into the format required by the selected data mining method. Since the proposed multimodal system for recognizing pigmented skin lesions is a fully connected neural network, it must encode the data as a vector of features. A corresponding metadata information vector is generated for each image in the dataset, which depends on the amount and type of statistical information. One-hot encoding can sometimes outperform complex encoding systems . All mulSuppose the One-hot encoding is used to encode the statistic In deep learning, multimodal fusion or heterogeneous synthesis combines different data types obtained from various sources . In the For the recognition of multidimensional visual data, the most optimal neural network architecture is CNN . The inpThe dermatoscopic image includes The concatenation layer at the input receives the feature map, which was obtained on the last layer intended for processing dermatoscopic images The activation of the last layer of the multimodal neural network is displayed through the Data from the open archive of The International Skin Imaging Collaboration (ISIC), which is the largest available set of confidential data in dermatology, was used for the simulations . The maiThe modeling was performed using the high-level programming language Python 3.8.8. All calculations were performed on a PC with an Intel (R) Core (TM) i5-8500 CPU @ 3.00 GHz 3.00 GHz with 16 GB of RAM and a 64-bit Windows 10 operating system. Multimodal CNN training was carried out using a graphics processing unit (GPU) based on an NVIDIA video chipset GeForce GTX 1050TI.Preliminary heterogeneous data processing was carried out at the first stage of the proposed multimodal classification system. Dermatoscopic image pre-processing consisted of stepwise hair removal and image resizing. The removal of hair structures was carried out using the developed method based on morphological operations, presented in The pre-processing of patient metadata consisted of one-hot encoding to convert the vector format required for further mining. The coding tables for each patient metadata index are presented in CNN AlexNet , SqueezeLarge volumes of training data make it possible to increase the classification accuracy of automated systems for neural network recognition of dermatoscopic images of pigmented skin lesions. Creating large-scale medical imaging datasets is costly and time-consuming because diagnosis and further labeling require specialized equipment and trained practitioners. It also requires the consent of patients to process and provides personal data. Existing training datasets for the intelligent analysis of pigmented skin lesions, including the ISIC open archive, are imbalanced across benign lesion classes. All of this leads to inaccurate classification results due to CNN overfitting.Affine transformations are one of the main methods for increasing and balancing the amount of multidimensional visual data in each class. The possible affine transformations are rotation, displacement, reflection, scaling, etc. The selected dermatoscopic images of pigmented skin lesions include multidimensional visual data of various sizes. Different CNN architectures require input images of a certain size. Scaling using affine transformations transforms visual data into a set of images of the same size. Scaling is usually combined with cropping to achieve the desired image size.Augmentation of dermatoscopic images of pigmented skin lesions included all of the above methods of affinity transformations, examples of which are shown in New multidimensional visual data were created from existing ones using augmentation for more effective training. This allowed us to increase the number of training images. Training data augmentation has proven effective enough to improve accuracy in neural network recognition systems for medical data . When trPre-processed images of pigmented skin lesions were fed into CNN architectures. The vector of pre-processed metadata was provided to the input of a linear neural network, which consisted of several linear layers and ReLu activation layers. After passing the different input signals through the CNN and the linear neural network, the heterogeneous data passed fusion on the concatenation layer. The combined data was fed to the softmax layer for classification. The results predicted by the multimodal neural network from the test sample were converted to a binary form to construct the Receiver Operating Characteristic curve (ROC curve). Each predicted class label consisted of a combination of two characters with a length of 10 characters. The ROC curve represents the number of correctly classified positive values on incorrectly classified negative values.Following the analysis of the confusion matrices in The The results of the analysis of the McNemar test from Even though the proposed multimodal neural network system with the stage of preliminary cleaning of hair structures shows higher results in recognition accuracy compared to existing similar systems, as well as compared to visual diagnostic methods for physicians in the field of dermatology, the use of the proposed system as an independent diagnostic tool is impossible due to the presence of a false-negative response in cases of malignant neoplasms. This system can only be used as a high-precision auxiliary tool for physicians and specialists.AlexNet deep neural network architecture is superior to other architectures in the following ways: it does not require specialized hardware and works well with limited GPU; learning AlexNet is faster than other deeper architectures; more filters are used on each layer; a pooling layer follows each convolutional layer; ReLU is used as the activation function, which is more biological and reduces the likelihood of the gradient disappearing . The lisAs a result of modeling the proposed multimodal neural network system, the best recognition accuracy was 83.6%. The preliminary cleaning of hair structures and the analysis of heterogeneous data made it possible to significantly exceed the classification accuracy compared to simple neural network architectures to recognize dermoscopic images. In  CNN GoogIn , prelimiA comparison of the recognition accuracy of various multimodal neural network systems for recognizing pigmented lesions and skin with the proposed system is presented in In , the autIdentical conditions for modeling, hardware resources, image base, and many diagnostic categories used make it possible to compare the results obtained with the proposed multimodal neural network system with the stage of preliminary hair removal with the results from work. The recognition accuracy of the proposed multimodal system with the stage of preliminary hair removal on the test set was 83.6%, which is about 20.2% higher than the results of testing the system from . The maiIn , a multiThe authors of  presenteIn  proposedThe main limitation in using the proposed multimodal neural network system for recognizing pigmented lesions in the skin is that specialists can only use the system as an additional diagnostic tool. The proposed system is not a medical device and cannot independently diagnose patients. Since the major dermatoscopic training databases are biased towards benign image classifications, misclassification is possible. The use of augmentation based on affine transformations makes it possible to minimize this factor but not completely exclude it.A promising direction for further research is constructing more complex multimodal systems for neural network classification of pigmented skin neoplasms. The use of segmentation and preliminary cleaning of the hair’s visual data will help highlight the contour of the pigmented skin lesion. Distortion of the shapes of the skin neoplasm is an important diagnostic sign that may indicate the malignancy of this lesion.The article presents a multimodal neural network system for recognizing pigmented skin lesions with a stage of preliminary cleaning from hair structures. The fusion of dissimilar data made it possible to increase the recognition accuracy by 4.93–6.28%, depending on the CNN architecture. The best recognition accuracy for 10 diagnostically significant categories was 83.56% when using the AlexNet pre-trained CNN architecture. At the same time, the best indicator of improving the accuracy was obtained using the pre-trained ResNet-101 architecture and amounted to 6.28%. The use of the stage of preliminary processing of visual data made it possible to prepare dermatoscopic images for further analysis and improve the quality of diagnostically important visual information. At the same time, the fusion of patient statistics and visual data made it possible to find additional links between dermatoscopic images and the results of medical diagnostics, which significantly increased the accuracy of the classification of neural networks.Creating systems for automatically recognizing the state of pigmented lesions of patients’ skin can be a good incentive for cognitive medical monitoring systems. This can reduce the consumption of financial and labor resources involved in the medical industry. At the same time, the creation of mobile monitoring systems to monitor potentially dangerous skin neoplasms will automatically receive feedback on the condition of patients.


The mission of the Caregivers Clinic at Memorial Sloan Kettering Cancer Center (MSK) is to assure that no caregiver of an MSK patient experiencing significant distress as a result of their caregiving responsibilities goes unidentified and deprived of necessary psychosocial services. This presentation will cover the steps taken and barriers faced in the development of the Clinic, including advocating for caregivers to receive their own unique medical records. Data regarding the number of caregivers seen for psychotherapy and for medication management will be presented, as will data regarding presenting complaints and average length of care. Also included is a discussion of the challenges faced in expanding and maintaining the capacity of the Clinic, especially in the setting of the pandemic during which caregivers' use of psychosocial care at MSK is notably higher than in years past. Several current adjunct approaches to address capacity needs currently being piloted will be discussed.


Combined with the characteristics of the Chinese environmental regulation supervision system and evolutionary game theory, the spillover effect of local governments’ investment behaviour has been incorporated into their payment function to study the influence of spillover on the strategy choice of local governments and enterprises. The results show that (1) the spillover effect is one of the reasons for distortions in the implementation of environmental regulations. Whether the influence of the spillover effect on the probability of local governments choosing the strategy of strict supervision is positive or negative depends on the environmental benefit of the local government’s environmental protection investment. (2) Increasing the reward for the enterprise’s complete green technology innovation behaviour is conducive to improving the probability of the enterprises choosing the strategy of complete green technology innovation, while it reduces the probability of local governments choosing the strategy of strict supervision. Increasing punishment for enterprises’ incomplete green technology innovation behaviour is conducive to improving the probability of enterprises choosing the strategy of complete green technology innovation, but its impact on the probability of local governments choosing the strategy of strict supervision is uncertain due to the limitations of many factors. (3) Enterprises’ emission reduction capacity is positively related to the probability of the enterprises choosing the strategy of complete green technology innovation and is negatively related to the probability of local governments choosing the strategy of strict supervision. The research conclusions provide a new explanation for the distorted enforcement of environmental regulations from the perspective of the spillover of local governments’ investment behaviour. Since reform and opening up, China’s economy has grown by leaps and bounds and has become the world’s second largest economy after the United States. However, with rapid economic expansion, China’s ecological environment has been seriously damaged. In the face of the dual pressure of environmental protection and economic development, the 19th National Congress of the Communist Party of China proposed adhering to the basic national policy of ‘saving resources and protecting the environment’ and emphasized that green technology innovation is a major measure to promote the transformation of the production mode of enterprises and to realize the win-win situation of economic benefits and environmental effects. Green technology innovation refers to a series of technologies in the production process, such as improving the production process, product structure, and innovative production activities, which are conducive to reducing energy consumption, reducing pollutants and improving production efficiency . EnterprChina’s environmental policies are formulated by the central government and implemented by local governments, and there is information asymmetry in this principal–agent relationship. Local governments in various regions are motivated to distort the enforcement of environmental regulations, such as reducing enforcement, providing tax incentives and lowering environmental standards . HoweverThe existing literature focuses on the influencing factors of the game mechanism of environmental regulations between local governments and enterprises, but few studies have considered the spillover effect of local governments’ investment behaviour into the game system of environmental regulations between local governments and enterprises. Some scholars have proposed that local governments’ behavioural decisions not only affect the improvement of regional environmental quality but also influence the environmental quality of neighbouring areas . When thIn view of this, based on the positive and negative external environmental effects of local governments’ investment behaviours, this paper establishes an evolutionary game model between local governments and enterprises to identify how spillover effects influence the implementation mechanism of environmental regulations. The evolutionary trajectories of local governments and enterprises to realize the system’s evolutionary stability equilibrium strategy under different circumstances are analysed. Furthermore, through numerical simulation, the influence of positive and negative externality spillover effects of local governments’ investment behaviours, punishment and reward for enterprises’ green technology innovation, and enterprises’ emission reduction capacity on the strategy choice of local governments and enterprises is further examined. The main contribution of this paper is that the spillover effect of local governments’ investment behaviour is incorporated into the study of the game relationship between local governments and enterprises, and the influence of the spillover effect on the strategy choice of local governments and enterprises is analysed. The existing literature focuses on the influence of incentive and constraint mechanisms among different stakeholders on the strategy choice of environmental regulatory subjects, while the spillover effect of local governments’ investment behaviour has not been considered. In addition, this paper adopts the method of case analysis combined with numerical simulation based on the research objects of the governments of Hubei Province, Hunan Province, and the YT Environmental Protection Technology Company, and quantitatively explores the impact of some key factors on the strategy choice of both parties in the game to effectively control the influence of the spillover effect. The conclusion of this paper provides a new explanation for the failure of environmental regulations and is conducive to identifying factors that affect the implementation distortion of environmental regulations, which provides a policy basis for the central government to improve local governments’ environmental regulation efficiency.The implementation process of environmental regulations is the game process of local governments and enterprises . The acaIn the context of fiscal decentralization, performance appraisals based on GDP make local governments compete fiercely for resources to increase the probability of political promotion, thus affecting the impact of the implementation of environmental regulations. Due to the inevitable preference conflict between performance appraisals and residents’ welfare, local governments distort the implementation of environmental regulations . Fiscal (1)The environmental regulation strategy of the ‘race to the bottom’Most early scholars adopted the viewpoint of the ‘race to the bottom’; that is, local government competition, reduces the intensity of environmental regulations. Wilson  and Raus(2)The environmental regulation strategy of the ‘race to the top’2 emissions reduction but did not have competitive behaviour in SO2.With the deepening of the research, an increasing number of people put forward the view of the ‘race to the top’; that is, local government competition prompts local governments to increase the intensity of environmental regulations. Potoski  examined(3)The differentiated competition environmental regulation strategyA few scholars have noted that environmental regulation competition among local governments involves differentiated competition; that is, local government competition has no significant impact on regional environmental policies. Chirinko and Wilson  showed tIn our research, local governments’ behaviour refers to the supporting behaviours and preferential policies related to economic development and environmental protection. Competition among local governments causes officials in different regions to imitate or fight over policies around competition for promotion opportunities, the supply of public products, and the introduction of liquidity factors, which aggravates the spillover effect of local governments’ investment behaviour on regional development. There are many types of formal and informal connection in regional economic activities, which makes it easier for enterprises in the region to obtain information and knowledge from neighbouring regions. Therefore, the decision-making behaviour of regional local governments has mutual influence and mutual radiation, leading to a positive spillover effect and a negative spillover effect.On the one hand, the behaviour of local governments supporting local economic development has a negative externality on the environmental governance of adjacent areas, which has increased environmental pollution due to the improvement of regional production capacity. Hao et al.  found thOn the other hand, the behaviour of local governments supporting local environmental governance has improved the local environmental quality due to the reduction of environmental pollution and has a positive externality to the environmental governance of neighbouring areas. First, regional environmental regulation has a positive environmental spillover effect, which comes from the regional ‘demonstration effect’ and ‘warning effect’. Zhao et al.  found thThe spillover effect can occur horizontally or vertically, so the measure of spillover effects in the existing literature varies with the direction of spillover. In the study of vertical spillover effects, Newman et al.  used theBy combining and summarizing the existing literature, we can see that existing scholars have conducted considerable research on local government competition and environmental regulations. It is widely believed that local government competition has a significant impact on regional environmental protection enforcement investment, but there are great differences in the research conclusions. In addition to differences in index measurement, research methods and research sample selection, the key problem is the lack of in-depth research on environmental regulation transmission mechanisms, ignoring the spillover effect of local governments’ behaviour. In fact, the strategy choice of local governments competing with each other is the reaction function of each other’s behavioural decisions. When the local area increases the investment in environmental protection, the environmental quality and the neighbouring areas will also be improved. When the local area increases the investment in production, pollutant spillover will cause environmental damage to neighbouring areas.Yi  establisIn China’s administrative system, the central government is responsible for formulating environmental policies, while local governments supervise and manage enterprises’ energy conservation and emission reduction activities by implementing environmental regulations. Local governments are responsible for the economic construction and environmental protection of the region, so local governments have two types of investment behaviour. The first is economic constructive investment, which refers to local governments providing financial support for local natural resource development and infrastructure construction to encourage enterprise to actively participate in activities related to economic development. The second is environmental protection investment, which refers to local governments providing financial support to promote enterprises to conduct energy conservation and emission reduction, including special funds, energy conservation and emission reduction subsidies, and tax incentives. The behaviour of local governments in supporting local economic development has a negative externality on the environmental governance of adjacent areas, which has increased environmental pollution due to the improvement of regional production capacity. The behaviour of local governments in supporting local environmental governance has improved the local environmental quality due to the reduction of environmental pollution and has a positive externality to the environmental governance of neighbouring areas.To simplify the analysis, this paper takes market incentive environmental regulation as an example. Local governments will charge enterprises to discharge pollutants to keep their emissions within a certain range. In addition, local governments’ environmental protection investment behaviour is affected by the spillover effect of neighbouring governments’ investment behaviour.Assumption 1.Based on the work of Yi , there aand within the jurisdiction of the central government. The total investment budget of the local government is, which can be used to support the development of environmental protection and economic construction. Either party’s investment in environmental protection can bring benefits to both parties, any party’s investment in economic production can benefit itself, and the production of pollutants can reduce the benefits of the other party. Namely, the economic constructive investmenthas a negative externality, and the environmental protection investment behaviourhas positive externalities.Assumption 2.Local governments’ environmental protection investmentnot only brought environmental benefitsto local governments but also contributed to reducing the cost of enterprise green technology innovation. The cost reduction of enterprises is, whereandare the environmental benefit coefficients obtained by local governments and enterprises, respectively, andAssumption 3.If the local government strictly implements environmental regulations, the reward for an enterprise’s complete green technology innovation behaviour is, and the punishment for an enterprise’s incomplete green technology innovation behaviour is. At the same time, when the enterprise’s emission reduction rate is, the local government charges pollutant discharge feesfor the enterprise’s pollutant discharge, andis the sewage charge that the enterprise needs to pay per unit of sewage discharge .Based on the literature of Yi , the invWhen governments Combined with optimization theory according to Formula (2), the optimal environmental protection investment benefit If the local government chooses the strategy of strict supervision and the enterprise chooses the strategy of complete green technology innovation, the local government’s profit function consists of environmental investment returns According to the above description, the game payment matrix of local governments and enterprises can be obtained, as shown in An enterprise’s adaptability in choosing the strategy of complete green technology innovation is as follows:An enterprise’s adaptability in choosing the strategy of incomplete green technology innovation is as follows:The average fitness is:The dynamic equation of enterprise replication is as follows:The local government’s adaptability in choosing the strategy of strict supervision is:The local government’s adaptability in choosing the strategy of non-strict supervision is:The average fitness is:Likewise, the replication dynamic equation of the local government is as follows:According to the Malthusian equation , the groThe strategy combination, corresponding to the equilibrium point calculated by Equation (11), is an equilibrium of the evolutionary game.Proposition 1.The equilibrium point of system (11) is ,When:so the system’s equilibrium point isProof. According to equations Set According to Equation (11), the Jacobian matrix of the system can be obtained as follows Substituting the equilibrium point into equations When strategy . CombineSituation 1: When Situation 2: When Situation 3: When Situation 4: When According to the equation ofWhen the initial state of the system falls in region I, the game converges to . When the initial state of the system falls in region II, the game converges to . When the initial state of the system falls in region III, the game converges to . When the initial state of the system falls in region IV, the game converges to .Situation 5: When Situation 6: When Situation 7: When Situation 8: When Situation 9: When Based on the above dynamic evolutionary model, there are four evolutionary stability strategies for the behavioural choice of local governments and enterprises in the environmental regulation transmission mechanism. In addition, the evolutionary path of the two parties in the game is related to the game payout matrix and changes in some central parameters. The impact of the main factors related to the behavioural characteristics of local governments and enterprises on the equilibrium results of system evolution has been discussed.(1)The impact of the spillover of local governments’ investment behaviour on the choice of local governments’ environmental regulation strategy.The spillover of local governments’ investment behaviour reflects the impact of regional government environmental regulation decisions on the environmental performance of neighbouring regions. Whether the spillover effect is positive or negative related to the probability of local governments choosing the strategy of strict supervision depends on whether the spillover effect is a ‘demonstration effect’ or a ‘free rider’ on the neighbouring areas. When the environmental protection awareness of local residents is low, environmental regulations cannot effectively encourage local enterprises to consciously save energy and reduce emissions, and the environmental protection investment benefits of local governments are relatively low. Therefore, neighbouring regional governments and enterprises have ‘free-riding’ behaviours in energy conservation and emission reduction. Local governments will be more likely to choose strict supervision strategies because of the low enthusiasm of local enterprises to save energy and reduce emissions. When the environmental protection awareness of local residents is high, environmental regulations can effectively encourage local enterprises to consciously save energy and reduce emissions, and the environmental protection investment performance of local governments is relatively large. Hence, the environmental quality improvement and environmental pollution brought by the investment of local governments have a ‘warning effect’ and ‘demonstration effect’ on the environmental protection of neighbouring areas. Local governments will be more likely to abandon strict supervision strategies because of the high enthusiasm of local enterprises to save energy and reduce emissions.Proof. Please see the Proof of Proposition A1 in (2)The impact of local government reward and punishment for enterprises’ green technology innovation behaviours on the strategy choice of local governments and enterprises.The punishment and reward for enterprises’ green technology innovation behaviour by the local government is directly related to the costs and benefits of enterprises and local governments. The higher the reward for enterprises’ complete green technology innovation behaviour, the greater the green technology innovation benefits of the enterprises, and the higher the environmental protection cost of the local government. The greater the punishment for enterprises’ incomplete green technology innovation behaviour, the higher the green technology innovation cost of enterprises, and the lower the environmental protection cost of local governments. Therefore, the greater the reward, the greater the probability of enterprises choosing complete green technology innovation strategy to obtain more benefits, and the lower the probability of local governments choosing the strict regulation strategy to reduce management costs. The greater the punishment is, the greater the probability of enterprises choosing a complete green technology innovation strategy to reduce costs. The impact of punishment on the choice of the local government’s environmental regulation strategy depends on the trade-off between the environmental benefits and economic losses brought about by the punishment.Proof. Please see the Proof of Proposition A2 in (3)The impact of enterprises’ emission reduction capability on the strategy choice of local governments and enterprises.Emission reduction capability determines the difficulty of green technology innovation for enterprises. The stronger the emission reduction capability is, the more easily enterprises can develop and utilize clean technologies, and the higher the willingness of enterprises to choose complete green technology innovation. The high willingness of enterprises to engage in green technology innovation reduces the effectiveness of strict environmental supervision, and the local government will abandon the strategy of strict environmental supervision.Proof. Please see the Proof of Proposition A3 in To better describe the influence of various parameters on the strategy choice of local governments and enterprises in the transmission mechanism of environmental regulations, a combination of case analysis and numerical simulation has been adopted to quantitatively examine the influence of different parameters on the choice behaviour of both sides of the game.The 11 provinces of the Yangtze River Economic Belt regard the restoration of the Yangtze River’s ecological environment as an overwhelming task. Lake governance, especially the governance of cross regional large lakes, requires the joint efforts of all governments in the basin, realizing joint prevention and control. If only one party carries out pollution control and the other party carries out pollution discharge, it is difficult to achieve the expected effect of environmental improvement. Hunan and Hubei provinces have similar economic development and adjacent geographic positions in the central region and are two important areas adjacent to the Yangtze River Economic Belt, the ecological restoration of which plays an important role in the growth of the Yangtze River Economic Belt. Although the central government and provincial government have invested a lot of funds in lake protection and governance, the efficiency of governance is low due to the problems of cross regional sewage transfer and unclear responsibility for pollution control. Therefore, grasping the spillover effects of local government investment behavior is a prerequisite for establishing an effective joint prevention and control mechanism in the governance of trans-basin rivers.As an important environmental protection enterprise in the Yangtze River Economic Zone, YT Environmental Protection Technology Co., Ltd. is a company specializing in environmental engineering general contracting, environmental protection facility renovation, trusteeship operation, water treatment pharmaceutical series products, and environmental protection equipment research and development. Its green technology innovation behaviour is supervised and managed by the Hunan provincial government. This paper takes the Hubei provincial government, Hunan provincial government, and YT Environmental Protection Technology Co., Ltd. as the research objects and focuses on the influence of the competition between the Hubei provincial government and the Hunan provincial government on the choice of Y T Environmental Protection Technology Co., Ltd.’s green technology innovation strategy.For the sake of evolutionary game analysis, the key stakeholders are simplified as Hunan province local government and the YT company, focusing on the behavioral spillover effect of the Hubei province local government. Based on in-person investigations and data collection from the relevant government departments and enterprises, we use the following series of parameter values as the benchmark: the supervision intensity of local governments choosing strategy of no-strict supervision as According to the benchmark value, the influence of different key parameters on the evolutionary trajectory of the two sides of the game is numerically simulated and analysed as shown in (1)(i)As seen in (ii)As shown in (2)(3)The impact of punishment (i)When (ii)When (4)From the perspective of local government competition, the spillover of local governments’ investment behaviour has been incorporated into the objective function of the local governments to construct an evolutionary game model between local governments and the enterprises. The following conclusions are obtained.(1)(I)strict supervision and complete green technology innovation;(II)non-strict supervision and complete green technology innovation;(III)strict supervision and incomplete green technology innovation; and(IV)non-strict supervision and incomplete green technology innovation.Under the constraints of environmental regulation, spillover effects have a significant impact on the payment function of local governments, leading to distortions in the implementation of environmental regulations. When the payment function changes, there are four evolutionary stability strategies in the evolutionary game system of local governments and enterprises:(2)When the environmental benefit of the local governments’ environmental protection investment behaviour is less than the threshold, the spillover of local government investment behaviour may lead to the reduction of regional environmental protection investment for the effect of ‘competition to the bottom’ and ‘free riding behaviour’, which enhances the dependence of the improvement of environmental quality on the strict supervision of local governments. Hence, the probability of local governments choosing the strict supervision strategy increases with the increase in the spillover effect. When the environmental benefit of the local governments’ environmental protection investment behaviour is greater than the threshold, clean technology and environmental pollution in external areas may encourage local enterprises to increase investment in energy conservation and emission reduction for the ‘demonstration effect’ and the ‘warning effect’. This leads to the low dependence of the improvement of environmental quality on the strict supervision of local governments. Hence, the probability of local governments choosing a strict supervision strategy decreases with the increase in the spillover effect of strict supervision.(3)The reward for enterprises’ complete green technology innovation behaviour increases enterprises’ profits, while punishment for enterprises’ incomplete green technology innovation behaviour increases enterprises’ costs. The choice of complete green technology innovation strategy is the best choice to increase revenue and reduce costs for enterprises. Hence, with the increase in reward and punishment, the probability of enterprises choosing complete green technology innovation strategy gradually increases.(4)The reward for enterprises’ complete green technology innovation behaviour increases the environmental governance costs of local governments and reduces the willingness of local governments to strictly supervise. The impact of punishment on the probability of the local government choosing strict supervision strategy is uncertain.(5)The stronger enterprises’ emission reduction capability is, the greater the willingness of enterprises to save energy and reduce emissions, leading to a decline in the willingness of local governments to strictly supervise.First, the central government should formulate an environmental governance supervision system according to the differences in the environmental awareness and environmental responsibility of residents in different regions, making full use of the ‘demonstration effect’ of regional environmental governance behaviour spillover to produce a positive impact on regional environmental governance decision-making. Within the region, the central government should unify regional environmental management laws, standards, and policy systems, establish regional pollution compensation mechanisms, benefit coordination mechanisms, and ‘green GDP’ competition mechanisms, and improve environmental information sharing mechanisms, joint early warning mechanisms, and demonstration effect mechanisms.Second, local governments should formulate differentiated reward and punishment mechanisms for green technology innovation in combination with the differences in environmental quality in different regions. Local governments should guide enterprises to actively carry out green technology innovation activities through appropriate fiscal and tax preferential policies and increase support for energy conservation, emission reduction and pollution prevention technology research and development. To form an effective incentive and restraint mechanism for green technological innovation, reward should be increased in areas with better environmental quality and punishment should be strengthened in areas with poor environmental quality.Third, local governments should formulate differentiated supervision systems based on individual differences in the emission reduction capabilities of different companies. Through incentive means, enterprises with strong emission reduction capacity should be guided to give full play to the ‘demonstration effect’, strengthen the cooperation of regional enterprises in the research and development and utilization of green technology, speed up the elimination of ineffective production capacity, and improve environmental production performance. At the same time, local governments should strengthen the supervision of the energy-saving and emission-reduction behaviours of enterprises with poor emission reduction capabilities, not only to avoid the effect of ‘competition on the bottom line’ among enterprises but also to prevent the transfer of heavily polluting enterprises between different regions.Based on evolutionary game theory, this paper studies the impact of external government investment spillover on the strategic choice of local governments and enterprises in regional competition and suggests a direction for improving the transmission mechanism of environmental regulation. However, in the construction of the game relationship between environmental regulation subjects, only the key factors in the behavioural characteristics of local governments and enterprises are considered. Future research will combine risk preference, environmental awareness, and social responsibility factors to examine the impact of local government competition on the strategic choice of game players.


This review focuses on peripheral forms of hereditary hearing loss and how these impairments can be studied in diverse animal models or patient-derived cells with the ultimate goal of using the knowledge gained to understand the underlying biology and treat hearing loss.Inherited forms of deafness account for a sizable portion of hearing loss among children and adult populations. Many patients with sensorineural deficits have pathological manifestations in the peripheral auditory system, the inner ear. Within the hearing organ, the cochlea, most of the genetic forms of hearing loss involve defects in sensory detection and to some extent, signaling to the brain  Impairment of hearing can be due to several factors including environmental insults, the effects of aging, and hereditary defects. Of these three forms, the most common form is due to aging , which c1 Of the non-syndromic forms, more than 120 genes have been implicated in hearing loss and the majority of cases involve recessive mutations in which both copies of the gene are mutated. Approximately a third of the cases are dominant, requiring only one copy to be mutated. As with aging, sometimes the middle ear is affected, leading to a loss of conduction of sound. However, the majority of mutations are sensorineural in nature, mainly affecting the inner ear, with many having developmental or functional consequences for hair cells.Hereditary hearing loss is one of the most common sensory deficits in humans affecting one out every 500 newborns . The levEfforts to understand the etiologies associated with hearing loss have been ongoing for several decades. The purpose of this review is to highlight a few recent studies of non-syndromic hereditary hearing loss that illustrate the different types of pathology found in the inner ear. The following studies focus on three different tissue or cell types of the cochlea, namely the stria vascularis, sensory epithelium and the afferent neurons of the spiral ganglion. These studies were also chosen based on the variety of animal models or the use of human-derived cell lines to determine the function of the genes. Due to the inaccessibility of the inner ear in patients, a basic scientific approach with models is necessary to gain a better understanding of the nature of the defects caused by genetic variants that are associated with human hearing loss.An important prerequisite for hair-cell function is the presence of an ionic environment that is conducive to excitation. Unlike other extracellular fluids throughout the body, the fluid inside the scala media of the inner ear is exceedingly rich in potassium ions . The higAlthough marginal or “dark” cells found in the vestibular inner ear of vertebrates are thought to perform a similar function to the stria vascularis, the electrochemical potential created is substantially lower and defined cell layers are not evident . FurtherHGF). Despite the name suggesting a specific role in the liver, this extracellular ligand has been implicated in many biological processes involving cell proliferation, survival, and motility. More surprisingly, the only disease in humans associated with mutations in HGF is non-syndromic hearing loss. In mice, the knock-out of Hgf results in embryonic lethality, whereas a conditional knock-out in the inner ear does indeed result in deafness . Zebrafish have an inner ear that is anatomically similar to the vestibular portion of human ears. For hearing, they use the saccular end-organ. The sensory hair cells in the zebrafish inner ear rely on many of the same basic components necessary for hearing and balance in humans, and well over a dozen models of human hearing loss have been generated and studied in detail [for comprehensive reviews of studies in zebrafish see As an illustration of (i) using a non-rodent model, the zebrafish, to study human hearing loss, and (ii) the ability to compare the findings with this animal model to that of the mouse model, this review will focus on two recent studies of transmembrane inner ear  play a more critical role in hearing  projecting out of the bone-encased inner ear into the hindbrain. The fibers of the afferent neurons in the cochlea along with the cell bodies comprising the spiral ganglion are shown in yellow in DIAPH1, TMPRSS3 and PJVK  and the vertebrate inner ear. Of the genes required for auditory function in fruit flies, 20% have human orthologs implicated in deafness  in the antenna harboring the Johnston’s organ caused deficits in gravity sensing and balance in adult flies. At the cellular level, the sensory scolopidia were disorganized, including abnormalities of internal structures such as actin bundles, and there was a loss of synapses formed by scolopidia neurons in the fly brain. To test the whether the Gln104Leu variant was causative, the authors compared rescue of the behavioral defects in the drk fly mutant by expressing the wild type human gene and the human Q104L variant and found that the variant form of GRAP was ineffective at rescuing the fly phenotype. The ability to rescue the deficits of an animal model with the corresponding human gene and test newly identified variants is an important and much needed approach for establishing causality of mutations found in the genome of hearing loss patients.A recent study of a novel deafness gene serves as an excellent example of the use of flies to study hereditary hearing loss . In thisin vitro experiments. The authors found that sensory neural-like cells heterozygous for the S1400G mutation had defects in later steps of differentiation and physiological responses. These defects were accompanied by a decrease in microtubule dynamics. Most of the heterozygous S1400G cells had shorter neurites in contrast to the CRISPR-corrected cells or sibling-derived cells. To further confirm their findings, the authors engineered a mouse model expressing the same dominant mutation. Heterozygous mutant mice displayed moderate yet progressive hearing loss. In addition, primary cultures of the spiral ganglion neurons exhibited similar decreases in neurite length and altered electrophysiological properties.The study of animal models is invaluable for understanding the potential etiology caused by mutations. Nevertheless, with the recent advances in stem cell biology, it is also possible to take cells from patients such as blood cells and reprogram them into cells that resemble those in the auditory system. in vitro studies. This approach is an invaluable method for assessing the pathological consequences of a mutation in human cells. Although the technology is in its infancy, another potentially useful method is to generate human organoids of the inner ear. These 3D structures contain cell types that resemble hair cells and the sensory neurons that innervate them (The above study highlights the utility of reprogramming patient-derived cells into a desired cell type for ate them . Inner evia genomic sequencing and to establish animal models or study patient derived cells is a key step toward selecting the appropriate therapeutic approaches to ameliorate hearing loss.In summary, hereditary sensorineural forms of hearing loss primarily affect the tissues and cell types of the inner ear that are vital to sensing sound and transmitting signals to the brain. Our knowledge of the genetics of hearing loss is growing as the pace of identifying novel human mutations associated with impairments in hearing is rapidly increasing . This inDrosophila are highly advanced, the existence of an obvious ortholog of a human deafness gene is not always the case. In addition, extrapolating the pathological defects in fly mutants to potential defects in human patients can be challenging due to the very different structures of the hearing organs in flies. With respect to zebrafish, some deafness genes may be duplicated due to the large-scale duplication of approximately 40% of the genome in teleost fish during evolution. Depending on the expression pattern of the gene duplicates, it may be necessary knock out and analyze two genes instead of one. Also, fish do not have a cochlea; questions about the structures or tissues present only in the mammalian cochlea cannot be addressed. In mice, the need for dissection and cochlear explants to study the cellular defects makes the work more challenging. Generally, research with this particular animal model tends to be more costly and time consuming. Branching out to the use of human stem cells and organoids to study hearing loss is certainly exciting and gaining traction. Whether in vitro differentiated cells truly resemble desired cell types or how well the organoids recapitulate the environment of the inner ear is, however, not clear. To date, generating auditory hair cells from stem cells has yet to be achieved. Despite the above shortcomings, animal and cell models have been very valuable for studies of human hearing loss and continuing efforts with these models will undoubtedly yield more insights into the defects and pathology at the molecular, cellular and physiological level.The choice of animal or cell model is dictated by several factors. Although the genetic methods in Aside from helping patients navigate hearing loss, research with animal models and patient-derived cells increases our basic understanding of how the inner ear works. These studies also add fascinating insights of how this remarkable sensory organ evolved and they provide clues about strategies that are employed to suit the auditory needs of a particular animal. On the whole, the interplay between basic and translational research is a fruitful one and offers hope to patients with hearing loss.The author wrote the manuscript and confirms being the sole contributor of this work and has approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Systemic Lupus Erythematosus (SLE) is a heterogeneous autoimmune disease characterized by hyperactive immune responses leading to severe and potentially life-threatening organ damage. Recent work indicates that in many patients increased interferon-driven responses are the root of the increased immune responses and the first therapy directed against the Type I Interferon receptor was recently approved for the treatment of SLE .A genetic polymorphism in purine nucleotide phosphorylase (PNP), which catalyzes the hydrolysis of adenosine and inosine to adenine and hypoxanthine, respectively, is strongly associated with the risk for development of SLE in patients with high levels of Interferon In this issue of EBiomedicine Hesse and colleagues report that, although CD73 expression remains relatively unchanged, the enzymatic activity of CD73 is markedly reduced on the surface of B cells from patients with SLE The authors speculate that the reduction of adenosine in the extracellular milieu of the B cells of these patients would lead to increased activity of the immune system, a finding that could predispose to the development of SLE. Nonetheless, it is unclear whether diminished enzymatic activity contributes to the development of SLE or is a result of SLE disease activity. It is also tempting to speculate that since CD73 is GPI-linked, like cell surface complement-regulatory proteins, that secondary alterations in the plasma membrane could lead to altered expression on the cell surface with diminished enzymatic activity. It would also be interesting to know whether the reduced activity of CD73 is associated with increased disease activity or manifestation of disease (skin vs kidney for example).Nonetheless, these questions aside, the authors have made an interesting finding that could suggest a complementary mechanism for the overactivity of SLE lymphocytes and the resultant autoimmunity. These findings complement earlier observations of the effect of changes in purine metabolism which offer a potential metabolic basis for SLE.Dr Cronstein is Chair of the Scientific Advisory Board and holds stock in Regenosine, LLC, a company that has licensed technology patented by his team and assigned to NYU Grossman School of Medicine.


This paper introduces for the first time the equal intercept transformation radar chart—an improved form—to the assessment of soil environmental quality of Nanling commodity grain base. The equal intercept transformation radar chart, a visual graphical data analysis method, translates data from a numerical to graphical format. This visualization enables data presentation, analysis process and results stick out a mile and is capable of fully retaining information contained in data and excavating it in depth from geometry. Moreover, it overcomes pertinently the main defect of the conventional radar chart that the evaluation result depends heavily on the order of arrangement of indicators. The results indicated that the soil environmental quality at depths of 0–60 cm in the low mountain area of the Nanling commodity grain base was the second grade, while that in the hilly and plain areas were both first grade. The indicators of poor soil environmental quality in the low mountain area were exogenous Cd and endogenous As; those in the hilly area were exogenous Cd and endogenous As and Hg; and that in the plain area was exogenous Cd. The results were in line with the actual situation of the study area. Soil quality integrates inherent and dynamic soil properties and is influenced by land use and management practices that interacts with the soil system2. Soil environmental quality, as an important component of soil quality, reflects the level of harmful substances in the soil. The scientific, accurate and comprehensive assessment of the soil environmental quality of the study area has important significance for planning land resources rationally, developing high-standard farmland, enhancing characteristic agriculture and improving the quality and efficiency of agricultural production4.Nanling important commodity grain base is an important component of the Wan Jiang Economic Belt and is a national high-standard farmland demonstration area that produces high-quality rice and vegetables. The selection of planting patterns and the consistent production of high crop yields are largely controlled by the soil properties and quality of the base. Soil quality can be defined as the capacity of a specific type of soil to sustain plant and animal productivity, maintain environmental quality and support human health and habitation within natural or managed boundaries8. The commonly used methods of soil environment quality assessment include the single factor index method, comprehensive index method, fuzzy mathematics method, multivariate statistical analysis and artificial neural network method.Many methods and various models have been used for soil quality assessment12. Weissmannová and Pavlovský13 provided a review of assessments of soil quality using various indices. The indices were divided into individual indices, and total comprehensive indices and the calculation formulas for every index, along with the classes of contamination or risk of soil indicated by the corresponding index value, were presented. This method can only provide the grade of soil quality and is unable to display the difference in indicator content, thereby losing some unique information originally present in the data.The comprehensive index method has been successfully used to assess soil quality in many regions, at different scales and under different agricultural management practices.14 applied the fuzzy mathematical method to the environmental risk assessment of soil at a petroleum-contaminated site in China and distinguished the primary environmental risk in the soil. This method considers the fuzziness of evaluation, but the determination of fuzzy weight is subjective, which directly affects the reliability of evaluation results. Singh et al.15 performed an environmental risk assessment of heavy metal pollution using multivariate analysis in the soils of Varanasi, India, and identified the principal contaminants. However, this method has shortcomings in terms of classification and consistency checks. Liu et al.16 assessed the soil quality of soil polluted with heavy metals in Tai Yuan city based on the support vector machine method and provided a classification of the soil quality. This type of intelligent algorithm has a strong ability to build mapping relationships, but the model training and computation processes are complex.Hu et alA radar chart, which refers to charts that resemble navigation radar graphics and are also known as spider charts, is a graphical method of data analysis. In this method, the value of multiple related attributes are drawn by a certain method; then, through analysis of drawn charts, the subject of analysis can be comprehensively evaluated. Radar chart are mainly used in the evaluation of an enterprise's financial condition, operation risk assessment and so on.17 applied the radar chart method to audit the economic benefits of two companies, obtained evaluation results, and analyzed the reasons to provide corresponding suggestions.Du.18 applied a radar chart to distinguish basalt tectonic environments and trace mineral source areas and analyzed its applicability and ability to achieve certain effects. Zhang19 compared and analyzed the environmental quality of different regions and different years using the radar chart method and obtained a comprehensive environmental index. In the assessment of soil environmental quality, the use of radar charts is still rare. Besides, there is a major weakness in traditional radar chart method that the evaluation result varies wildly from one order of arrangement of indicators to another.In the fields of the Earth sciences and environmental quality, the radar chart method has rarely been used: Zhang et al20, not to mention application of it to study of soil environmental quality.The equal intercept transformation radar chart could effectively address this disadvantage by adding equal intercept axes. There are very few works published on the equal intercept transformation radar chartIn order to verify the applicability of equal intercept transformation radar chart and improve the evaluation results, this paper introduced originally the equal intercept transformation radar charts in the assessment of the environmental quality of shallow soil in different landforms and depths in the Nanling commodity grain base. In the assessment, the equal intercept transformation radar chart area was used to represent the soil environmental quality level.23.Unlike other assessment methods of soil environment quality in common use, the equal intercept transformation radar chart, as a visual graphical data analysis method, translates data from a numerical to graphical format. This visualization enables data presentation, analysis process and results intuitive and is capable of fully retaining information contained data and examining it in depth from geometry. Meanwhile, the equal intercept transformation radar chart is totally independent of the orders of arrangement of indicatorsThis study could broaden the scope of application of equal intercept transformation radar chart and improve the evaluation of soil environmental quality further.The equal intercept transformation radar charts of soil environmental quality at different depths in the low mountain area, hilly area and plain area of the study area are shown Figs. The area of an equal intercept transformation radar chart represents the soil environmental quality. The areas of the above equal intercept transformation radar charts are shown in Table The areas of the soil environmental quality equal intercept transformation radar charts of various geomorphic units at different depths were compared with the standard radar chart. If the measured area is less than the standard radar chart area of the first grade, the soil environmental quality level of the corresponding geomorphic unit and corresponding depth is classified as the first grade. If the area is between the standard radar chart area of the first grade and that of the second grade, the soil environmental quality level of the corresponding geomorphic unit and corresponding depth is classified as the second grade. According to this, the soil environmental quality level in each depth on each geomorphic unit can be obtained , hilly areas (II) and plain areas (III). The soil types in the study area are mainly acidic paddy soils.The site is an important part of the Wan Jiang Economic Zone. Nanling County is the main grain-producing area in Anhui Province, and rice and tea are abundant in this site. Scientific evaluation of soil environmental quality is therefore critical to high-standard farmland planning and development in this site.20. Its basic elements include: first, N rays drew with the same angle from the same origin as figure axis respectively represent the N indicators of the evaluation objects; second, a fixed length line segment was cut on the bisector of every two adjacent index axes, i.e. “equal intercept”; third, With the coordinates of each index value, the N points are made on the corresponding axis; last, the N points and N ends of intercepts are connected successively by line segments to form a 2N-side polygon, equal intercept transformation radar chart.The equal intercept transformation radar chart is an improved form of conventional radar chart by adding equal intercept axesIt is suitable for the comprehensive evaluation of an object composed of several indicators. In the application, the distances from the origin to the end of different axes should not vary too much. If the gaps between different indicators are too large, it needs to be scaled by a certain method so that the corresponding length of the line segments on the graph is in the same order of magnitude. The values represented by the coordinate ranges and unit lengths of different axial directions may be different to suit the actual values of different indicators.This paper used 1962 groups of soil samples collected from a 1:5 million land quality geochemical survey and selected the eight indicators of Cd, Hg, As, Cu, Pb, Cr, Zn and Ni according to the People's Republic of China soil environmental quality standard (GB15618-1995 and GB15618-2008 referred) to explore the application of equal intercept transformation radar charts in the assessment of the environmental quality of shallow soil in different landforms and depths in the Nanling commodity grain base.The average values of each index of soil samples at different depths in different geomorphic areas of the study area were calculated, and equal intercept transformation radar charts were drawn accordingly. The standard values of soil environmental quality given by GB15618-1995 were also drawn on the charts. In the drafting of the charts, instead of directly using each indicator's content, the data were multiplied properly to ensure that the contents of different indicators were on the same order of magnitude.Then, these drawn radar charts were analyzed. First, a single indicator analysis was carried out to separately calculate the environmental quality levels of the soil indicators at different depths in different geomorphological areas. Second, the area of each equal intercept transformation radar chart, which represents the comprehensive soil environmental quality, was calculated (see Formula n represents the number of indicators (n = 8 in this paper); Ai represents the value of the i indicator/axis; L represents “equal intercept” (L = 150 in this paper); In the formula,


This study was aimed at determining the effect of microstructure on the macro-mechanical behavior of a composite solid propellant. The microstructure model of a composite solid propellant was generated using molecular dynamics algorithm. The correlation of how microstructural mechanical properties and the effect of initial interface defects in propellant act on the macro-mechanics were studied. Results of this study showed that the mechanical properties of propellant rely heavily on its mesoscopic structure. The grain filling volume fraction mainly influences the propellant initial modulus, the higher the volume fraction, the higher initial modulus. Additionally, it was found that the ratio of particles influences the tensile strength and breaking elongation rate of the propellant. The big particles could also improve the initial modulus of a propellant, but decrease its tensile strength and breaking elongation rate. Furthermore, the initial defects lowered the uniaxial tensile modulus, tensile strength, and the relaxation modulus of propellant, but did not affect the relaxation behavior of the propellant. Composite solid propellant is a high-energy composite material that is widely used as a power source for launch vehicles and various strategic and tactical missiles. The mechanical properties of the composite solid propellant greatly affect the survivability and combat capability of the missile. Moreover, composite solid propellant is composed of the hydroxyl terminated polybutadiene (HTPB) as a binder matrix and solid particles such as aluminum powder (AL), ammonium perchlorate (AP), and hexogen (RDX) as filler. The macro mechanical properties of composite solid propellant strongly depend on the mesostructure and its multi-scale physical process under an external load. Early research on composite solid propellants is mostly based on continuum mechanics to obtain the constitutive relationship of the composite solid propellant . HoweverNumerous experimental investigations have been conducted in recent years to explore the micromechanical properties and failure mechanisms of composite solid propellants. D. Bencher  and Liu With the development of computational technologies, Matouš and Inglis  develop The mechanical properties of the bonding interface between the particles and matrix are important factors that could affect the macro stress-strain relationship of propellant. Based on the characteristics of meso-damage of propellant, Li  introducElsewhere, Han  found thThese described studies considered that the mesoscopic composition of propellant is intact but various forms of initial defects existing in the production process of propellant were not considered. The existence of these defects may not only affect the macro mechanical properties of propellant but also affects the combustion characteristics during engine ignition. There are few studies on the effect of initial defects on the mechanical properties of propellant. It has been reported that He  studied The formula and component information of a composite solid propellant were shown in It was found that the number ratio of different particles is related to their corresponding particle size. According to the size distribution of AP particles in propellant obtained through a real test given in the literature , the num2 × 4410 μm2. Similar to the experimental observation results, it was found that the particles were randomly and evenly distributed, closely staggered, while the small particles were distributed in the gap of large particles  The mechanical properties of HTPB propellant depend heavily on its mesoscopic structure and the random distribution of particles hardly affects its macro mechanical properties. The simulation results present the initial modulus of the composite solid propellant increases with the increase of the particle filling volume fraction. The different particle ratio significantly affects the tensile strength and fracture elongation of the propellant. Although the existence of large particles improves the initial modulus of the propellant, it reduces its tensile strength and fracture elongation. (2) The main forms of initial defects were analyzed using a scanning electron microscope of the initial section of HTPB propellant. The filling models with different initial interface defect contents are constructed to predict the uniaxial tension and stress relaxation process. It was found that the initial defect is the main reason for the decrease of the initial modulus, relaxation modulus, and tensile strength of the composite solid propellant. However, the relaxation characteristics of the composite solid propellant will not disappear with the increase of the initial defects.