Due to the prevalence of COVID-19, providing safe environments and reducing the risks of virus exposure play pivotal roles in our daily lives. Contact tracing is a well-established and widely-used approach to track and suppress the spread of viruses. Most digital contact tracing systems can detect direct face-to-face contact based on estimated proximity, without quantifying the exposed virus concentration. In particular, they rarely allow for quantitative analysis of indirect environmental exposure due to virus survival time in the air and constant airborne transmission. In this work, we propose an indoor spatiotemporal contact awareness framework (iSTCA), which explicitly considers the self-containing quantitative contact analytics approach with spatiotemporal information to provide accurate awareness of the virus quanta concentration in different origins at various times. Smartphone-based pedestrian dead reckoning (PDR) is employed to precisely detect the locations and trajectories for distance estimation and time assessment without the need to deploy extra infrastructure. The PDR technique we employ calibrates the accumulative error by identifying spatial landmarks automatically. We utilized a custom deep learning model composed of bidirectional long short-term memory (Bi-LSTM) and multi-head convolutional neural networks (CNNs) for extracting the local correlation and long-term dependency to recognize landmarks. By considering the spatial distance and time difference in an integrated manner, we can quantify the virus quanta concentration of the entire indoor environment at any time with all contributed virus particles. We conducted an extensive experiment based on practical scenarios to evaluate the performance of the proposed system, showing that the average positioning error is reduced to less than 0.7 m with high confidence and demonstrating the validity of our system for the virus quanta concentration quantification involving virus movement in a complex indoor environment. The worldwide COVID-19 pandemic has brought about many changes in our daily lives and struck a devastating blow to the global economy. It is widely recognized that airborne transmission serves as the primary pathway for the spread of COVID-19 via expiratory droplets, especially in indoor environments ,3,4. SomContact tracing in indoor environments can complement the ones used in outdoor environments to enable comprehensive digital contact tracing. However, indoor contact tracing imposes unique technical challenges due to virus concentrations and unreliable GNSS signals in indoor environments . The virAlthough the virus concentration will gradually decrease due to inactivation, deposition, and air purification after the virus-laden droplets are exhaled, the poor air exchange rate, superspreaders, and more virulent variants will keep it at a relatively high concentration for a long time in an indoor environment ,12. The To be precisely aware of the amount of the virus one is exposed to and to detect both direct and indirect contacts, an indoor spatiotemporal contact awareness (iSTCA) framework is proposed. Since the virus concentration (at different times in the same area) is not the same because of the dispersion and diffusion of the virus and human movements, we employed a self-contained PDR technique to calculate the human trajectory with accuracy and further achieve the location and time of the expelled virus droplets for the quantitative measurement of the concentration at any time in different spots. Moreover, based on the acquired changing virus concentration and reliable trajectories, the exposure time and distance of both direct and indirect contacts can be derived via cross-examination to realize quantitative spatiotemporal contact awareness.To accurately present the virus concentrations at different times, we established quantitative virus concentration changes in various areas of indoor environments at different times by infected individuals. The viral-laden droplets were continuously released during the expiratory activities, moving forward. During the movements of viral-loaded droplets exhaled by infectious individuals at different locations and times, the virus instances met in certain spots at certain times and contributed to the calculation of the concentration. Finally, the concentration of each virus instance was integrated.We properly selected PDR for the acquisition of the trajectory to conduct contact awareness without requiring extra infrastructure or being affected by coverage limitations compared with other indoor positioning techniques.We considered various landmarks to calibrate the accumulative error for trajectory achievement by using PDR. A custom deep neural network using bidirectional long short-term memory (Bi-LSTM) and multi-head convolutional neural networks (CNNs) with residual concatenations were designed and implemented to extract temporal information in forward and backward directions and spatial features at various resolutions from built-in sensor readings for landmark identification.Additionally, we demonstrate the effectiveness of the proposed Bi-LSTM-CNN classification model for landmark identification through empirical experiments, as well as the performance of our proposed iSTCA system for quantitative spatiotemporal contact analytics.Our main contributions are as follows:The remainder of this paper is organized as follows. The related work about contact awareness and indoor localization techniques, including PDR, is reviewed in Contact tracing is used to identify and track people who may have been exposed to a virus due to the prevalence of many infectious diseases in our society. To conduct contact tracing, it is necessary for the infected individuals to provide their visited locations and people whom they encountered based on the specific definitions of meetups for different diseases. Instead of interviews and questionnaires via traditional manual tracing, technology-aided contact tracing can track people at risk conveniently and intelligently. To reduce the spread of COVID-19 effectively, digital contact tracing, which generally depends on applications installed on smartphones, has been developed in both academia and industry, using various technologies, such as GNSS, Bluetooth, and Wi-Fi.There are typically two approaches for encounter determinations, peer-to-peer proximity detection-based and geolocation-based. Peer-to-peer proximity can be estimated by the received signal strength (RSS) of wireless signals, such as Bluetooth and ultra-wideband (UWB), and the distance between two devices in geolocation-based approaches can be precisely derived from the cross-examination after obtaining the accurate location and trajectory with the help of localization techniques using various technologies, such as global positioning system (GPS), Wi-Fi, and PDR.Some systems based on peer-to-peer proximity using Bluetooth or BLE have been implemented, and part of them are deployed by the governments of various countries, such as Australia (COVIDSafe), Singapore (Trace together), and the United Kingdom (NHS COVID-19 App) due to their ubiquitous embedding in mobile phones . Among tTo achieve accurate geolocation in contact tracing, plenty of localization systems have been researched with the joint efforts of researchers and engineers in the past based on GNSS, cellular technology, radio frequency identification (RFID), and quick response (QR) code . GNSS caOne of the ultimate goals of contact awareness systems is to estimate the risk based on the recorded encounter data . MoreoveThe aforementioned contact tracing research usually only considers the static virus concentration without considering the exposure to the environmental virus and dynamism in the virus concentration. Moreover, in contrast to the qualitative estimation of exposure risks that can be achieved in previous works, there is a lack of sufficient quantitative awareness about the concentrations of contracted viruses. Such awareness would be useful in our daily lives to protect ourselves from virus infections.Virus-encapsulating secretions are continuously exhaled and aerosolized into airborne virus-laden particles with infectivity from daily expository activities. There is a great difference between the size and number of droplets expelled, depending on their origin locations in the respiratory tract . The timThe viral loads of virus-containing droplets change after leaving the human expiratory tract with airborne transmission and a combination of environmental factors. In particular, the viral load emitted is expressed in terms of the quanta emission rate  [t 50 Hz) ,36. It it 50 Hz) ,37.For the quantitative evaluation of the virus quanta concentration, the precise spatial distance and temporal distance between two individuals should be efficiently estimated. To reach this objective, a variety of indoor positioning techniques have been proposed for various scenarios. The widely studied fingerprinting-based method relies on the latest fingerprint database that needs to be precisely updated in time. In addition to the time-consuming and labor-intensive collection and re-establishment, the instability of RSS due to environmental uncertainties poses another challenge to the accuracy . MoreoveSince PDR does not need additional equipment or a pre-survey, it has a wide range of potential applications for the indoor positioning of pedestrians. It relies on the inertial sensors extensively existing in mobile devices, e.g., smartphones, to acquire information about the user’s movements, which are then combined with the user’s previous location to estimate the present position and further achieve complete trajectory. The equation utilized for location estimation is as follows:destrian .As mobile technology continues to evolve, a growing number of physical sensors are being installed in smartphones and, thus, various combinations of sensors can provide increasingly rich information, which makes PDR more feasible and accessible. A typical PDR consists of three main components: step detection, step-length estimation, and heading estimation .Step detection. As the most popular method for accurate step detection, peak detection is employed in this paper, which relies on the repeating fluctuation patterns during human movement. Using the smartphone’s accelerometer to determine whether the pedestrian is stationary, or walking is straightforward as it directly reflects the moving acceleration. The magnitude of acceleration on three dimensions artphone . A peak Stride length estimation. Various linear and nonlinear methods are proposed to estimate the step length, which varies from person to person because of different walking postures determined by various factors, including height, weight, and step frequency. Therefore, it is not easy to precisely construct the same step-length estimation model. Some researchers assume that the step length is a static value affected by the individual characteristics of different users. On the contrary, the empirical Weinberg model estimates the stride length according to the dynamic movement state, which is closer to reality [ reality . The modach step .Heading estimation. Heading information is a critical component for the entire PDR implementation, which seriously affects localization accuracy. To avoid the accumulative error in the direction estimation based on the gyroscope, and short-term direction disturbances based on the magnetometer, the combination of the gyroscope and magnetometer is typically adopted for heading estimation [timation . The curtimation . As theytimation . The rotAlthough PDR methods can estimate the location and trajectory of pedestrians, low-cost inertial sensors built into smartphones provide poor-quality measurements, resulting in accuracy degradation. Moreover, the cumulative error, including the heading estimation caused by the gyroscope and step-length estimation error caused by an accelerometer, could be produced in the long-term positioning using PDR, increasing the challenge of precise localization collection. Therefore, it is necessary to prepare the reference points with the correct positions known during the movement to reduce the accumulated errors when the user passes. Spatial contexts, such as landmarks, can be properly chosen to calibrate the localization error based on the inherent spatial information without additional deployment costs. Landmark is defined as a spatial point with salient features and semantic characteristics from its near environment in indoor positioning systems, such as corners, stairs, and elevators . These fLandmark identification involves classifying the sequences of various sensor data recorded at regular intervals by sensing devices, usually smartphones, into a well-defined landmark, which has been extensively regarded as a problem of multivariate time series classification. To address this issue, it is critical to extract and learn the features comprehensively to determine the relationship between sensing information and movement patterns. In recent years, numerous features have been attained in many studies on certain raw signal statistical aspects, such as variance, mean, entropy, kurtosis, correlation coefficients, or frequency domains via the integration of cross-formal codings, such as signals with Fourier transform and wavelet transform . MoreoveTo facilitate feature engineering and improve performance, artificial neural networks based on deep learning techniques have been employed to conduct activity identification without hand-crafted extraction. Deep learning techniques have been applied in many fields to solve practical problems with remarkable performance, such as image processing, speech recognition, and natural language processing, to solve practical problems ,51. Manyeptively . In our More importantly, the convolution operation in CNN can efficiently capture the local spatial correlation features by limiting the hidden unit’s receptive field to be local . CNN conrections .Therefore, both Bi-LSTM and CNN are involved in capturing the spatial and temporal features of signals for landmark identification. The architecture of the proposed landmark identification is shown in Exhalation and inhalation respiratory activities are constantly alternating , and droplets are continuously being released from the respiratory tract with a horizontal velocity during the process of exhalation with the same direction as the movement of the human. The particles exhaled at each moment will continue to move forward, starting from the user positions when they are expelled. The viral droplets exhaled from the infectious host are transported and dispersed into the ambient airflow before finally being inhaled by a susceptible person. Each exhalation lasts several seconds , in which a long distance can be traveled for those who are in motion, and the initial position of droplets expelled cannot be accurately estimated in an indoor environment. Therefore, once complete, the exhalation period is divided into many short-term  particle ejections. Because the interval is short, the continuous virus exhalation process can be converted into an instantaneous process, i.e., the virus is released instantly at the beginning of each interval. The virus-laden droplets expelled at different intervals maintain independent and identical motion patterns and the initial positions of the particles released in each interval can be regarded as the locations of the people at the initial moments. The virus-containing particles maintain a uniform motion of initially horizontal velocity  and an Android application installed. The application can periodically read and store the readings of 11 channels  as the user walks along the prescribed routes at a normal speed in the experimental area. Moreover, participants are required to hold their smartphones at chest level, which is a reasonable position where participants can record extra information to facilitate data processing. Indeed, it is recommended that they record the timestamp and the identification of the passing landmark to construct the dataset for the landmark identification model training.The proposed landmark recognition model was extensively evaluated by a series of experiments and implemented using the Keras framework with the TensorFlow backend to minimize the cross-entropy loss. The model was performed using the collected data with 3863 samples. The dataset was divided into training (70%) and testing (30%) sets, randomly, without overlapping. There were a total of 11 landmarks, including 7 corners, 2 stairs, and 2 elevators.Moreover, the model configuration  was selected as the optimizer during the gradient descent. Other training hyperparameters were also evaluated and their recognition accuracies are presented in Following the considered model configuration and optimal training hyperparameters, the accuracy curve and loss curve of the training and testing processes are illustrated in Moreover, to evaluate the proposed network more comprehensively, further comparisons were conducted on other deep neural networks  with the same depth and training hyperparameters as shown in The path shown as the red line in As mentioned above, we regard all virus particles exhaled every 0.1 s during exhalation as virus instances. There will be many virus instances expelled during the entire movement of an infector. During the transmission of each instance, a uniform motion with a velocity of 3.9  and the device’s status variation . In addition, a large amount of power of the smartphone is consumed during the indoor positioning process, resulting in the smartphone being overheated.Technology-assisted virus exposure tracking approaches are increasingly being adopted to mitigate and tame the epidemic. In view of the complexity of quantifying virus exposure due to human movement and airborne dispersion of virus particles, we propose iSTCA, a self-containing contact awareness approach that exploits PDR-based techniques. Quantitative information support directly concerned with risk assessment is provided for self-protection and epidemic control. More precisely, to reduce and calibrate the accumulative errors of trajectories based on landmarks, we apply Bi-LSTM and multi-head CNN with residual concatenation to long-term dependency in forward and backward directions and extract local correlations at various resolutions for landmark identification. The proposed method exploits the trajectories of people with viral-laden droplets exhaled and the transmission and attenuation of viruses in the air to quantify the virus quanta concentration in an indoor environment via spatiotemporal analytics for prevention and sanitization. In future work, we will continue studying the landmark identification model with different devices and various attitudes of the device and conduct further research on the exploration of other advanced deep neural networks and fusion algorithms. We will consider employing wearable devices, such as smartwatches and smart bands, to replace mobile phones for power saving in indoor positioning. Moreover, we plan to apply the proposed techniques for the development of services in developing communities without reliable digital infrastructure.


The liver is the central metabolic organ of the body. The plethora of anabolic and catabolic pathways in the liver is tightly regulated by physiological signaling but may become imbalanced as a consequence of malnutrition or exposure to certain chemicals, so-called metabolic endocrine disrupters, or metabolism-disrupting chemicals (MDCs). Among different metabolism-related diseases, obesity and non-alcoholic fatty liver disease (NAFLD) constitute a growing health problem, which has been associated with a western lifestyle combining excessive caloric intake and reduced physical activity. In the past years, awareness of chemical exposure as an underlying cause of metabolic endocrine effects has continuously increased. Within this review, we have collected and summarized evidence that certain environmental MDCs are capable of contributing to metabolic diseases such as liver steatosis and cholestasis by different molecular mechanisms, thereby contributing to the metabolic syndrome. Despite the high relevance of metabolism-related diseases, standardized mechanistic assays for the identification and characterization of MDCs are missing. Therefore, the current state of candidate test systems to identify MDCs is presented, and their possible implementation into a testing strategy for MDCs is discussed. Metabolism-disrupting chemicals (MDCs) are environmental chemicals that can alter metabolic processes thereby influencing the onset of metabolic diseases such as obesity, type II diabetes T2D), or fatty liver. Historically, such chemicals have been first termed obesogens by Grun and Blumberg and they further hypothesized that susceptibility to obesity starts during development and can be influenced by specific endocrine-disrupting chemicals (EDCs) ,2. With D, or fatThe liver is the central organ of glucose and fatty acid metabolism, reached by enterally absorbed nutrients and xenobiotics via the portal vein. Compounds and metabolites that have entered the body through other routes of exposure are transported to the liver via the hepatic artery. Branchings of the two blood vessels converge in the periportal areas of the so-called liver lobules, the functional units of the liver, from where blood flows through the sinusoids towards the central vein. Sinusoidal endothelial cells are specialized, fenestrated liver cells that allow contact between the blood and the hepatocytes surrounding the sinusoids. The space between sinusoids and hepatocytes, termed space of Disse, harbors two other cell types of the liver, namely Kupffer cells and Ito cells. Kupffer cells are the resident macrophages of the liver, whereas Ito cells are stellate cells, required for fat and vitamin A storage .Most of the liver’s metabolic functions are executed by hepatocytes. They sense and respond to endocrine signals from adipose tissue, stomach, pancreas, intestine, thyroid, adrenal gland, skeletal muscle, and brain, as well as to liver-specific signaling molecules  7]. In . In 7]. Energy metabolism is among the most prominent functions of the liver. In the fed state, the liver responds to blood levels of glucose and insulin. Hepatic glucose is converted to glycogen (glycogenesis) for storage purposes and metabolized to pyruvate that either serves as an energy supply via mitochondrial oxidation or is used to synthesize fatty acids (FAs) through de novo lipogenesis . FAs froIndividual signaling molecules trigger downstream signaling cascades by acting on specific receptors. Those molecules, including insulin, leptin, ghrelin, glucagon, and catecholamines, activate metabolic pathways in hepatocytes by acting on the cells via receptors located on the cell surface ,19,20,21PPARG is only weakly expressed in the human liver, compared to adipose tissue pyrene (BaP) result from incomplete combustion of organic material. PAHs are mostly activators of AhR and some compounds from this group are known for their mutagenic and carcinogenic potential . Affectipression .Pparg and its target genes in adipocytes leading to increased body and liver weight . I. I189]. In order to refine animal testing, different strategies can be followed. First, additional techniques may be employed to increase the information yielded from tissue samples after a study has been conducted following the established guidelines. With respect to metabolic alterations, the potential number of metabolic intermediates to be measured appears almost infinite and a complete overview of this topic is far beyond the scope of this work. Such metabolic analyses may use different experimental platforms and include targeted strategies to measure a single metabolite or a panel of pre-defined metabolites. Exemplarily, gas chromatography-based analysis of triglyceride levels in liver tissue is listed as a targeted method that is suited to gain quantitative information about metabolites highly relevant in hepatic steatosis . AnotherIn vitro studies with human cell cultures are an alternative to animal testing, avoiding ethical issues and providing opportunities for high-throughput testing yielding mechanistic information without the problem of inter-species differences. A plethora of human liver cell lines are available, and numerous biochemical assays exist which are capable of recording changes in enzyme activities, metabolites, transcription factor activation, the activity of signaling cascades, or the expression of genes and proteins. Knowledge about the molecular mechanisms leading to a certain adverse outcome is a prerequisite to establishing a meaningful mechanism-based testing strategy. In this regard, the AOP concept is a sequential chain/network of causatively linked key events (KE) at different levels of biological organization, connecting a molecular initiating event (MIE) to an adverse outcome ,102. AOPIn order to replace, refine and reduce (3Rs) animal testing, the ECHA developed a read-across assessment framework (RAAF) to make use of relevant information from tested substances to predict the properties of the target . This apThere is accumulating evidence that some chemicals contribute to metabolic disorders, both in laboratory animals and in humans. The current, mainly animal experiment-based testing strategies and guidelines applied in different fields of regulation, however, do not cover metabolism-related endpoints very well, thus posing a need for the development and validation of further testing methods for MDC assessment. This can be achieved based on increased knowledge of molecular mechanisms of toxicity, put together in AOPs as a basis for the development of test systems for individual modes of action, and subsequent implementation of in vitro tests as a testing battery for metabolic endocrine disruption. This will help to further improve risk assessment and consumer safety, along with the possibility to reduce the use of animals in toxicological testing.


Adversarial examples present a severe threat to deep neural networks’ application in safetycritical domains such as autonomous driving. Although there are numerous defensive solutions, they all have some flaws, such as the fact that they can only defend against adversarial attacks with a limited range of adversarial intensities. Therefore, there is a need for a detection method that can distinguish the adversarial intensity in a fine-grained manner so that subsequent tasks can perform different defense processing against perturbations of various intensities. Based on thefact that adversarial attack samples of different intensities are significantly different in the highfrequency region, this paper proposes a method to amplify the high-frequency component of the image and input it into the deep neural network based on the residual block structure. To our best knowledge, the proposed method is the first to classify adversarial intensities at a fine-grained level, thus providing an attack detection component for a general AI firewall. Experimental results show that our proposed method not only has advanced performance in AutoAttack detection by perturbation intensity classification, but also can effectively apply to detect examples of unseen adversarial attack methods. Deep learning technology has demonstrated excellent performance and has played a key role in many fields, such as finance, medical care, and public safety ,2,3,4. HFrom an attack perspective, researchers are working on exposing the vulnerabilities of DNNs to explore their mechanisms and interpretability. There are many ways to classify attack methods, which can be divided into white-box, gray-box, and black-box attacks according to the degree of information acquisition of the attacked model or system. In a white-box attack, the adversary has complete knowledge of the DNN, including its design, weights, inputs, and outputs. Specifically, the generation of the adversarial instances involves resolving an optimization issue guided by the gradient of a model. Common white-box attacks include gradient-based attacks ,10 and oThe defense works are trying every means to solve exposed or potential loopholes to ensure the reliability and trustworthiness of DNNs in practical applications. There are numerous ways to categorize defense strategies, which can be separated into intrusive and non-intrusive methods depending on whether the protected model is modified. Intrusive methods mainly include modifying model regularization loss ,16 and aMany adversarial defense strategies have already been developed, but as far as we can tell, they all have flaws. For instance, they may only be effective against adversarial examples with a specific range of perturbation intensities or may result in relatively high accuracy loss for clean inputs. In other words, even when defenses have been deployed, deep learning systems are still susceptible to attacks outside the range of an effective defense. The problem with limited defense range is shown at the top of The main steps of the proposed FAD method are as follows: first of all, through the statistical observation of the spectrum of clean samples and adversarial examples with different intensities, this paper proposes an approach based on amplifying high-frequency components to improve the distinguishability of adversarial examples. The procedure is to use the Haar discrete wavelet transform (DWT) to decompose the high-frequency and low-frequency components, amplify the high-frequency components, and then use the inverse discrete wavelet transform (IDWT) to create the reconstructed image. Then, through the experimental observation of DNN to distinguish adversarial examples and refer to the existing methods of using DNN to detect adversarial examples, this paper proposes to use DNN to classify the perturbation intensity of the reconstructed image. This paper designs a 16-layer network based on the residual block structure  to achieBy studying the pattern of various intensity perturbations of AA in the feature space, the proposed FAD could extend to the fine-grained categorization of perturbation intensity of additional attack methods . Our proposed method has a strong detection capability and can correctly classify the intensity of adversarial examples generated by different attack methods. The average classification accuracy of the proposed FAD technique, which detects different intensities of different adversarial attacks under the To the best of our knowledge, FAD is the first fine-grained adversarial perturbation intensity classification method, and is a non-intrusive adversarial detection method.The FAD approach, which amplifies the high-frequency portion of the image, provides cross-model generalization capabilities as well as the ability to detect unseen and various mechanism adversarial attacks.We empirically demonstrate the feasibility of fine-grained perturbation intensity classification for adversarial examples, providing a detection component for general AI firewalls.The main contributions of this paper are as follows:The rest of this paper is organized as follows. In this section, we review and summarize some existing methods for adversarial attacks and adversarial defenses. Furthermore, we briefly discuss the characteristics of these existing methods and the advantages of our proposed method.x and J is the neural network’s loss function, and y is the corresponding real label. Numerous algorithms for adversarial attacks have been created by researchers. Goodfellow et al. proposed the fast gradient sign method (FGSM) , believit, and x as the origin and the radius On this basis, Madry et al. improved the step size and the number of iterations that increase in the opposite direction of the gradient sign, and proposed the projected gradient descent attack (PGD) . Its genw, transforming the problem of optimizing the perturbation w by defining: Different from PGD, Carlini et al. proposed an optimization-based attack called a CW attack . The CW jth iteration, jth iteration, then the updated step size of APGD is:jth iteration generated by original PGD, and For the lack of diversity in attacks such as PGD, Croce et al. proposed two improved PGD methods and combined them with FAB  and SquaAdversarial training and network modification are two common examples of intrusive defense. When Goodfellow et al.  proposedNon-intrusive defense is mainly divided into input transformation defense and adversarial detection. Among them, the input transformation defense preprocesses the input samples, and then inputs the processed image into the classifier to make it output correctly. Mustafa et al.  used supAdversarial detection methods divide the input samples into clean samples and adversarial examples, and reject the adversarial examples to input the classifier. Tian et al. proposed a sensitivity inconsistency detector (SID) , which uOur proposed FAD is a non-intrusive method that has stronger cross-model generalization ability than intrusive methods. In contrast to input transformation defenses in non-intrusive methods, our method does not degrades the classification performance for clean samples. Moreover, compared with detection methods in non-intrusive methods, our method can not only distinguish whether an input sample is adversarial or not, but also fine-grained classify its intensity under the This paper introduces powerful AA adversarial examples  in the tCurrently, there is no unified conclusion on the distribution characteristics of different adversarial examples. In the existing work, some studies posit that the adversarial perturbation is concentrated in the high-frequency region ,38,39,40It is not difficult to find that all the spectral differences are more obvious in the high-frequency region (four corners), while the difference in the low-frequency region is slightly weaker. Especially in the spectrum difference between the AA attack samples with Some works utilize the features of the last few layers of DNN to train shallow detection networks ,30,31,32In this low-dimensional feature space, adversarial examples with While humans primarily employ low-frequency components to identify images, DNN can integrate high-frequency and low-frequency components of images for classification processing. This paper designs the FAD’s workflow n is the number of intensities of the set adversarial perturbations). This dataset consists of raw data (label 0) and corresponding adversarial examples . In order to train the detector, we first train a base classifier model on a regular  dataset as usual, and then use the AA attack against the base classifier to generate adversarial examples of different intensities for each data point of the training set. A balanced multivariate classification dataset that is To evaluate the effectiveness of the proposed FAD, we adopt four classic adversarial attack methods  may be because it has learned the common features of adversarial examples in high-frequency regions. Further, some mechanism similarities between AA, PGD, and FGSM may result in a similar distribution of the final optimized adversarial examples. The similarity between CW and AA is small, which may account for the slightly diminished effectiveness of detecting unseen CW adversarial examples.This work generates adversarial examples of various intensities against GoogLeNet   is higher than that of using other attack examples (or Gaussian noise samples).This paper designs experiments to compare the adversarial intensities (clean samples and AA examples) classification effect of our proposed 16-layer network . In addition, combining our method with defense methods applicable to different intensities has the potential to increase the proportion of correctly identified frames among several consecutive frames, improving the stability and reliability of DNN continuous decision-making. For future studies, we intend to investigate a more accurate distinguishing of different intensities of adversarial examples in the transform domain to obtain a more general fine-grained categorization of adversarial example intensities.


Innovation in the healthcare profession to solve complex human problems has always been emulated and based on solutions proven by nature. The conception of different biomimetic materials has allowed for extensive research that spans several fields, including biomechanics, material sciences, and microbiology. Due to the atypical characteristics of these biomaterials, dentistry can benefit from these applications in tissue engineering, regeneration, and replacement. This review highlights an overview of the application of different biomimetic biomaterials in dentistry and discusses the key biomaterials  and biomimetic approaches  that have been researched to treat periodontal and peri-implant diseases in both natural dentition and dental implants. Following this, we focus on the recent novel application of mussel adhesive proteins (MAPs) and their appealing adhesive properties, in addition to their key chemical and structural properties that relate to the engineering, regeneration, and replacement of important anatomical structures in the periodontium, such as the periodontal ligament (PDL). We also outline the potential challenges in employing MAPs as a biomimetic biomaterial in dentistry based on the current evidence in the literature. This provides insight into the possible increased functional longevity of natural dentition that can be translated to implant dentistry in the near future. These strategies, paired with 3D printing and its clinical application in natural dentition and implant dentistry, develop the potential of a biomimetic approach to overcoming clinical problems in dentistry. As technological innovation continues to push the limits of what is possible in the healthcare field, nature has played an important role in addressing human problems and challenges for thousands of years. Humans have always drawn inspiration and guidance by studying and emulating designs, processes, and strategies based on solutions proven by nature. This practice can be referred to as “Biomimicry”, which involves understanding the way natural systems work and using that understanding to create new technologies and materials that mimic their behavior, structure, or function. The practice of biomimicry can be dated as far back as the start of human civilization, with one of the earliest known records of biomimicry being silk fabric from the silkworm. Biomimicry has always played an influential and important role in human development as it allows for more efficient and effective technologies that can also lead to materials and systems becoming more biocompatible and sustainable. The application of biomimicry also spans a wide range of fields, including dentistry, architecture, renewable energy, biomechanics, materials sciences, and microbiology .The use of biomimicry in dentistry has been extensive, with the development of dental materials that have been researched to be resistant to degradation and biocompatible, such as hydroxyapatite (HA), casein-phosphate, and bioactive glasses ,3,4. OthA major focus has now shifted to using the advantages of atypical 3D-printed biomimetic biomaterials to mimic the function of the periodontal ligament (PDL) in the periodontium through means of tissue engineering, regeneration, and replacement. The PDL consists of a group of fibrous tissues that attach teeth to the surrounding bone in the jaw. These tissues play a critical role in maintaining the stability of natural dentition and allowing them to function properly. However, with the current prevalence of infection in the oral cavity, such as periodontitis in natural dentition and peri-implantitis in dental implants, many recent studies have elucidated potential preventative solutions to either reverse or reduce the effects of both periodontitis and peri-implantitis using different biomimetic biomaterials for the purpose of PDL engineering, regeneration, or replacement ,10. In tThe use of biomaterials in the fields of medicine and dentistry has encompassed a range of widely researched and applied concepts since the 1950s . The advMechanical considerations, such as the load bearing, fracture resistance, tensile strength, hardness, modulus of elasticity, and wear resistance to abrasion and corrosion, all play a vital role in the ideal function of biomaterials ,14 SimilThe natural environment of the human body is harsh and can expose biomaterials to varying levels of pH and humidity from bodily fluids, which may result in corrosive and toxic responses owing to inadequate corrosion resistance and degradation of the biomaterial . In addiBiomimetic biomaterials, as the name suggests, are biomaterials which mimic the tissues of the body anatomically and physiologically to generate an effect similar to that of the native tissues. Numerous materials that mimic the constituents of the periodontium, particularly bone, are being used for the regeneration of the periodontium. Due to its favorable biological activity and biocompatibility, HA is commonly used as a scaffold in artificial bone . The conThe periodontium is a group of tissues  that support and keep the teeth in place. Each one of these tissues has unique histological and biological characteristics . PeriodoInvestigations into the use of conventional regenerative methods, such as guided tissue regeneration (GTR), have been limited and unpredictable in clinical trials. This surgical approach works by reflecting the mucoperiosteal flap, removing the causative causes, and blocking the defective area with biocompatible biomedical materials placed as a barrier under the gingiva to prevent epithelial tissue migration ,24. The Tissue engineering is another periodontal regeneration strategy. In order induce tissue regeneration, stem/progenitor cells, scaffolds, and bioactive agents must be used to create biomimetic systems. This technique can be classified, according to its biomaterial usage, as either scaffold-free or scaffold-based . ScaffolAnother highly important aspect of periodontium regeneration is controlling the release patterns of drugs and growth factors from carriers to obtain sustained long-term effects while avoiding negative biological effects. Therefore, periodontal tissue regeneration requires the administration of a combination of bioactive chemicals to keep infection and inflammation under control, while boosting cell proliferation and differentiation ,30. ReceA cell-sheet approach, which is a novel scaffold-free tissue engineering method that transplants cultured stem/progenitor cells without carriers, has only been able to regenerate simple structures ,29. CemeMytilus genus, which they can use to attach themselves to many different inorganic and organic surfaces within their marine environments. MAPs consist of as many as 20 different proteins that entail some collagenous and adhesive plaque proteins that all work together in the mussels’ adhesive process, which consists of a series of byssal threads that anchor the organism to its substrate. One of the key chemical properties of these MAPs is their high catechol group content, consisting of a six-membered aromatic ring with two hydroxyl groups attached , and DOPA-containing mussel foot proteins 3 and 5 , all expressed in methylotrophic yeast, P. pastoris [P. pastoris a suitable expression system of adhesive proteins, allowing for a higher production rate and improved post-translational modifications for the function of the protein, in addition to the greater cohesion of proteins in acidic pH 3–5. Successful attempts have also been made to produce mussel-inspired synthetic polymers, such as the more notable Polydopamine (PDA), through a simple dip-coating method in an aqueous solution of dopamine [There have been many studies that have elucidated the importance of DOPA, and in particular, their potential application in cross-linking reactions of catechol groups via oxidation to aid in the rapid solidification of concentrated solutions of DOPA for attachment onto substrates . There ipastoris . The autdopamine . The impAs the technology of bioadhesives improves, their applications in the dental field have become an important step in replacing the deteriorating key anatomical structures of the periodontium, that include periodontal tissues to teeth or regenerating surrounding bone loss near dental implants, in cases of periodontitis and peri-implantitis, respectively. The current research has been primarily focused on the applications of functionalized PDA with respect to guided bone regeneration (GBR) and GTR paired using notable Food and Drug Administration (FDA) cleared biocompatible and biodegradable 3D polymer scaffolds, such as polylactic acid (PLA) or poly(ε-caprolactone) (PCL) ,40,41. T2+ channels. The results show that the scaffold was able to facilitate cell adhesion and, with the help of the catechol groups of PDA, confer an anti-inflammatory effect and accelerate periodontal bone healing under diabetic conditions.In one study, investigators examined a PCL-based nanofibrous membrane scaffold with and without an incorporated biomimetic PDA nanoscale coating. The reported results demonstrated that using a patterned PDA coating allowed an adherent substrate for cells, but also induced the osteogenic differentiation of cultured PDLSCs . In anotAs the technology and clinical application of 3D-printed scaffolds improve within dentistry, an important consideration that must be acknowledged is 3D printing or additive manufacturing. Although 3D printing has become very useful in creating complex scaffold shapes, they are not without their limitations . Some ofE. coli and Streptococcus aureus (S. aureus). Another study investigated the immobilization of dopamine and cefotaxime sodium (CS) onto the surface of Ti via copolymerization, which was able to prevent the adhesion and proliferation of E. coli and Streptococcus mutans (S. mutans) [PDA coatings have also been extensively demonstrated to enhance the expression of bone-related genes, osseointegration, cell adhesion and proliferation, and aid in periodontium regeneration. Another unique aspect of PDA coatings that extends their application beyond the periodontium is their ability to possess antimicrobial activity in conjunction with their existing properties. Peri-implantitis has become a topic of discussion due to its ambiguous etiology, with multiple theories that propose a biological, genetic, and biomechanical mechanism that results in the onset of peri-implantitis. Currently, the exact mechanism behind peri-implantitis is still not entirely understood. One study approached the problem of peri-implantitis from a biological approach, detailing biofilm formation and bacterial colonization as contributing factors . Investi mutans) . Mendhi  mutans) . The comA common theme among many in vitro experiments in the field of bioadhesives, particularly the use of MAPs and PDA, is that they are primarily used as surface coatings for substrates or 3D scaffolds to help immobilize various proteins or genetic materials of interest . Very feThe key chemical properties of MAPs have been utilized effectively by many researchers to improve and develop novel bioadhesive technologies in the realm of tissue engineering. PDA has become fundamental in immobilizing the key proteins, genetic material, antibiotics, and inorganic and organic antibacterial agents. However, a complete understanding of MAPs and PDA-mediated techniques are still required, as the exact mechanisms of their physiochemical properties remain elusive. Further research should be conducted on the interactions between PDA-coated substrates and cells, including tissue stem cells and bone-resorbing mediators. The application of MAPs in tissue engineering has become increasingly widespread and it will be important that the prior clinical application of these novel bioadhesives undergo rigorous human clinical trials to ensure their safety and efficacy in the short- and long-term.Due to MAPs’ distinct ability to retain their adhesive properties in a moist environment, they can also be employed in various clinical procedures that require the proximity of adherends. The anti-microbial properties of MAPs and the increased differentiation of osteoblasts by MAPs make them more suited as biomaterials for restoring the periodontium.MAPs, as a surface coating for implants, have been theorized and evaluated for the facilitation of osseointegration. A statistically significant difference in the differentiation of bone marrow stem cells  has been observed with the MAP coating of implants . MoreoveDue to their tenacious nature, MAPs have also been considered in GBR as an adjunct to conventional bone grafts. The effect of mussel-inspired PDA coatings on calcium silicate cement was studied on mesenchymal stem cells. The coating enhanced cell adhesion and promoted ECM secretion, including collagen I and fibronectin. In addition, there was a statistically significant increase in cell-adhered proteins, such as integrin f1 and pFAK, which resulted in accentuated cell proliferation . AdditioMAPs also improve the handling characteristics of GBR membranes as the need for secondary fixation devices (bone screws or bone tacks) or techniques  is eliminated. However, MAPs have not been shown to increase the rate of bone regeneration. The use of tissue adhesives may cause resorbable collagen membranes to degrade prematurely . An imprMAPs can also be used as adhesives for the primary closure of wounds. Mussel foot proteins (MFPS)-inspired double cross-linked hydrogel adhesives have been assessed for use as a potential adhesive for biomedical applications. Subcutaneous implantation demonstrated the biodegradability and biocompatibility of the double cross-linked hydrogel . The appMAPs may be used as an adhesive medium for local drug delivery (LDD) in sites of incipient periodontal lesions. Similarly, MAPs may be employed for the retention of periodontal dressings following surgical procedures, such as flap or mucogingival surgery. Extensive in vitro and clinical studies will be required for the validation of these applications. At present, the utilization of MAPs to regenerate and replace key periodontium structures has been extensively studied, with the same techniques reported in these studies, the application of MAPs can also extend into the field of implant surface treatments and bone graft coatings with immense potential, but will require human studies for commercialization.The current advancements in bioadhesive technology have helped provide an extensive understanding of the mechanism by which MAPs and PDA adhere to many different substrates. This has resulted in 3D scaffolds with increased bioactive potential and PDA-functionalized coatings that can initiate bone and tissue cellular differentiation. Preliminary research has exploited these biomimicking properties to enhance tissue and bone repair and regeneration in the periodontium, thus serving as a promising therapeutic measure. Although it mandates substantial experimentation and clinical trials, further applications of MAPs in the fields of implant dentistry remain dynamic.


Medial maxillary fractures are defined as fractures of the medial aspect of the maxilla, that is, fractures of the nasomaxillary buttress. The diagnosis of medial maxillary (nasomaxillary buttress) fractures is challenging because of its similarities with nasal, and naso-orbito-ethmoidal (NOE) fractures.The patients included a 17-year-old Japanese man and a 37-year-old Japanese woman with facial injuries. Swelling of the affected cheek, nasal hemorrhage, periorbital ecchymosis, and C-shaped deviation of the nasal dorsum with normal nasal tip and root position were observed. Mild hypesthesia was noted in the affected region innervated by the left infraorbital nerve. Telecanthus, double vision, eye movement disorder, epiphora, trismus, tooth fracture, and malocclusion were absent in both cases.Based on clinical signs and imaging findings, the patients were diagnosed with medial maxillary (nasomaxillary buttress) fracture.The 17-year-old man underwent a reduction of the medial aspect of the maxillary bone with the treatment of concomitant fractures, and the 37-year-old woman did not request treatment.Medial maxillary (nasomaxillary buttress) fractures are not included in any current classification of the maxillary fracture patterns. As medial maxillary (nasomaxillary buttress) fractures are similar to nasal, and NOE fractures, careful differential diagnosis is required before selecting the surgical procedure to be performed because the treatment of concomitant fractures is also necessary. In typical cases, depression of the lateral wall of the nasal cavity morphologically results in a C-shaped deviation of the nasal dorsum, with narrowing of the nasal cavity, nasal obstruction, and nasal hemorrhage as symptoms. However, different symptoms manifest corresponding to the region to which the fracture extends because the medial surface of the maxillary bone joins with other bones, including the nasal, ethmoid, and lacrimal bones. If a medial maxillary (nasomaxillary buttress) fractures extend toward the frontal process of the maxilla, the medial orbital wall including the lacrimal and ethmoid bones, and the nasal bone are affected. If the fracture extends continuously to the orbital floor, a blow-out fracture develops. Surgical treatment of medial maxillary  fractures requires an accurate diagnosis and careful planning in each case because the treatment of concomitant fractures is also necessary. Recently, Yoshioka et al and Hwang et al have only reported 8 and 15 cases of this fracture, respectively. Medial maxillary (nasomaxillary) fractures are not included in any current classification of the maxillary fracture patterns, which include Le Fort-type, sagittal, or fracture of the alveolar process. Therefore, the clinical conditions and diagnosis of medial maxillary (nasomaxillary buttress) fractures are still not understood by many surgeons and radiologists. We present 2 cases of medial maxillary (nasomaxillary buttress) fracture in terms of differential diagnosis and pathogenesis.Four primary processes such as frontal, palatine, zygomatic, and alveolar processes form a thick portion of the maxillary bone, and the thicker portion forms a buttress extending from the maxillary alveolar process to the frontal cranium. Three vertical buttresses are present in each part of the maxillary bone which increases the strength of the midface to protect the cranium. Medial maxillary fractures are defined as fractures of the medial aspect of the maxilla, that is, fractures of the nasomaxillary buttress. Medial maxillary (nasomaxillary buttress) fracture was initially described by May et alA 17-year-old Japanese man was bruised on his face by a hard baseball and visited the Department of Oral and Maxillofacial Surgery, Gunma University Hospital. Swelling of the left cheek and nasal hemorrhage were observed. C-shaped deviation of the nasal dorsum was observed, but the tip and root of the nose remained in a fairly normal position. Mild hypesthesia was noted in the region innervated by the left infraorbital nerve. Telecanthus, double vision, eye movement disorder, epiphora, trismus, tooth fracture, and malocclusion were absent. In the horizontal view on computed tomography (CT), a fracture line was noted in the anterior wall of the maxilla and the bone fragment was depressed. The medial aspect of the maxillary bone  deviated inside and medially on three-dimensional (3D)-CT. A fracture of the maxillary bone region constituting the orbital floor was also observed. We had a definitive diagnosis of a compound fracture of the left mesial maxillary (nasomaxillary buttress) and blow-out fracture. As the reduction of the lateral nasomaxillary buttress by closed reduction from the nasal cavity alone was difficult, open reduction was performed under general anesthesia, through a subciliary incision and an oral vestibular incision. Reduction of the medial aspect of the maxillary bone was performed by inserting an elevator into the maxillary sinus. For the fixation of the orbital rim and border of the pyriform aperture, an absorbable plate was used. For the bone defect of the orbital floor formed by the deviation of the medial aspect of the maxillary bone and blow-out fracture, a sheet prepared with only cancellous bone from the anterior superior iliac crest was transplanted. The nasal dorsum improved aesthetically, and the disorder of the inferior orbital nerve had resolved at the 1-year postoperative follow-up  fracture. Surgery was not performed because the patient did not request a treatment Fig. . However, this fracture cannot be diagnosed based on this deviation alone because a similar deviation is present in simple nasal fractures and NOE fractures. In medial maxillary (nasomaxillary buttress) fractures, the tip and root of the nose remain in a fairly normal position because the nasal bones are not disturbed.Medial maxillary (nasomaxillary buttress) fractures are characterized by a C-shaped deviation of the nasal dorsum. Yoshioka et al, Anderson et al, and Hillstrom et al, or in the patients described in this report. May et al and Hillstrom et al suggested that the difference in the fracture pattern between NOE and medial maxillary (nasomaxillary buttress) fractures is due to the difference in the direction of the external force. Medial maxillary (nasomaxillary buttress) fractures were suggested to occur through an external force on the lateral surface of the medial maxillary wall, that is, an external force from the lateral side in many cases. Telecanthus is unlikely in this situation because the medial canthal tendon deviates medially and/or toward the midline with the frontal process of the maxillary bone. The 2 patients described in this report were also injured by an external force from the lateral side. On the other hand, Trost et al proposed that the difference in the level of the injured region is observed as a difference in the fracture pattern of medial maxillary (nasomaxillary buttress) fractures compared to nasal and NOE fractures; the point of impact in medial maxillary (nasomaxillary buttress) fractures are lower, at the limit between the nasal pyramid and the medial part of the infraorbital rim. In contrast, in nasal or NOE fractures in the Markowitz classification, the point of impact is higher on the nasal pyramid, leading to the impaction of the nasal pyramid in the ethmoidal cells and frontal sinus. This difference in the level of the injured region is also considered to be related to the development of telecanthus . Theoretically, telecanthus observed in NOE fractures is a possible complication due to the deviation of the frontal process of the maxillary bone. However, telecanthus was not noted in any of the medial maxillary (nasomaxillary buttress) fractures reported by May et al,hus Fig. .In conclusion, medial maxillary (nasomaxillary buttress) fractures are not included in any current classification of the maxillary fracture patterns. As medial maxillary (nasomaxillary buttress) fractures are similar to nasal and NOE fractures in clinical signs, careful differential diagnosis is required before selecting the surgical procedure to be performed.www.editage.com) for English language editing.We would like to thank Editage (MO and SY drafted the manuscript as corresponding authors. MO, SY, and TM performed the clinical diagnosis and the operation. HN and TM managed the patients. MO, SY, TY, KS, and YT participated in the operation.Formal analysis: Masaru Ogawa.Project administration: Masaru Ogawa, Satoshi Yokoo.Writing – original draft: Masaru Ogawa.Writing – review & editing: Hidenori Nakamura, Takahiro Yamaguchi, Keisuke Suzuki, Yu Takayama, Takaya Makiguchi.All authors read and approved the final manuscript.


Polymer composites have been widely used in the aviation, aerospace, automotive, military, medical, agricultural and industrial fields due to their excellent mechanical properties, heat resistance, flame retardant, impact resistance and corrosion resistance. In general, their manufacturing process is one of the key factors affecting the life cycle of polymer composites. This article provides an overview of typical manufacturing technologies, including surface coating, additive manufacturing and magnetic pulse powder compaction, which are normally used to reduce the failure behaviour of polymer composites in service so that the quality of composite products can be improved. Advanced polymer composite powder manufacturing processes, the processing mechanism and experimental methods are described, and the influence of different manufacturing processes on the moulding quality is revealed. This investigation can provide suitable methods for the selection of manufacturing technology to improve the quality of polymer composite products. With the rapid development of aviation, aerospace, automobile, medical and health, military and other fields, polymer composites with their unique properties of high specific stiffness and strength, corrosion resistance, light weight and other advantages can replace traditional heavy metals, including steel and aluminium, to realise light weight and intelligence. Especially in the automotive industry, a large number of polymer composites are used to manufacture hybrid electric vehicles and electric vehicle batteries for the purpose of achieving lightweight designs . PolymerThe first use of advanced polymer composites in the automotive industry can be traced back to 1953 when the first Chevrolet Corvette car was exhibited. Since then, glass fibre-reinforced plastics (GFRP) have attracted extensive attention in the automotive industry. Composite automobile grid panels, braking systems, trunk lids and body reinforcement, automobile body parts, door panels, hoods, internal structures, engine frames, T-joints, signal transmission on aircraft, aircraft wings, safety facilities and other parts have emerged, showing prospective applications of polymer composites in the lightweight design of automobiles and aircrafts ,7. Then,Polymer composites have gradually attracted extensive attention in biomedical applications  because The quality of polymer composite products is not only limited by the composite preparation but also affected by the manufacturing technology ,31. BaseThe manufacturing technology of polymer composites is the way to obtain polymer products, embody the properties of materials and develop new materials. Traditional polymer composite moulding manufacturing technology mainly includes extrusion moulding, injection moulding, calendaring moulding, hot pressing moulding and others that are highly repeatable and capable of achieving process control and delivering high-quality components. Moulding processing has been widely used in the manufacturing of complex cross sections , complexSurface coating is a surface manufacturing technology that is used to coat a thin film onto the surface of a substrate material to improve the performance of the substrate. The substrate material can be a polymer material or a non-polymer material. Generally, a layer of film of other materials is coated on the surface of a polymer matrix or a layer of the polymer film is coated on a non-polymer material matrix. The former is mainly used in the biomedical field, while the latter is used as an anti-corrosion material in corrosive working environments to protect the matrix material . SurfaceThe film and substrate mainly exhibit mechanical interlocking combined with physical and chemical adsorption ,60. The Factors influencing the coating performance of plasma spraying technology have been described in multiple papers. Rubarsky et al.  conducteDifferent from plasma spraying, magnetron sputtering is the collision process between the incident particle and the target, and its working principle is shown in The roughness of the coating has a great influence on the service performance of the product ,66, and In comparison to physical vapour deposition methods, such as evaporation, molecular beam epitaxy (MBE) and pulsed laser deposition (PLD), although magnetron sputtering yields a wider range of target selection, faster deposition rate, lower equipment cost and less damage to the substrate , the depAiming at the problem that the working temperature of plasma spraying and magnetron sputtering is too high, electrophoretic deposition technology is favoured due to its low- and medium-temperature working conditions . ElectroIn addition, electrophoretic deposition is more flexible than plasma spraying and magnetron sputtering, which can control the thickness of the film at will by controlling the deposition time, voltage and concentration of particles in the solution ,76. The However, the shear and tensile strengths of carbon nanotube/epoxy resin composites modified by the matrix are much larger than those modified by the interface, which limits the application range of electrophoretically deposited films. In addition, the electrophoretic deposition composite coating had better performance than the single material coating. For instance, regarding a protective layer of copper, RGO-PVC monomer composite coatings deposited by electrophoresis had higher corrosion resistance and adhesion strength than pure PVC monomer coatings . The nanSol–gel technology, first reported by Yamane et al. , has beeThe second step is film coating. The sol–gel method can be divided into two groups: sol–gel dip-coating and sol–gel spin-coating , and theDue to the high temperature of the plasma spraying and magnetron sputtering film preparation process, the film prone to oxidation is generally coated under vacuum conditions, while in contrast, sol–gel technology does not need to be coated under a vacuum, and the working temperature is lower. However, sol–gel technology is prone to cracking of the film during the drying process, and the preparation time is too long . AlthougAdditive manufacturing, also known as rapid manufacturing technology, is a multidimensional manufacturing technology that stacks materials layer by layer, which generally refers to 3D printing technology . On the Three-dimensional printing is a prototyping technology using powdery metal, plastic and adhesive materials to print objects layer by layer see , includi2O3 to improve wear resistance [2 contributed to a 13.2% increase in its tensile strength, but its elongation and toughness were significantly decreased while its brittleness increased. Therefore, it is important to select suitable additives for obtaining high-quality products, which can reduce or avoid failure behaviour during manufacturing and service.Some new special materials for 3D printing can be prepared to improve the quality of polymer composite parts. Laboratory research findings have demonstrated that by adding synthetic particles to increase the stiffness of polymer composites , adding sistance , or addisistance , the persistance  used nylsistance  proved tAlthough reinforced materials can significantly improve the performance of parts, reinforced materials often increase material anisotropy and porosity , and theFour-dimensional printing technology with increased time dimensions has been developed in the past decade since it was found that the shape of three-dimensional printed products changes autonomously over time, as shown in Five-dimensional printing can print products through five axes, as shown in The difference between 3D, 4D and 5D printing technology is that 3D printing can only be moved in the plane to achieve layer-by-layer printing, while 5D printing can achieve printing at any angle. Four-dimensional printing is a special method that does not achieve four-axis printing like five-dimensional printing but increases the dimension of time, and the materials to achieve four-dimensional printing must be smart. Recently, 4D and 5D printing technologies have been combined to propose 6D printing technology  by addinThe key indicator to measure the quality of powder moulding is compaction density. The extrusion moulding, injection moulding, calendaring and hot press moulding manufacturing technologies mentioned above are all quasistatic moulding, and an uneven density distribution of compacts is prone to occur during the moulding process. The friction between the powder particles and the die leads to energy loss, which causes the green compact to generate large residual stress during the sintering process and induce cracking of the part. Magnetic pulse powder compaction technology is a rapid prototyping method that belongs to a dynamic high-velocity compaction process. Similar to explosive compaction and other high-velocity compaction technologies, the powders are compacted through stress waves, as shown in Magnetic pulse powder compaction technology is a high-velocity compaction technology in which a strong pulse magnetic field is generated by the instantaneous discharge of a discharge capacitor to the coil, thereby forming a magnetic field force and pushing the punch to compact the powder. Magnetic pulse powder compaction technology can be divided into radial compaction  and axiaIn During the magnetic pulse high-velocity compaction process, as the compaction rate increases, the friction coefficient between the powder particles and the die will decrease, thereby reducing the reduction in the compaction force caused by friction loss and ultimately making the density distribution more uniform . At the Research on magnetic pulse powder compaction technology is mainly aimed at metal or metal composite materials ,137,138,Many factors affect the quality of magnetic pulse compaction products. In addition to the process parameters, the basic properties of raw materials are the key influencing factors, such as the electrical conductivity, thermal conductivity and mechanical properties of the material. To predict the distribution of the stress field, strain field and damage field of materials in the process of manufacturing and service and to reduce product cost, finite element numerical simulation analysis is an indispensable method. Wang et al.  carried Magnetic pulse powder compaction has the advantages of high density and uniform distribution, strong comprehensive performance, low elastic aftereffect, low cost and high productivity. However, the energy utilisation rate of equipment is extremely low, and most of the energy is consumed by the magnetic field penetrating into the workpiece, the coil resistance heating and the residual energy of the magnetic field is converted into heat. Although the energy loss can be reduced by reducing the penetration depth of the magnetic field and winding the coil with low resistance, the energy utilisation rate still cannot achieve the expected effect, so energy recovery and utilisation are still difficult.During the manufacturing process of polymer composites, online real-time monitoring cannot be carried out due to the characteristics of equipment, working environment and product shape, etc., and failure behaviour and evolution process cannot be predicted in time. Therefore, the establishment of a finite element numerical simulation model can effectively and accurately describe the product manufacturing process at a relatively low cost. Some studies have analysed defects from the manufacturing process of polymer composites by surface coating, additive manufacturing and magnetic pulse powder compaction technology to predict the evolution of defects during the manufacturing process ,146. In 2O3 coating by the C++ program, and the results showed that cracks initiated inside the coating or in the interface between the coating and the substrate. If the crack initiates inside the coating, the crack will extend vertically to the coating surface. If crack initiation occurs at the interface between the coating and the substrate, the crack will evolve under the interaction of other cracks, which will lead to the coating peeling off. When two kinds of cracks work together, the failure of the coating is more obvious. Lin et al. [The main defects of surface coating technology are pores and cracks in the coating. Numerical analysis can be used to understand the failure mechanism and improve the quality of coating products, and it is crucial to develop a numerical model that can describe the evolution of microstructure defects during the manufacturing process. The most common failure of surface coatings is cracking and shedding due to residual stress, which affects the integrity, performance, service life, fatigue performance and corrosion resistance of coating parts . Althougn et al.  obtainedTo prolong the service life of the coating, it is necessary to reduce the residual stress of the coating and avoid cracking and premature failure. A large number of researchers have carried out studies on the influence of process parameters and particle properties on residual stress. Shayegan et al.  establisStress analysis of the numerical simulation demonstrated that reducing the coating thickness had a positive effect on the reduction of residual stress, and the higher convective heat transfer coefficient and shorter cooling time were more favourable for the coating. Meng et al.  used theThe main defect of additive manufacturing is the porosity and residual stress in the billet. Due to the poor interface combination between the reinforcement material and the polymer, the porosity of printed parts increases significantly after the addition of the reinforcement material, which leads to stress concentration and premature failure of the parts. Porosity is an important factor affecting the service quality of products, and it can rarely be reduced by postprocessing. The main method of porosity measurement at present is image collection, but the measurement of porosity in the unit and simulation of product pores within a product are still difficult. At present, there are few reports about the simulation of product porosity. Moumen et al.  proposedAnother important factor affecting the failure behaviour of parts is the residual stress, which is caused by the repeated deposition of hot materials into cold materials . Althoug20 powder were predicted by using this model, and the correctness of the model was verified through experiments. Although the slit of the shape after compaction caused an uneven density distribution, the degree of unevenness was tiny. Olevsky et al. [The biggest problem of quasistatic powder compaction technology lies in the uneven density distribution, while magnetic pulse compaction technology can significantly improve the powder compacting density distribution, but as a result of magnetic pulse powder compaction being passed in the form of stress waves, pressure loss is inevitable, especially for large, compacted parts, which leads to the uneven density distribution of green compacts and easy cracking. Density is the most important index that affects the performance and life of parts compacted by magnetic pulse powder compaction technology. From static compaction to dynamic compaction and from cold compaction to warm compaction, the density and density uniformity of the compacted parts are improved. Only a few numerical simulations are available on magnetic pulse powder compaction technology. Li et al.  realisedy et al.  establisPolymer composites have a wide range of applications in aerospace, aviation, biomedicine, automatic parts, electrodes, packaging materials and other fields. Traditional manufacturing processes such as injection moulding, rolling moulding, extrusion moulding and hot pressing cannot meet these needs. This paper reviews the advantages and disadvantages of surface coating technology, additive manufacturing technology and magnetic pulse powder pressing technology, as well as the factors affecting the performance of polymer composites see .However, these manufacturing processes are still facing some challenges, and the defects existing during the manufacturing process have become a problem that needs to be considered. The residual stress in the surface coating process, the pores and thermal stress caused by additive manufacturing and the uneven density distribution of the compact under the magnetic pulse powder compaction process seriously affect the failure behaviour of the product. Finite element simulation can effectively describe the product manufacturing process to judge the failure behaviour and predict the failure evolution process to reduce costs. Although research on defect analysis in the manufacturing process is still insufficient, FEA is undoubtedly an effective method for analysing the structure of composite materials and predicting the failure behaviour, especially for developing simulation tools.In the future, intelligent manufacturing will assist these advanced manufacturing techniques in processing polymer composites. Due to the rapid development of intelligent manufacturing, some robots have been used to manufacture polymer composite parts in terms of labour cost control and reduction of production defects. The combination of traditional manufacturing technology and artificial intelligence will be prospective, which can not only detect defects in real time but also compensate for defects.


The aim of this study is to review the valuable lower limb biomechanical contribution to table tennis topspin forehand. Databases included Scopus, PubMed, and Web of science. In this case, 19 articles were selected for the systematic review. The mechanics of the plantar, lower limb joints kinematics and kinetics, muscle activity, and racket-joint relationship are described through gender, performance level, and footwork. The study found that the hip movement characteristics and the hip muscle group activity following a proximal-to-distal sequence strategy significantly contributed to the maximum acceleration of the racket. Optimizing the motion strategy of the ankle and plantar as well as the ankle muscle group activity is beneficial for the transmission of energy in the kinetic chain. Muscle groups around the ankle and subtalar joints are heavily activated during landing to maintain foot stability during the landing phase. Lower limb muscle development plays an important role in movement control and stability as well as sports injury prevention in table tennis footwork during the performance of the topspin forehand. Furthermore, physical development levels and anatomical differences (such as hip and lower trunk muscle strength differences), maybe the main reasons for gender differences observed during the topspin forehand. Systematically summarizing this valuable information can contribute to athletes’ and coaches’ knowledge to enhance topspin forehand performance and training regimes. We suggest that future research could consider the joint contact forces, ball movement, and ball-racket impact during a performance of topspin forehand. Table tennis is a spectator and highly competitive sport which have the characteristics of high speed and fast rotation. Athletes perform perfect strokes in combination with upper and lower limb movement, handwork, footwork, and trunk rotation. This is in combination with racket movement and positioning in a limited period to pose an attacking threat to the opponent. As one of the most popular racket sports, table tennis attracts over 40 million participants around the world ,2. TheseTopspin forehand is known as one of the most basic and aggressive strokes in table tennis. Especially for an elite offensive player, excellent forehand topspin skill is necessary to maintain a strong attacking posture . Some clBiomechanics reviews have provided strong support for improving performance and preventing injury in various sports , such asThis study was conducted according to preferred reporting items for PRISMA  statements . The proTo ensure the accuracy of the study results, the design of the search was checked and approved by all the authors of the study. The electronic databases of ISI Web of Science, Scopus, and PubMed were used for searching electronic literature from the earliest available date to 7 July 2022. The search strategies were shown in The following inclusion criteria were used to screen the studies (1) the article should be published in English; (2) the article should be published in a peer-review journal; (3) biomechanics research with a table tennis experiment process; (4) the article investigated the lower limb biomechanics information of topspin forehand of table tennis players.Articles were excluded if (1) the participant was under 18 years old; (2) had a musculoskeletal problem, injury, or rehabilitation; (3) the article focused on table tennis robots or machine learning; (4) the article only used theoretical model or simulations; (5) without specified stroke movement information.Two reviewers (Y.H. and Y.G.) independently screen the methodological quality by including articles based on the Combie criteria which included seven domains . AccordiAs shown in n = 5), racket (n = 3), backhand (n = 2), serves (n = 1), and the physiology issues (n = 1), and the participants with disabilities (n = 2). Furthermore, one article could not be retrieved. Finally, 19 articles were selected for the systematic review.There were 144 articles included in the initial search. After the process of removing duplicates and pooling, there were 100 articles selected for the screening section. Totally 34 studies were finally selected in the process of eligibility . In the The original characteristics of each included study could be seen in The quality of all selected studies was assessed in terms of risk of bias, and the results were presented in Two articles reported on the gender differences in forehand topspin, one of which explored the effect of gender on lower limb joints biomechanical characteristics during the forehand topspin stroke with chasse step footwork . CompareA total of 6 articles investigated the biomechanical characteristics of the lower limbs of different performance levels athletes during the topspin forehand. Five reported the kinematic information of the lower limb joint, two were related to footwork, one was related to electromyogram (EMG), and one was related to the movement of the center of pressure (COP). In this study, the advance player (AP) and intermediate player (IP) were defined according to the selected articles in which the advance player refers to the national I level and the intermediate player refers to the national II level. Lower trunk axial rotation of AP contributed more to racket speed during the topspin forehand . Lower lThree articles addressed EMG information during the topspin forehand, two were based on table tennis footwork, and two were based on performance level differences. Lower limb muscle activity levels were significantly higher during forehand topspin compared with other types of strokes . Hip, knA total of 6 articles explored the biomechanical characteristics of footwork during the topspin forehand. The lower limb biomechanics of cross-step, chasse step, and one-step footwork seem to have received more attention and research. The chasse step footwork is a side movement that could combine with racket movement to perform offensive and defensive strokes in table tennis ,28. CompA total of 4 articles explored the mechanical characteristics of the plantar during the topspin forehand. Plantar mechanics are related to lower limb drivability. In addition to the movement of COP , indexesFive articles reported the relationship between lower limb joints biomechanical characteristics and racket movement during the topspin forehand. The influence of the human joint movement on racket movement has always been the main content of biomechanical research on the topspin forehand. The maximum speed of the racket is increased through the human kinetic chain effect, which brings benefits to enhancing the rotation and aggression of the ball ,6,9,23. Research on the biomechanics of the lower limbs in table tennis has received extensive attention and reports. The key information and findings of the research have been extracted, categorized, combined with practice, and applied for training and participation in table tennis competition. This study provides a systematic review of lower limb biomechanical studies on forehand topspin skills. Information on joint kinematics, muscle activity, joint kinetics, plantar dynamics, and synergistic relationships between racket and joints during topspin forehand. The review summarizes and considers footwork, gender, and performance level. The purpose was to reveal the inner mechanisms of the lower limb biomechanics during topspin forehand skill, and to provide a theoretical basis and reference for scholars and related practitioners. In addition, the paper also outlines unsolved problems and provides possible solutions.Personalized training is one of the principles of sports training, which aims to adapt training programs, training methods, and training loads to the individual needs of the athlete . AthletiThe foot and plantar biomechanical characteristics of forehand topspin have been extensively studied and reported in recent years, and this information is generally considered to be related to lower limb drive ability ,20,24 anThere are several table tennis review studies that have to be mention, and it is valuable to compare was this study. Wong et al.  summarizIn this field of research, some unanswered questions need to be raised. Firstly, in the existing biomechanical studies on topspin forehand skills in table tennis, there is little research and motion capture of the ball movement. In fact, combining human motion with ball motion to explore the inner connection between human movement and ball movement can further elaborate and develop the depth and breadth of research in this field. Secondly, the current research also lacks reports on the collision effect between the ball and the racket, which is actually an important section of research. Thirdly, from the perspective of sports injuries, it is also interesting and valuable to use musculoskeletal models to further explore the biomechanical characteristics of joints, such as calculating joint contact and shear forces through Opensim software.The present study could probably provide some support for clinical application. The table tennis coach and the professorial athlete could acquire valuable information to optimize training strategy and enhance the lower limbs’ motor control ability during topspin forehand. Relevant researchers could quickly establish a basic understanding and knowledge base on the lower limb biomechanics of table tennis topspin forehand through this study.There are some limitations in this study. (1) The included articles of this study hardly report effect size and statistical power in detail, and there are certain statistical limitations, and follow-up research can be strengthened. (2) The existing research results are all derived from the experimental environment rather than the real game environment, which is the main limitation. (3) The existing researchers rarely observe the motion of the ball and the collision effects between the ball and the racket. These are research directions worthy of further attention. (4) Existing studies have not studied the contact force of the lower limb joints in forehand topspin and understanding the joint contact force can help predict possible joint damage. Therefore, we suggest that future research could consider the joint contact forces, ball movement, and ball-racquet collision effects during the performance of topspin forehand.In general, the lower limb biomechanics for forehand topspin skills are widely studied. The mechanics of plantar pressure, lower limb joints kinematics and kinetics, muscle activity, and racket-joints relationship are described through gender, performance level and footwork. The hip muscle group are activated first, following the proximal-to-distal sequence to drive the hip, knee, and ankle joints to perform correct footwork to reach the perfect position to hit the ball. The medial and lateral rearfoot, 5th metatarsal, and lateral forefoot regions absorb energy from impact during landing, and muscle groups around the ankle and subtalar joints are heavily activated during landing to maintain foot stability during the landing phase. Based on the stretching-shortening cycle theory, the elastic energy stored in the muscle-tendon stretching phase can enhance the concentric movement of the muscle, and the concentric contraction of the muscle group around the subtalar joint drives the foot eversion and plantar flexion, and then, the energy following the kinetic chain transmission effect, the contraction of muscle groups around the hip and knee joints, drives the generation of axial rotation and moment. Axial rotational angular velocities and moments of the hip joint provide gains for the maximum acceleration of the racket, while whole body weight transfer and energy transfer also result in larger loads and peak pressures in the medial region of the first metatarsal, forefoot. Systematically summarizing this valuable information can make a contribution to athletes and coaches to enhance topspin forehand performance and training regimes level. We suggest that future research could consider joint contact forces, ball movement, and ball-racket impact during topspin forehand performance.


In implementation science, contextual inquiry guides the implementation process for successful uptake of evidence-based practices. However, the conceptualization and measurement of context varies across frameworks and stakeholders. To move the field forward, future efforts to advance the understanding of context should incorporate input from implementation stakeholders through co-creation, elicit stakeholders’ perspectives in low- and middle-income countries (LMICs) to generate a more comprehensive list of determinants, and refine inconsistencies in terminology to promote research synthesis. Greater conceptual clarity and generalizability in contextual inquiry will enable improved communication and collaboration, thus facilitating a shift in focus to development and evaluation of implementation strategies to improve healthcare and health outcomes. The field has grown exponentially in recent years, as illustrated by the development of over 150 theoretical frameworks, established implementation outcomes,2 taxonomies of implementation strategies,4 and over 600 determinants of practice5 . The core approaches within implementation science focus on (1) engaging in contextual inquiry to understand the context for implementation, (2) designing and selecting implementation strategies based upon this inquiry, and (3) testing the effectiveness of the selected implementation strategies.6 The first step of contextual inquiry involves employing mixed-methods approaches to understand the context in which implementation will occur and the fit between the innovation and that context. This contextual inquiry is essential because context guides the implementation process for successful uptake of evidence-based practices. However, despite the recognition of the importance of understanding context, the conceptualization and measurement of “context” varies across studies and existing frameworks, which presents a challenge for the advancement of implementation science. To advance conceptual knowledge in implementation science, theoretical development needs to focus on the iterative process of theorizing that builds upon developed theory.8 The definition of context and related contextual determinants are not static. The study by Squires et al provides an example of engaging in iterative processes for development of contextual frameworks.9 To realize the promise of scientific discovery, efforts must carefully attend to the process of implementing these discoveries. To address the lack of consistency in definition of concept and minimal stakeholder input in conceptualization, Squires et al elicited health system stakeholders’ perspectives to further elucidate the idea of context in implementation research. Through semi-structured interviews with implementation stakeholders  and implementation science researchers in Canada, Australia, the United States, and the United Kingdom, they compiled a comprehensive list of 16 contextual attributes  comprised of 66 unique features , including: patient characteristics , health professional characteristics , collaboration , culture , evaluation , facility characteristics , financial considerations , governance , leadership , organizational readiness for change , professional role , resource access , system features , work structure , political climate , and regulatory and legislative standards . Participants from all countries described the importance of at least one feature for each of the attributes, indicating consistency across settings. These findings offer conceptual clarity regarding implementation context from the stakeholder lens while highlighting opportunities to further advance the field, as outlined below.10 In the study by Squires et al, the authors describe that only implementation stakeholders discussed the feature of “provincial responsibility” related to regulatory and legislative standards. Researchers did not posit this determinant. Thus, to yield a more robust understanding of contextual factors, and implementation science theory in general, co-creation11 through engagement of a range of stakeholders in different roles and functions for the development of a comprehensive repository of attributes is paramount. First, the research amplifies the need to include stakeholders’ perspectives involved in implementation in the development of implementation science frameworks. A recent review on the development of implementation determinants frameworks revealed that current contextual frameworks were conceptualized through literature review of empirical studies, authors’ own implementation experiences, or review of existing theory, notably lacking input from stakeholders.12 The current study only included participants in four high-income countries, which limits the generalizability of the findings. To advance efforts to provide conceptual clarity, future research should elicit perspectives on context from stakeholders in LMICs. Although some determinants may only apply to LMICs, this elicitation of input would contribute to a more comprehensive list of contextual factors. Second, the study by Squires et al underscores the need to include stakeholders’ perspectives in low- and middle-income countries (LMICs) for framework development. Implementation science frameworks aim to provide common terminology and conceptual clarity across settings, but important features and attributes vary across settings. For example, researchers have suggested adaptations to the Consolidated Framework for Implementation Research (CFIR) to include additional constructs better-suited to resource-limited settings and LMICs.5 a comprehensive checklist for the identification of implementation determinants, Squires et al propose a new contextual attribute for consideration: facility characteristics. Facility characteristics refer to the geography, type, and size of the facility. However, similar concepts exist in other leading implementation science frameworks. For example, the CFIR13 includes a domain for the inner setting, referring to characteristics of the implementing organization. Although CFIR does not explicitly articulate facility characteristics as a construct, researchers often conceptualize characteristics of a facility under this domain. The current work offers an important insight by emphasizing the importance of this attribute from the stakeholders’ perspective but illustrates an opportunity for improvement in clarity. Inconsistent terminology in implementation science can hinder the advancement of knowledge by limiting the synthesis and application of concepts. Thus, a consolidation of existing implementation determinant frameworks is needed to refine terminology.14 Although consolidation may lose the nuance in the phrasing of a contextual determinant, consolidation will advance the field of implementation science by contributing to fewer, more comprehensive lists of contextual factors and effectively promoting collaboration and communication among researchers and stakeholders. Third, the findings emphasize the need for consistent terminology in implementation science. When comparing the results to the comprehensive Tailored Implementation for Chronic Diseases’ checklist, Overall, the work provides conceptual clarity around the idea of “context” with regard to knowledge translation and implementation science. The findings contribute to a common list of contextual factors and offer an advancement on previous work. However, to create generalizability in the understanding of context, and implementation science in general, future efforts should include the input of stakeholders across settings and refine inconsistencies in terminology. In turn, greater generalizability on the concept of context will enable better communication and collaboration between implementation researchers and stakeholders, thus facilitating a shift in focus to development and evaluation of implementation strategies to improve health outcomes. Not applicable. RSB receives royalties from Oxford University Press. RSB has provided consultation to United Behavioral Health. RSB serves on the Clinical and Scientific Advisory Board for Optum Behavioral Health. AVP and RSB contributed to the concept. AVP drafted the manuscript, and RSB provided critical revision of content. Both authors have read and approved the final manuscript. This work was supported by the National Institutes of Health (P50 CA244690), the Penn Implementation Science Center at the Leonard Davis Institute of Health Economics (PISCE@LDI), and the Penn CFAR ISPHERE Scientific Working Group, an NIH-funded (P30 045088) program.