Airborne radars are susceptible to a large number of clutter, noise and variable jamming signals in the real environment, especially when faced with active main lobe jamming, as the waveform shortcut technology in the traditional regime can no longer meet the actual battlefield radar anti-jamming requirements. Therefore, it is necessary to study anti-main-lobe jamming techniques for airborne radars in complex environments to improve their battlefield survivability. In this paper, we propose an airborne radar waveform design method based on a deep reinforcement learning (DRL) algorithm under clutter and jamming conditions, after previous research on reinforcement-learning (RL)-based airborne radar anti-jamming waveform design methods that have improved the anti-jamming performance of airborne radars. The method uses a Markov decision process (MDP) to describe the complex operating environment of airborne radars, calculates the value of the radar anti-jamming waveform strategy under various jamming states using deep neural networks and designs the optimal anti-jamming waveform strategy for airborne radars based on the duelling double deep Q network (D3QN) algorithm. In addition, the method uses an iterative transformation method (ITM) to generate the time domain signals of the optimal waveform strategy. Simulation results show that the airborne radar waveform designed based on the deep reinforcement learning algorithm proposed in this paper improves the signal-to-jamming plus noise ratio (SJNR) by 2.08 dB and 3.03 dB, and target detection probability by 26.79% and 44.25%, respectively, compared with the waveform designed based on the reinforcement learning algorithm and the conventional linear frequency modulation (LFM) signal at a radar transmit power of 5 W. The airborne radar waveform design method proposed in this paper helps airborne radars to enhance anti-jamming performance in complex environments while further improving target detection performance. The rapid development of airborne radar has eliminated the effects of the ground environment and the curvature of the earth on surface-to-air radar. Airborne radar has expanded the detection distance of various low-altitude and ultra-low-altitude targets on the ground, in the air and at sea, and has become one of the key factors of battlefield victory . AirbornWith the continuous development of communication technology and electronic warfare technology, there are many types of electronic equipment on the modern battlefield, and there are situations where the frequency bands used by electronic equipment overlap and interfere with each other. With the rapid development of manufacturing technology and the continuous upgrading of enemy jamming equipment, airborne radar must not only overcome the impact of terrain clutter caused by the complex geographical environment, but also the diversified, dexterous and intelligent jamming of aircraft and missiles that are rushing to attack. These include passive jamming techniques such as foil jamming and towed jamming; active jamming techniques such as deception jamming; and suppression jamming, for which there are a variety of implementation methods, such as long-range support, follow-on and self-defence jamming. Strong clutter and jamming signals in complex environments can reduce the probability of radar target detection by drowning out target echo information, as well as blurring the target signal and reducing the probability of target identification, or forming false targets and increasing the probability of false alarms. These jamming techniques all pose a challenge to airborne radars performing tasks such as search, identification and guidance .Traditional anti-main-lobe jamming techniques include passive anti-jamming methods such as null-domain zeroing, frequency agility and phase encode technology. In particular, the airspace anti-jamming method  uses an Designing and transmitting waveforms based on cognitive radar concepts  that matThis paper aims to design an optimal anti-jamming waveform in a complex and changing electromagnetic environment, based on the electromagnetic environment information acquired by the radar in advance and the mission requirements of the radar, and to lay the theoretical foundation for promoting the development of active anti-jamming technology for radars.Active radar jamming techniques seriously degrade the target detection, tracking and identification performance of radars and are the biggest threat to radar survival today. Therefore, it is necessary to study radar anti-active jamming techniques. With the improvement in hardware performance and in-depth research on signal processing technology, waveform design is favoured by radar researchers at home and abroad as one of the most effective ways to improve the overall performance of the radar.Waveform shortcutting is valued for its anti-jamming properties in the face of main lobe jamming . The maiPhase-coded signals are also a common form of signal used for shortcuts . ThroughThe above research shows that radar anti-jamming technology has made great progress. However, the existing anti-jamming waveforms are not designed to change in real time according to the environment. The waveforms have limited variation and the echo signal processing is fixed, making it difficult to meet the time-varying, non-smooth and non-uniform operating environment. When airborne radars are confronted with new types of jamming, the practical anti-jamming performance of traditional anti-jamming techniques is limited , so therProfessor Simon Haykin has developed a cognitive radar concept  that draCognitive radar waveform design, as one of the main ways of active radar anti-jamming at present, can better design radar anti-jamming waveforms adapted to the current environment based on the electromagnetic spectrum characteristics of the signal and the characteristics of the detected target, to improve the detection and identification performance of the radar. Research on radar anti-jamming based on cognitive radar waveform design has yielded fruitful results. To address the extended clutter suppression problem, the literature  investigReinforcement learning can be found in many areas of artificial intelligence where decision making and control are required, such as in games and gaming. Reinforcement learning has the ability to interact with the environment in real time and to make optimal decisions by continuously learning information about the environment, and has been successfully applied in many areas, such as Go, gaming and medical diagnosis, even surpassing human levels. Reinforcement learning theory fits well with the idea of cognitive radar in that both involve exploring the environment, sensing information about the surroundings and interacting with it, using it to make the best possible decisions to achieve the ultimate goal. For example, the most important feature of reinforcement learning is that decisions are learned through rewards, and the reward function can correspond to rating criteria in cognitive radar systems, such as the signal-to-jamming-noise ratio, amount of mutual information and probability of detection, among other criteria. While reinforcement learning seeks optimal solutions for specific objectives, cognitive radar requires the design of optimal transmitting waveforms to meet specific mission requirements to achieve optimal radar performance. Reinforcement learning requires consideration of the long-term nature of the strategy, and the constant game of cognitive radar against jamming is also a process of finding winning strategies in terms of long-term goals. Therefore, the use of reinforcement learning theory, which is highly compatible with cognitive radar and game theory, can help radar achieve interactive sensing and adaptive firing with the environment, improve the ability of intelligent sensing, processing and feedback of radar and realize the overall performance of radar in complex adversarial environments .With the continuous research on arbitrary waveform transmitters, the maturity of cognitive radar theory and the wide application of artificial intelligence technology, exploring waveform design methods for intelligent anti-jamming of airborne radars based on cognitive radar ideas and artificial intelligence technology has become a feasible new anti-jamming approach for radars. The method can greatly improve the active anti-jamming performance of radars and better adapt to the complex environment of the future intelligent battlefield. A joint adaptive frequency hopping and pulse width allocation scheme based on reinforcement learning was proposed in the literature , and theIn recent years, the field of reinforcement learning has made significant breakthroughs in many artificial intelligence tasks based on a combination of traditional theory and deep learning, giving rise to a new research area of deep reinforcement learning, which provides a viable way to solve complex scenario problems in the real world.Deep Q network (DQN), one of the classical algorithms for deep reinforcement learning, is highly regarded by the academic community. To address the situation in which cognitive radars do not know the exact jamming model, Li K. et al.  used reiAs a value-based algorithm, DQN can only solve finite and discrete action spaces. A series of improvements have been proposed in academia for the DQN algorithm and many research results have been published , such asAs shown in In summary, to address the problem of intelligent anti-jamming of airborne radars in complex electromagnetic environments, we should introduce cognitive radar ideas and establish Markov decision process (MDP) models to describe radar and target jamming countermeasures from the perspective of waveform design. Interaction between airborne radar and environmental information is determined via analyzing the spectral characteristics of target response, jamming signals, clutter response and airborne radar transmit waveforms. Using deep reinforcement learning algorithms, we study waveform design methods for airborne radars under jamming conditions and explore feasible ways for airborne radars with predictive and anti-intelligent jamming capabilities, laying a solid foundation for the realization of intelligent radars.In the first stage, we studied the anti-jamming problem of the airborne radar in a complex environment and proposed a radar anti-jamming waveform design method based on the strategy iteration method . HoweverThe main contributions of this paper are as follows.To address the problems of single and idealized airborne radar countermeasure scenario models, this paper investigates a Markov decision process (MDP)-based approach for modelling dynamic airborne radar countermeasure scenarios. The airborne radar electromagnetic environment under clutter and jamming conditions is investigated, and the dynamic countermeasure process between airborne radar and jamming is modelled using MDP. The MDP-based radar modelling approach allows for the analysis of the electromagnetic information present in realistic scenarios and the arbitrary design of countermeasure models containing a variety of influencing factors such as noise, clutter, the impulse response of the detected target, radar-transmitted signals and jamming signals. The method overcomes the limitations of traditional models and improves the flexibility, accuracy and predictability of the description of airborne radar operating scenarios, providing a viable way to realize the increasingly complex modelling of actual airborne radar operating scenarios.This paper proposes an intelligent waveform design method based on DRL to address the problem of anti-jamming of radar under clutter and jamming conditions. Radar-environment information interaction is determined by modelling the MDP for radar and jamming countermeasures. A radar frequency domain optimal anti-jamming waveform strategy generation method based on the D3QN algorithm is proposed. We build two deep neural networks to fit the state value function and action value function of the radar. The “overestimation” problem of the value function is solved using the fixed Q target method and the preferred experience replay method. To improve radar learning efficiency, prevent training overfitting, etc., the action value function network adopts a pairwise structure. Once the optimal frequency domain waveform strategy has been computationally selected, the ITM is used to generate the corresponding time domain signal with a constant envelope. The simulation results show that the radar transmit waveform designed by this method achieves intelligent anti-jamming of airborne radar while further improving the radar target detection probability compared to the conventional LFM signal, based on the radar waveform strategy generated by the strategy iterative method.Through extensive simulation experiments, the results show that the optimal waveform design method for airborne radar proposed in this paper significantly improves the anti-jamming performance and target detection performance of airborne radar, and outperforms traditional linear FM signals and previous research results based on reinforcement learning.The expression of the signal  follows :(1)y(t)=At the time variance .(5)σh2 into Equation (4) and use Schwartz’s inequality to solve for Equation (6).The equals sign holds under the condition that the SJNR takes the maximum value when and only when Agents are actionable entities for reinforcement learning. For self-driving cars, the environment is the current road conditions; for Go, the status is the current game. At each moment, the agent and environment have their state, such as the current position and speed of the car, the vehicle and pedestrian conditions on the road. The agent determines an action based on the current state and performs that action. It then moves on to the next state with the environment, and the system gives it a feedback value, rewarding or punishing the action, and forcing the agent to perform the desired action. As shown in Reinforcement learning is a class of methods that solve such decision-making problems. The algorithm learns a mapping function called the strategy function through sample learning, whose input is the environment information at the current moment, and the output is the action to be performed, in this case The problems to be solved by reinforcement learning can be abstracted into the MDP. Markov processes are characterized by the fact that the state of the system at the next moment is determined by the state of the current moment, regardless of the earlier moment. Unlike the Markov process, in MDP, the agent can perform actions that change the state of itself and the environment and receive a punishment or reward.The MDP model can be described by a five-tuple t factor . The staThe radar transmits signals to detect the target and the jammer performs jamming on the received radar signals. Radar for the electromagnetic space of jamming signals, environmental clutter and the characteristics of the target being detected integrates this information to design a new radar-transmitted signal to complete the anti-jamming and target detection tasks. The waveform changes in the process of radar-jamming confrontation are Markovian, and the radar confrontation environment can be modelled as an MDP model to achieve intelligent anti-jamming waveform design for airborne radars by interacting with environmental information, such as environmental noise, clutter and jamming signals. The radar signal All jamming signals form the state space Similarly, all radar signals form the action space The reward is the key factor that affects the good or bad decision. The SJNR of the radar signal is used as the action reward of the intelligent body decision, and the reward value size is proportional to the radar signal SJNR; the larger the SJNR, the larger the reward.Setting In this paper, the MDP model is established for the radar anti-jamming environment under clutter and jamming conditions. Firstly, the deep neural network is trained to realize the perceptual interaction with complex electromagnetic environment factors such as clutter, noise and jamming. Second, the SJNR of the radar signal is set as the reward function by combining the impulse response of the detected target acquired in advance. Then, the frequency domain energy optimal strategy of the radar anti-jamming signal is obtained based on the D3QN algorithm, and its time domain constant mode signal is synthesized to realize the intelligent anti-jamming waveform design for airborne radar.The principle of D3QN-based radar intelligent anti-jamming is shown in Due to the max operation, the value function has an overestimation problem at each point of the value, and an uneven amount of overestimation leads to a suboptimal solution, so a method for fixing the Q target is needed.First, an evaluation network and a target network are created. A target network with fixed parameters Then, the evaluation network is used to obtain the action corresponding to the optimal action value in the state To help the radar fully learn and adapt to the current electromagnetic countermeasure environment and to improve the speed of environmental information acquisition, an empirical replay method is used. First, the data, such as the action, However, the uniform random sampling of data during the neural network training process suffers from insufficient learning of important experiences. To avoid the possibility that more important radar countermeasure experiences may occur less frequently than others, a priority experience replay method is adopted so that important experiences have a high probability of being replayed, thus greatly improving the efficiency of the utilization and learning of radar countermeasure data .The radar adversarial process is a model-free reinforcement learning, which requires the use of the concept of time difference error (TD error) to represent the difference between the current Q value and the target Q value as a measure of the importance of each set of radar training data. If the TD error is larger, it means that there is still much room for improvement in prediction accuracy, and the more intelligent the body updates, the more this sample needs to be learned, i.e., the higher the priority ample is .(17)Pωi=, and the output of the action value function network is:Among them, In summary, combined with the actual countermeasure scenario, the airborne radar anti-jamming problem is transformed into a reinforcement learning problem, the countermeasure model between radar and target is established, and the optimal anti-jamming strategy is obtained by describing the electromagnetic environment and training the neural network based on the D3QN algorithm with the following algorithm steps (Algorithm 1).Algorithm 1: Airborne radar anti-jamming strategy design algorithm based on D3QN.Initializes the current Initialize the replay buffer For 1)Initialize the environment and obtain the state S , 2)a)Based on the state b)Perform the action c)Save 5 elements d)if breake)Randomly sample f)Use the mean squared loss function g)if h)while True:The radar detection problem in this paper can be defined as a hypothesis testing problem . By solvThe simulation was carried out based on foreign airborne radar setting parameters such as operating band, centre frequency and signal bandwidth, as well as target flight speed, target impulse response and environmental clutter information, as shown in During the confrontation between radar and jamming, the radar generates the optimal anti-jamming waveform frequency domain strategy by interacting with the environment using the D3QN algorithm. To verify the effectiveness of the method in this paper, experimental comparisons were made between the conventional LFM signal of the radar and the frequency domain anti-jamming strategy generated by the team’s previous iterative method based on the classical reinforcement learning strategy under the same experimental conditions, respectively, and the results are shown in As can be seen from The SJNR is an important parameter for measuring the performance of radar target detection. To verify the performance of the D3QN-based algorithm for airborne radar anti-jamming strategy design, the optimal anti-jamming waveform strategy designed in this paper is compared with the LFM signal and the anti-jamming signal designed by the classical strategy iteration method in reinforcement learning, and the target detection performance of the optimal waveform strategy is analyzed. The radar receiver SJNR and radar target detection probability are calculated by Equations (7) and (23), respectively, to compare and analyze the optimal strategy performance, and the simulation results are shown in The simulation results in The simulation results in The simulation results in From For more visualization, a 3D plot reflecting the variation in the SJNR with To better apply this method to practical radar detection systems and improve target detection performance, it is necessary to generate the time-domain-transmitted signals of the optimal waveform strategy in the radar frequency domain. There are many methods to obtain the time domain characteristics of the generated signal, and the simplest method is the direct inverse fast Fourier transform (IFFT) method, which performs an IFFT on the optimal amplitude spectrum and then normalizes the transformed signal in terms of amplitude. However, the time domain signal synthesized by this method differs significantly from the optimal strategy . The fixThe radar time domain signal is synthesized according to the radar optimal anti-jamming frequency domain strategy in Airborne radars play a vital role in modern national defence by carrying out important tasks such as target search, detection, identification, tracking and imaging. With the rapid development of electronic countermeasure technology, the electromagnetic signals emitted by numerous electronic devices on the battlefield, enemy intelligent jamming signals and complex terrain clutter pose a serious threat to the survival and performance of airborne radars. Therefore, it is necessary to conduct research on anti-jamming technology for airborne radars in complex environments. In recent years, artificial intelligence algorithms have been widely used to provide a viable path for the implementation of cognitive radar. Cognitive radar waveform design is a main research area, involving modelling complex real-world operating environments. How to realize the interactive sensing of radar and electromagnetic environment information, make full use of target characteristics and jamming signal spectrum characteristics, design radar-transmitted waveforms in real time to adapt to complex environments and detected targets and achieve good anti-jamming while improving radar target detection performance is the focus of current research.In response to the problems of single and idealized radar countermeasure scenario models in traditional anti-jamming technology research, we study a dynamic radar countermeasure scenario modelling method based on the Markov decision process. The MDP model overcomes the limitations of traditional models, improves the accuracy and predictability of the actual radar operating environment and provides a model basis for radar waveform design research. The MDP model overcomes the limitations of traditional models, improves the accuracy and prediction of the actual radar operating environment and lays the model foundation for post-radar waveform design research, further promoting the development and application of cognitive radar.To address the problem of dynamic countermeasures between airborne radar and jamming in complex environments, we propose a deep-reinforcement-learning-based anti-jamming waveform design method for airborne radar under clutter and jamming conditions from a waveform design perspective and build a dynamic countermeasure model for airborne radar and jamming in complex environments based on MDP. We construct two deep neural networks for training learning of the neural networks by iteratively computing the reward values to the adversarial data using different radar waveforms in different jamming states. We recommend a design technique for the optimal anti-jamming waveform strategy of airborne radar based on the D3QN algorithm and synthesize the optimal time domain transmitted signal by iterative transformation method. It has certain reference significance for the realization of radar intelligent confrontation technology in electronic warfare and has laid a theoretical foundation for the realization of cognitive radar.This paper outlines the current research status of airborne radar anti-jamming technology with research on deep-reinforcement-learning-based radar waveform design in complex environments and a focus on solving the dynamic confrontation problem between radar and jamming in electronic warfare, fundamentally improving radar’s active anti-jamming capability, enhancing radar adaptability in complex environments and laying the foundation for the development of radar confrontation. The main contributions of this work are as follows:The waveform design problem for complex environments has focused on the waveform design problem for electromagnetic information environments containing clutter, noise and jamming, while the waveform design for the non-smooth and non-uniform actual combat environments faced by airborne radars has still not been considered. Therefore, subsequent work should fully investigate waveform design methods for airborne radars in various non-smooth, non-uniform electromagnetic environments, such as clutter and new types of jamming signals, and discuss the performance of waveform design technology methods in a variety of complex environments, which is of great significance for improving the anti-jamming performance of airborne radars in actual combat.In response to traditional anti-principal flap jamming techniques’ difficulty coping with diverse and dexterous new types of jamming, we investigate a deep-reinforcement-learning-based approach to airborne radar waveform design. When building a dynamic countermeasure model between radar and jamming based on a Markov decision process, a discrete signal form and a reward function design based on a single performance indicator of the SJNR are mainly used, without considering continuous state and action representations, and a reward function setting that combines multiple performance indicators. The future development trend of radar must be multi-functional and intelligent, and in the subsequent research, attempts should be made to establish a continuous state and action space, which is conducive to the application of airborne radar intelligent waveform design technology in practice; the use of multiple radar performance indicators to combine the design of reward functions is of great significance to the development of multi-functional radar waveform design.To address the difficulty of the practical application of theoretical waveform design methods, we focus on the design of frequency domain optimal anti-jamming waveform strategies based on artificial intelligence algorithms, using an iterative transformation method to synthesize the corresponding constant envelope time domain signal. However, only the real, imaginary, amplitude and phase information of the time domain signal is obtained, and no actual transmittable time domain waveform is found. Most of the current radar waveform design studies do not consider the actual emission of the designed waveform. On the one hand, this is because the modelling of the problem deviates significantly from the actual environment when considering waveform design methods, making it difficult to apply to real-world scenarios. On the other hand, the hardware is limited by the production process of electronic equipment, and current radar transmitters are not yet able to meet the demand for transmitting arbitrary waveforms. Therefore, to ensure that radar waveform design research results can be used in practical equipment and truly improve airborne radar performance, future radar waveform design research should be closely integrated with practical application scenarios and equipment, so as to lay a solid foundation for the successful implementation of airborne radar waveform design and the smooth development of new system radars.This paper mainly aims to investigate the design of anti-jamming waveforms for airborne radars in complex environments based on deep reinforcement learning, drawing on cognitive radar ideas. The paper has carried out some work at the basic theoretical level and obtained some preliminary research results, which should be followed up by research on the following aspects and shortcomings. The main areas include the following:


The online version contains supplementary material available at 10.1186/s40249-022-01034-3. With some 134,073,166 people living in endemic communities at risk of infection . The Nat# 1. Additional platforms for delivering praziquantel must be identified aside from the school-based PC. Increased allocation of praziquantel tablets is required for PC in Nigeria. To this end, a spatially explicit map of schistosomiasis prevalence with the estimated number of persons requiring praziquantel treatment per community is imperative to guide the implementation of this recommendation. The georeferencing of all schistosomiasis’s endemic communities and validation of Expanded Special Project for Elimination of Neglected Tropical Diseases ward level prevalence data for Nigeria should be prioritized. Ward level prevalence maps and population data to estimate treatment needs from > 2 years are required to guide implementation. NSCHEP implementation guideline also needs to be revised to include PC of preschool children, pregnant women after the first trimester and lactating mothers. A challenge will be accessing the required donated praziquantel for Nigeria in the face of global scarcity.# 2. Stopping PC requires careful consideration, particularly for communities where PC is seen as government largesse. However, a decision to reduce the frequency of PC requires close epidemiological monitoring to ensure there is no rebound in prevalence. Implementation of test-and-treat will require a point-of-care (POC) rapid diagnostic kit for both types of schistosomiasis and praziquantel at a nearby health facility. This requires critical consideration of cost, which is currently outside PC activities and budget. POC kits will need to be imported, with the training of health workers on how to use the kits. Such training may be extended to the local pharmacy in hard-to-reach communities where there are no health facilities.# 3 NSCHEP and partners should/will identify endemic communities  for biannual treatment with persistently high prevalence despite rounds of PC. The decision to implement biannual treatment will require prior conduct of impact assessment surveys to identify hot-spot communities, which has cost implications for funding partners. Furthermore, regular safeguarding against any future erosion of community acceptance of offered treatments should be secured.# 4 The integration of the schistosomiasis control programme into the primary health care system to provide access to all age groups at proven or suspected risk, is a crucial step in response to the global call for schistosomiasis elimination. The feasibility of this was recently demonstrated by a pilot COUNTDOWN female genital schistosomiasis (FGS) health system study where sixty-six women with symptoms of FGS were able to access praziquantel treatment outside PC in Ogun State, Nigeria [# 5. There is a need for a collaborative effort and sharing of NTD and WASH data among stakeholders. The National Schistosomiasis Technical Working Group, NTDs WASH sub-committee and State Advisory Committee on Neglected Tropical Disease (SACON), comprising representatives from the Academia, WASH, National Orientation Agency, Primary Health Care Board, Media, Ministry of Education, and implementers should work collaboratively. SACON should be empowered and supported to develop an integrated NTD and WASH database for monitoring WASH and NTD activities. We also advocate the use of helminthiases as bio-indicators of WASH sector activity impact. NSCHEP should adopt research-proven innovative behavioural change and health education tools for sensitisation among people living in the endemic communities [#6. NSCHEP should leverage existing collaboration with schistosomiasis experts within academic and research institutions in Nigeria to develop MSc/PhD research projects at the request of Federal Ministry of Health (FMoH) for impact assessment, monitoring, and to establish the interruption of transmission in post-MDA communities. The collaboration will reduce the burden of FMoH on funding these verification activities, as such studies could establish and secure a research grant platform for its execution. A notable gap in current applied research is the lack of an appraisal of zoonotic schistosomiasis, alongside its contribution to the transmission of human schistosomiasis in Nigeria.NSCHEP and stakeholders must meet and issue new policy documents to domesticate the implementation of the new WHO guideline with support from local WHO offices WHO-AFRO/Nigeria. A critical dimension to consider is the raising of sufficient domestic funding, to fill potential gaps likely to emerge in the implementation of the new recommendations. This is particular apt in light of dwindling external funding for the national NTD programme.Additional file 1: Opportunities and Challenges of the new WHO recommendations.


In the article titled “Social Recommendation System Based on Hypergraph Attention Network” , the autAlthough hypergraph neural network shows the potential of high-order relational modeling in many fields, there is little work in the field of recommendation system, and only a few research works combine these two topics. HyperRec [38] uses the advantages of HGCN to recommend the next item for users. DHCN [39] models the session data as a hypergraph, and then extracts the feature information of the session by using the dual-channel hypergraph convolution network, so as to infer the next item in the session. SHARE [40] is different from DHCN in that it uses the hypergraph attention network (HGAT) [32], which can flexibly aggregate the context information of related items in the session to generate item embedding. However, these recommendation methods do not make use of social relations, resulting in unsatisfactory recommendation results. Therefore, we integrate social networks into the recommendation system, and exploit the potential information of users by using the characteristics of hypergraph that can capture complex high-order relations.Although hypergraph neural network shows the potential of high-order relational modeling in many fields, there is little work in the field of recommendation system and only a few research works combine these two topics. HyperRec [38] uses the advantages of HGCN to recommend the next item for users. DHCN [39] models the session data as a hypergraph and then extracts the feature information of the session by using the dual-channel hypergraph convolution network, so as to infer the next item in the session. SHARE [40] is different from DHCN in that it uses the hypergraph attention network (HGAT) [32], which can flexibly aggregate the context information of related items in the session to generate item embedding. MHCN [49] uses hypergraph convolutional network technology to mine users' potential information by leveraging high-order user relations. However, these recommendation methods do not exploit the hypergraph attention network to capture users' social relations, resulting in unsatisfactory recommendation results. Therefore, we integrate social networks into the recommendation system and exploit the potential information of users by using the characteristics of hypergraph attention that can flexibly capture complex high-order relations.


This teaching project aims to improve attitudes and perspectives towards psychiatry by using Patient as Educators (PaE) in a psychiatry teaching program early in medical training.Following the success of a small pilot study in 2020, the project was rolled out to the entire second year medical student body in 2021. Two-hour interactive sessions were delivered online to groups of approximately twelve students. Each session was introduced by a psychiatrist, followed by PaE discussion with questions and answers. The students completed a bespoke online survey at the beginning and the end of the session, looking at attitudes towards psychiatry. Comparative analysis of attitudes pre- and post-intervention was then undertaken. Qualitative data were examined through content analysis and quantitative methods were used to compare pre- and post- attitudes on the Likert scale.The pre- and post-intervention questionnaires were completed by 373 and 305 students respectively. Both pre- and post-intervention attitudes were overwhelmingly positive. Post-intervention qualitative results demonstrate the session, especially the PaE, helped students to better understand the complexities of mental illness, the stigma faced and the potential efficacy of good treatment. There was a 25.7% increase in students’ perception of preparedness to see mentally unwell patients. The most significant findings were that the majority of students found having the PaE valuable in improving attitudes regarding the value of psychiatry (72.8% agreed/strongly agreed) and increasing interest in the speciality (84% agreed/strongly agreed).Early experience to clinical placements is an essential component in medical education. In Psychiatry, apart from gentle introduction into the specialty, it is essential that students are orientated into the world of mental health and its various challenges. This project has clearly demonstrated the effectiveness of early exposure of medical students to psychiatry as a specialty. It also demonstrates the effectiveness of using PaE in medical education. Further research would aim to examine whether effect on attitudes persist and correlate the effect on early exposure on recruitment to the speciality.


The COVID-19 pandemic has highlighted a need for engaging online resources to enrich psychiatry training for undergraduate medical students. Podcasting is a well-established digital communication platform utilised daily in a myriad of capacities, including education. A group of medical students were tasked with creating their own educational podcasts covering specific aspects of psychiatry.Each pair was set a sub-topic of psychiatry and utilised software to produce educational resources. The objective of this project was to reflect upon production as well as explore the efficacy of podcasting as a tool within undergraduate training.The medical students conducted research and contacted experts within the field to contribute to their podcasts. The majority of the students then conducted reviews of the literature surrounding podcasting within medical education, which informed the production of their own podcasts. From this, it was discussed how this project could impact future practice, and indicated that podcasts may become crucial asynchronous learning tools in medical education.Literature review and first-hand experience of podcast production enabled the students to appreciate the advantages of podcasting and the potential for its widespread future applications. Their wider reading revealed that podcast-using study participants outperformed or matched their peers in assessments, and overwhelmingly enjoyed using podcasts over traditional teaching methods.The use of podcasting can complement traditional psychiatry training and appeal to a generation of digital natives that prefer this learning style. Podcast production is also an excellent revision method, highlighting the advantages of peer-to-peer education in both learning and increasing engagement with psychiatry.No significant relationships.


Camellia oleifera) oil. The deterioration behaviors and lipid oxidation of three kinds of camellia oils, including camellia crude oil (CO), moderate refined oil (MRO), and refined oil (RO), during heating were investigated in this study. The results of deterioration behavior analysis showed that the oxidation degree was RO > CO > MRO. Tocopherol and polyphenolic substances in the oil might help delay oil oxidation. The lipid oxidation results indicated that the heating process had greater effects on CO and MRO than RO; it upregulated neutral lipid content and downregulated phospholipid content in terms of lipid changes and the multiplicity of differences. Glycerophospholipid metabolism was the most remarkable pathway and was important to study the heating process of refined oil. Moderate refining is good for retaining the beneficial lipids in camellia oil. The results of this study would provide a theoretical basis for camellia oil processing.Refining degree has an important influence on the quality of camellia ( Camellia oleifera (C. oleifera) is one of the four major woody oil plants in the world and is a primary source of edible vegetable oil ) > 1 were considered differential lipids. For clustering heat maps, the data were normalized as z-scores and plotted by the Pheatmap package in R. A volcano plot was used to filter the lipids of interest based on log2(FC) and −log10 , through the ggplot2 package in R. The lipids with p < 0.05 (t-test) were used in the over-representation analysis (ORA) enrichment analysis, and the resulting KEGG pathways with p < 0.05 (ORA) were considered to have a statistically significant enrichment.Data normalization, principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed with the R package, MetaboAnalystR  . The Norp < 0.05 was considered statistically significant. The Pearson correlation was analyzed with SPSS 22.0.All analytical measurements were performed in triplicate, and the results were expressed as the mean ± standard deviation (SD). The data were fitted and plotted using Origin 9.0 . Comparisons among groups were performed by one-way ANOVA followed by the least significant difference test . The color variations of the camellia oils during heating are shown in The iodine value is used to evaluate the unsaturation degree of oil. A higher iodine value indicates a greater degree of unsaturation. The iodine value of oil will change when heated because of the oxidation reaction or polymerization reaction of unsaturated fatty acids (UFAs). As a result, the unsaturated degree of fatty acids in the oil is reduced in the process of heating. However, the change in iodine value can only explain the change in the total UFAs in the oil and cannot specifically reflect the change in UFA content .Changes in the iodine values of the three kinds of camellia oil during heating are shown in The initial fatty acid compositions of three kinds of camellia oil are shown in p-AV is a measure of the amount of aldehydes  in oil. The higher the p-AV, the more severe the deterioration. p-AV reflects the change in secondary oxidation products. We introduced TOTOX (TOTOX = 2PV + p-AV) to better evaluate the overall oxidation level of oil. The TOTOX values are closely related to the freshness of oils; the lower the TOTOX value, the higher the freshness of the oil . On. On2 viaIn this study, we used physicochemical and lipidomic analyses combined with a chemometric method to investigate the changes in the oxidation degree and lipid sub-stances of camellia CO, MRO, and RO during heating, and the effects of different refining degrees on camellia oil quality. The deterioration behaviors of three kinds of camellia oil were evaluated by measuring physical parameters, oxidation indexes, and active substance contents. Camellia oil when less refined is less oxidized, probably due to substances such as tocopherols and polyphenols in the camellia oil. However, camellia oil when less refined has a greater change in lipids during the heating process, but moderately refined camellia oil is good for retaining the beneficial lipids in camellia oil. The degree of refining will not only remove impurities from camellia oil, but also eliminate some beneficial components, which may directly affect the oxidation and lipid changes in the subsequent cooking process. Therefore, moderate refining should be advocated in the processing of camellia oil according to the quality of the crude oil and the usage of the oil.


The progress of contemporary cardiovascular therapy has led to improved survival in patients with myocardial disease. However, the development of heart failure (HF) represents a common clinical challenge, regardless of the underlying myocardial pathology, due to the severely impaired quality of life and increased mortality comparable with malignant neoplasms. Left ventricular ejection fraction (LVEF) is the main index of systolic function and a key predictor of mortality among HF patients, hence its improvement represents the main indicator of response to instituted therapy. The introduction of complex pharmacotherapy for HF, increased availability of cardiac-implantable electronic devices and advances in the management of secondary causes of HF, including arrhythmia-induced cardiomyopathy, have led to significant increase in the proportion of patients with prominent improvement or even normalization of LVEF, paving the way for the identification of a new subgroup of HF with an improved ejection fraction (HFimpEF). Accumulating data has indicated that these patients share far better long-term prognoses than patients with stable or worsening LVEF. Due to diverse HF aetiology, the prevalence of HFimpEF ranges from roughly 10 to 40%, while the search for reliable predictors and genetic associations corresponding with this clinical presentation is under way. As contemporary guidelines focus mainly on the management of HF patients with clearly defined LVEF, the present review aimed to characterize the definition, epidemiology, predictors, clinical significance and principles of therapy of patients with HFimpEF. Heart failure (HF) represents a syndrome of symptoms resulting from multiple myocardial diseases leading to impaired cardiac output or increased intracardiac pressure at rest or during exertion . It is eThus, the present article sought to summarise the up-to-date knowledge on the definition, epidemiology, predictors, clinical significance and practical aspects of the management of patients with HFimpEF. For this purpose, the Medline and EmBase databases were queried to obtain original articles and review papers using the following set of keywords: heart failure with improved ejection fraction; HFimpEF; HFiEF; heart failure with recovered ejection fraction; HFrecEF; heart failure improvement; and heart failure change.Although the phenomenon of LVEF improvement has been reported for years, no universal definition of HFimpEF exists. The oldest and least precise, yet simple, definition is based on the cohort from the Val-HeFT trial, which required an initial LVEF measurement <35% and an increase in follow-up LVEF after 12 months to >40% . An evenStill, the most contemporary definition comprises an initial LVEF < 40% and an increase of ≥10% and a follow-up measurement >40% . This deAlthough LVEF is regarded as the main categorizing parameter and marker of the response to treatment among HF patients, one should address the caveats related with its use as a universal therapeutic target. First, the symptoms of HF are secondary to impaired cardiac output related with both systolic and/or diastolic dysfunction. As obvious as it is, LVEF within the reference value does not exclude HF, and patients should be screened for structural abnormalities and elevated natriuretic peptides . HFpEF pThe rate of HFimpEF among the population of patients with HF depends on the applied definition, the proportion of patients with different aetiologies, the reversible causes of HF and the intensity and appropriateness of HF therapy. In the Val-HeFT trial, the criteria of improvement were met in 9.1% of 3519 patients with a baseline LVEF < 35% . The lonGiven the distinct phenotype, it seems reasonable to pursue reliable predictors of systolic function improvement among the broad population of patients with HF . HithertThe main premise for identifying responders to HF treatment consists of the strong evidence of a far better prognosis in this group of HF patients. Despite numerous predictors of HF outcome, such as LVEF, symptomatic class, frequent hospitalization for decompensated HF or the level of natriuretic peptides, the prognosis of HF remains vastly unfavourable and uncertain. The phenomenon of LVEF improvement identifies a subset of patients with a distinct set of phenotypes from patients with stable or declining LVEF , which ip < 0.001) [Jorgensen et al. found that patients with an increase in LVEF ≥5% within a median time of follow-up of 19 months had a lower risk of death than patients with persistently reduced LVEF  . Accordi< 0.001) . These r< 0.001) ,23. Thes< 0.001) .It is vital to note that HFimpEF does not represent a separate form of HF, rather a group of phenotypes with different aetiologies that share a better prognosis than patients without LVEF improvement . Still, The pathophysiology of a failing heart represents a complex interplay concerning alterations in gene expression, changes in metabolic pathways and the contents of the extracellular matrix. The progression of HF leads to modifications of the expression of multiple genes, including immune-modulation genes ,29, whicThe main metabolic change within cardiomyocytes in HF is the decreased uptake of fatty acids by cardiomyocytes and its reduced beta-oxidation and shift towards glycolytic pathways, which translates into an increased intracellular concentration of cytosolic lactate rather than pyruvate . In addi2+ influx and a reduced uptake of CA2+ to the sarcoplasmic reticulum due to the dysfunction of energy-dependent SERCA2 [2+, the spontaneous releases of Ca2+ from the sarcoplasmic reticulum and an increased risk of afterdepolarizations and life-threatening ventricular arrhythmia [Dysregulation in the intra-cellular levels of calcium and sodium plays a key role in the electrophysiologic abnormalities of a failing heart . Cardiomt SERCA2 , which trhythmia . The decrhythmia . An incrrhythmia . It is vrhythmia  and imprrhythmia .On the other hand, the reversal of pathologic changes has been demonstrated in the extracellular matrix (ECM), which is a vital habitat for cardiomyocytes necessary for its structural support and neurohormonal signalling. The environment of cardiomyocytes in HF is characterized by an increased level of the cross-linked fraction of collagen, osteonectin, osteopontin, tenascin C, thrombospondin, periostin and matrix metalloproteinases and a decreased activity of tissue inhibitors of metalloproteinases (TIMPs) . The cliAll in all, reverse remodelling reflected by the clinical setting of HFimpEF is accompanied by a reversal of pathology within ECM; however, an abnormal metabolism of cardiomyocytes and altered gene regulation warrant caution when it comes to the cessation of effective treatment.The initial management of HF comprises symptomatic relief mediated in part by diuretic therapy, the institution of disease-modifying pharmacotherapy and establishing the aetiology of HF. Irrespective of aetiology, all patients with HFrEF should receive the recommended guideline-directed medical therapy (GDMT), which has been shown to reduce the risk of hospitalization for HF and to prolong survival ,10. AccoLess is known how these disease-modifying medications promote functional and structural reverse remodelling, such as a reduction in LVESV, reduction in the level of sphericity index and, most importantly, an increase in LVEF.The impact of beta-blockade on reverse remodelling was demonstrated by Hall and co-workers, who gave evidence for the long-term increase in LVEF and the decrease in left ventricular mass and index of sphericity, following the initial negative inotropic effect resulting in the transient decrease in LVEF in the first days of treatment . Beta-blThe cornerstone of modern HF therapy is based on the use of ACEI, which has been shown to slow down ventricular remodelling and neurohumoral activation in HF of ischemic aetiology . The appFurther blockade of renin–angiotensin–aldosterone syndrome with the use of MRA has been linked not only to a reduction in the risk of death and hospitalization for HF among HFrEF patients but also to antifibrotic effects within the myocardium and a resultant reduction in arrhythmogenesis . In a coAccumulating evidence has shed light on the role of sacubitril/valsartan, which not only acts as ARB but also blocks the dipeptidyl peptidase IV responsible for the turnover of bradykinin and natriuretic peptides. Along with its impact on the reduction in the risk of death and hospitalization for HF among HFrEF patients in comparison to ACEI , sacubitYet another advance in the pharmacotherapy of HF was the introduction of SGLT2 inhibitors as independent drugs for the therapy of HF, irrespective of the diagnosis of diabetes mellitus . The curThe chronic character of HF raises an important clinical aspect in terms of the management of HF patients concerning the continuation of GDMT and limiting the burden for healthcare system in patients with LVEF improvement. In addition, the majority of patients perceive their health and quality of life by the number of drugs that they are recommended to take daily. The question of the maintenance of pharmacotherapy in patients with improvement or even full recovery of LVEF and the relief of symptoms is an important issue for patients that was addressed in a randomized TRED-HF study . This opThe surveillance of patients with HFimpEF should comprise medical consultation with a physical examination, ECG and natriuretic peptides screening for left bundle branch block every 6 months until 12–18 months of HFimpEF and subsequently every 6–12 months . PatientThe issue of HF therapy in the context of HFimpEF also concerns cardiac implantable electronic devices (CIED). This complex aspect of HF therapy comprises: (1) the choice of an optimal population of patients who will respond to cardiac resynchronization therapy (CRT) in patients with HFrEF and the concomitant electrocardiographic signs of left ventricular dyssynchrony; (2) the consideration of elective implantable cardioverter–defibrillator (ICD)/CRT implantation and the choice of its right timing in the context of potential systolic function improvement; and (3) the reassessment of indications for CIED replacement in patients who already have undergone implantation and require its elective replacement.The contemporary guidelines recommend the implantation of an ICD in the primary prevention of sudden cardiac death in HFrEF with LVEF ≤35% in symptomatic New York Heart Association class 2–3 who are expected to survive >1 year in good clinical condition, following 3 months of optimal medical therapy in order to reduce the risk of sudden cardiac death and all-cause mortality .p < 0.001) [HFrEF pharmacotherapy should be implemented and continued for an implicit period of time before determining the need for device therapies ,64. ICD < 0.001) .One can assume that it is the type of cardiomyopathy that determines the time to reassess LV function, hence in DCM, peripartum cardiomyopathy, tachycardia-induced cardiomyopathy and myocarditis, a waiting period of 6 months may be required to allow adequate reverse remodelling before re-evaluating the indications for ICD implantation, while improvements in ischemic HF are rare beyond 3 months of GDMT ,71.The efficacy of CRT is commonly treated as being a ‘CRT responder’, which may fall into a particular category of HFimpEF. The indications for CRT encompass symptomatic patients with LVEF < 35% and QRS prolongation ≥ 130 ms, optimally ≥ 150 ms, with left bundle branch morphology ,73. MoreThe significance of CRT and its long-term maintenance as a therapy is indisputable because an interruption of biventricular pacing leads to a worsening of LV function and an increase in functional mitral regurgitation ,76. The An analysis of the SCD-HeFT trial   without the structural abnormalities of leaflets and valve apparatus ,80. The If symptoms persist despite GDMT and CRT implantation, patients should be assessed by a heart team in terms of eligibility for surgery . MV repaThere is dispute over the role of transcatheter edge-to-edge repair of the mitral valve in the treatment of fMR given the conflicting results of the MITRA-FR and COAPT trials ,86. The The course of HF is inextricably related with its aetiology, hence the identification of HF cause and the prompt institution of specific treatment on top of GDMT represent the vital steps in the management of HF , Table 2Clinicians should pay particular attention to non-ischemic aetiologies of HFrEF, which give a greater promise of reversal of systolic dysfunction. Dilated cardiomyopathy represents a heterogenous group of primary disorders of myocardium, which are related with mutations in sarcomere genes, myocarditis, auto-immune response following myocarditis, toxic injury or thyroid dysfunction. Given a nearly 35% prevalence of familial DCM, genetic testing should be utilized in order to identify the mutations responsible for the clinical phenotype . TruncatTachyarrhythmia, most commonly due to atrial fibrillation and atrial flutter, can be both a cause and sequelae of HF . In the Due to the heterogenous aetiology of HF, no universal definition of the state of improvement exists. The most widespread criteria include an initial LVEF < 40% with a further absolute increase in LVEF of ≥10% above the threshold of 40%. This condition of LVEF recovery is present in 10–40% of patients diagnosed with HF. One should rather use the term ‘transient remission of systolic dysfunction’, as LVEF is variable and recurrent LVEF deterioration may occur. Patients with HFimpEF are characterized by a 50% lower risk of death and/or hospitalization of HF in contrast to patients with HFrEF or HFpEF. This underscores the importance of the identification of this subset of HF patients, given the generally ominous prognosis of the HF population.


The yawning gap between green bioproducts and fossil-based products calls into question whether the chemical industry can underpin the drive for sustainable development and reduction of socio-ecological disparities. The biochemical industry has, ostensibly, struggled with technological barriers. A wide assortment of biomedical and biopharmaceutical applications, ranging from implant fabrication to drug delivery, can be attributed to biopolymers .The development of biopolymers is mired in contradictions regarding the polymeric molecules. Biopolymers are polymeric biomolecules produced by living organisms, such as plants or bacteria. These types of polymers can be produced from renewable sources, are biodegradable, and can, therefore, be recycled by biological processes. However, certain chemical-based synthetic polymers are toxic to human and animal cells. Thus, biopolymers have been considered pinch hitters in biomedical and biopharmaceutical applications .At present, the biochemical projects have stumbled due to operational barriers and remain uncertain in light of market conditions. Getting these projects on the front burner is crucial for the establishment of a healthy market environment, where applicational infrastructure is considered a catalyst in fostering the evolution of biopolymers. Breakthroughs in synthesis and the advanced properties of biopolymers are intrinsic pillars for the expansion of biomedical applications, including their use in anti-inflammatory and antimicrobial agents, drug delivery systems, and regenerative medicine (tissue engineering and implant fabrication) .In this article, we explore subtle issues of the bio-based product landscape and suggest steppingstones towards biopolymer production. This mini compendium provides a timely discussion of the ongoing debate regarding biopolymers.The development of sustainable solutions is essential to drive the radical change to a green, bio-based economy. The socio-ecological deadlock reflects a cross-cutting concern about drastic change. The European Commission rendered a sharp rebuke to European Union (EU) members , imploriCurrently, the legislation includes the waste framework directive 2018/851, as indicated by EU commissions directives, which provides a long-term roadmap for waste elimination and bio-product recovery . PlasticAn example of the lifecycle of bio-based, biodegradable, and compostable plastics, with the aim of redeeming quality and value, in the economic reality of agriculture is given in Polymer companies pushing for more transparency in the bioproduct system question the claim that this is a sustainable alternative to chemical-based polymers. The R&D department focuses on churning out new biopolymer synthesis methods tailored to achieve a sustainable and efficient cascading technological route . AlthougThe advent of genomics resuscitated the biopolymer industry and rekindled the ailing bioeconomy. Microorganism evolution hinges on the complex interplay between microbiomes and environmental conditions. A cardinal number of biopolymer-related studies and goals delineate the status quo; it has been extensively alluded that utilisation of microbiological agents genetically modified to produce bioresources will benefit the biopolymer industry .Current research efforts in synthetic biology, as well as a bewildering number of reports on the weaning from chemical-based polymers, may herald unprecedented industrial focus. Pioneering work in genomics has also made possible the industrial stance regarding advanced bioproducts. Synthetic biology demonstrates the shrewdness of the biotech industry in embedding laboratory techniques and leveraging data and technologies .The ecological deadlock reflects a cross-cutting alarm and need for a proactive stance with drastic alterations in this direction. Synthetic biology is necessary to perk up the landscape and provide a cushion in times of food chain disruption. Future ventures that provide more funding of research may reinforce the bio-based product innovation . The repEnvironmental organizations suggest that bioeconomy-based research may curtail the production of inordinate amounts of emissions. The race to a bio-based economy requires collaboration between venture capital firms and scientific institutions. Investors and corporations are enamoured with technological breakthroughs and scientific advances. However, curtailments in the course of large-scale applications for bio-based production slow their commercialization . EffortsLeaders in the biochemical industry are considering waste as a sustainable solution for biopolymer production. Biowaste is regarded as a new biosource, related to biopolymers, which may be respected in the business arena. The promise of genetically engineered crops and algae is tantalizing, as previous studies have shown that genetic manipulation of organisms results in efficient secretion of biopolymeric compounds . BolsterIn addition, the annual amount of generated waste is dwarfed by the impact of national, regional, and local waste. Idleness on the part of several European members highlights the necessity for market reformation and stringent regulation; national policies need to converge on sustainable biochemical recovery in order to deal with waste accumulation. The resounding agreement on substitution of biowaste for waste provides grounds for complacency among biopolymer business investors .ante by imposing elevated market standards to spur the biochemical industry.As expected, environmental pollution is greatest in cities, as is the vigilance in reduction of biowaste, thereby creating a sweeping basis for reliable biochemical investments with the guarantee of long-term contracts . PrioritThe clustering of biowaste to biochemical technologies is a prerequisite for the sustainable production of biopolymers. Manoeuvrability of the technical pathways circumvents conventional chemical recovery and poor end-product availability . Policy However, the peculiarities of current policy result in energy businesses going bankrupt and the waste-to-energy sector becoming caught in a minor/major economic depression. Leveraging new technologies will spark change towards an eco-friendly industrial scheme with business risk averseness expediting sustainable development. Research advancements can offer a new lease on life to the biochemical sector. The European Commission must reveal the proximity of the biochemical market and end the unequal distribution of European subsidies to sustain stricken biopolymer producers and beleaguered biochemical companies.One of the main goals of the EU is to bail out low GDP EU members that suffer from significant economic austerity with regard to sustainable infrastructure. Technological breakthroughs in waste treatment techniques, referred to by some as the critical juncture of the biochemical economy, have led to the pledge that bioprocess scientists will expand the scope of end-products generated from waste treatment activities. Contentious arguments over the clinical translation of biomaterials  concomitantly jeopardise the commercialization of these techniques. As suggested by the results of several studies, understanding the operational factors may improve high-temperature technologies.When new bioprocessing technologies become mainstream, there is inevitable deliberation about their sustainability and efficiency prior to market integration. These dilemmas galvanise the debate surrounding fossil-based and green polymers. As a result, chemical companies are edging away from their main fossil-based products and are contending with a surge of investments in biopolymer projects.However, there is scepticism within the chemical industry about whether it is possible to anchor their activities in green plastics . The conThe biopolymer industry’s attempts to keep pace have been ineffective due to limited financial support from the government, dubious applicability, and investor apathy . ResearcBiopolymers encounter sizable barriers to entry and ascension in the polymer economy. Their cost of production eclipses the costs of the production of conventional polymers by 2.5–7.5 times . In addiIn 2021, the annual bioplastic production in Europe was 0.58 million tonnes (European Bioplastics). The worldwide COVID-19 pandemic had profound effects on industries and consumer behaviour. Logistical issues and material and manpower shortages have plagued industry and contracted or wiped-out economic growth. The plastic market was also strongly affected. Packaging is the largest and fastest growing market for biopolymers. Packaging deemed unnecessary was hit hard by the pandemic. However, the pandemic induced a rise in e-commerce and initiated new demand for packaging in essential shipping. A rapid paradigm-shift to the digital age was induced by this global crisis. Companies, to remain competitive, will have to evolve rapidly against this backdrop.Data show that the European market for biopolymers is rapidly expanding, and forecasts indicate the market value is set to increase from 1.2 billion dollars in 2021 to 3.4 billion dollars in 2026 . OverallThis mini compendium described and discussed the biopolymer conundrum and the repercussions for the bio-based economy. The European Union aims to implement a cascade strategy towards the synthesis of biopolymers to address the challenges posed by plastics throughout the value chain. Technological findings and innovations may improve the value chain functionality and drive investments in the right direction. The pouring of millions of Euros and dollars into biopolymers has enticed companies in industries from agribusiness and biotechnology to reduce use of petroleum and chemicals. The allure of a sustainable and greener future has solidified the preferences of investors and bystanders who pin their hopes for the world’s energy future on biopolymers.


Currently, coronary artery disease (CAD) has been identified as the leading cause of mortality in Malaysia and in other countries worldwide. Genetic predisposition and comorbidities such as hypertension and diabetes mellitus, gender, lifestyle, and several other risk factors can contribute to the development of CAD. Pharmacological and surgical treatments play a vital role in improving the quality of life of patients with CAD. New surgical techniques and continuous interventions have been introduced to improve the treatment outcome. Recently, cardiothoracic teams from Universiti Teknologi MARA (UiTM) and Universiti Sains Malaysia (USM) have conducted a 2-day live workshop on off-pump coronary artery bypass (OPCAB) surgery. In this brief communication, we share the highlights and clinical tips of the OPCAB surgery gained from the collaboration. According to the World Health Organization (WHO), 98.9 deaths per 100,000 population due to coronary artery disease (CAD) have been reported in Malaysia for 2012  machine is a fundamental component of CABG, which renders the heart motionless (cardioplegic arrest) and bloodless and, at the same instance, maintains the perfusion to vital organs. Off-pump CABG (OPCAB) surgery was first performed during the 1960s based on the case series described by Professor Kolesov, who is one of the pioneers of cardiovascular surgery . HoweverUpon the initiation of the CPB machine, the blood comes into contact with the extracorporeal circuit of the CPB machine, which then activates the humoral and cellular mediators, leading to a number of adverse consequences related to systemic inflammatory response . This reP < 0.01) between the patient risk profile and reduced perioperative morbidities  besides all-cause mortality  composite outcome of complications or death . Howeverortality .Cannulation or cross-clamping of the aorta in patients with extensive disease of the ascending aorta carries a significant risk of stroke. Hence, OPCAB is the preferred approach by some surgeons who are familiar with its technical nuances . This isConducting a pre-operative team briefing prior to cardiac surgery has been noted to improve communication and reduce errors and costs, according to a pilot study performed at Mayo Clinic . A 5-minIn addition to the standard and essential haemodynamic monitoring, a cerebral oximeter was used to ensure adequate cerebral oxygenation. Transesophageal echocardiography (TOE) is a key monitoring tool in modern cardiac surgery. Being competent in TOE is an added value in managing the haemodynamics during OPCAB. It provides continuous real-time monitoring of the overall cardiac function , facilitTM) and further stabilised with OctopusTM and Genzyme Immobilizer®  is further maintained with vasopressor infusion. Greater than normal filling pressures were required to maintain ventricular filling during anastomoses of posterior and lateral targets. Most of the time, the speed of heart positioning is more dramatic than the displacement itself. Progressive heart positioning, timely MAP adjustments of more than 60 mmHg with intermittent boluses of vasopressor and Trendelenburg position may minimise on the haemodynamic disturbances. After completing all distal anastomoses, the systolic blood pressure was aimed between 90 mmHg and 100 mmHg prior to application of side-biting clamp for proximal anastomoses at the ascending aorta.Close collaboration and good communication between the surgeons and anesthesiologists are pivotal in determining the success of the surgery. It is crucial for the surgeons to pre-emptively communicate with the anaesthesiologist prior to heart manipulation or positioning for prompt acute management of the haemodynamics. Simple maneuver such as small positional change or interventions such as intracoronary shunt or atrial pacing may significantly improve the ability to maintain stability. During anastomoses, significant haemodynamic disturbances such as severe hypotension, extreme bradycardia or recurrent dysrhythmias might occur. It may be necessary to advise the surgeon to stop the anastomosis and let the heart down, allowing it to re-fill and recover. This is at the expense of the coronary artery being still occluded and opened. In the event when both surgeon and anaesthesiologist are concerned of impending cardiovascular arrest before finishing the anastomoses, conversion to on-CPB should be initiated. Decision to convert to either a pump-assisted beating heart  or conventional CABG  needs to be individualised from case-to-case basis. A good surgeon-anaesthesiologist combo should be able to give ample time to the perfusionist team to prepare the CPB machine before the haemodynamic deteriorates and the heart arrests. Consensual decision for conversion to CPB is a matter of safety and should not be viewed as a failure when performing OPCAB.Patient selection, meticulous attention to detail and acquisition of new sets of skills in terms of heart positioning and haemodynamic management are fundamental in ensuring a successful OPCAB due to its narrow margin of safety compared to conventional CABG. Leaving our comfort zone and a significant paradigm shift from routine conventional CABG to OPCAB can be challenging, but this introduces us to a different level of flexibility in offering the best possible and perhaps a safer option for certain group of patients.


Reticulate acropigmentation of Kitamura (RAPK) is a rare genetic hyperpigmentation disorder that is a member of the dyschromatoses characterized by hyperpigmented macules or papules that may interrupt the dermatoglyphics with extra-dermatological manifestations. We present a case of a 29-year-old black male who presented with hyperpigmented atrophic macules both on the extremities and genitals, as well as bilateral clinodactyly of the 5th fingers and inferior gingival hyperplasia with teeth crowding, to draw attention to the novel extra dermatological manifestations of RAPK and the differential diagnosis of cutaneous hyperpigmented lesions. Reticulate acropigmentation of Kitamura (RAPK) is a rare genodermatosis characterized by an autosomal dominant inheritance pattern and multisystem involvement with predominance in females with Japanese heritage. This pigmentary anomaly first appears during childhood and is differentiated from other hyperpigmentation disorders by having sharp and demarcated reticulate hyperpigmented macules encompassing the dorsa of the forearms and hands combined with fine pitting and interruptions in the dermatoglyphics and palmoplantar pits ,2. RAPK A 29-year-old male (Fitzpatrick Skin Type V) with unremarkable past medical history originally presented to the clinic with complaints of a nevus on the foot which was determined to be benign. This initial presentation prompted the incidental finding of hyperpigmentation on the hands and feet. Upon physical exam, stellate hyperpigmented atrophic macules could be visualized. The patient reported the lesions to be present since childhood, and the lesions first appeared on the hands and feet and have been stable since their initial appearance Figure .Family history revealed a sister with similar skin findings on the hands but without a known diagnosis. The patient endorsed similar lesions on his genitals and denied hypopigmentation, associated pruritus, pain, or bleeding from the lesions. Cutaneous examination showed the hyperpigmented lesions contained palmar pitting and breaks in the dermatoglyphs Figure  in additX-ray imaging of the hands was ordered to better characterize the bony changes and displayed mild congenital foreshortening of the fifth finger middle phalanges bilaterally with the remodeling of the distal heads having slight shallow and radially oriented surface articulation of the head of the middle phalanges causing slight radial angulation of the distal phalanges bilaterally and consistent with the extra dermatological presentation of RAPK Figure . Skin biThe classical clinical progression of RAPK begins in childhood with the development of atrophic hyperpigmented papules or macules resembling lentigines on the dorsal palmar-plantar surfaces that coalesce into a reticular, net-like pattern. These lesions may further darken and spread with sunlight exacerbating progression. Other cutaneous manifestations include pitting of the palmar-plantar surfaces and discontinuity of dermatoglyphs . NotablyA mutation resulting in the loss of function of ADAM10, a gene encoding a notch signaling pathway activator metalloproteinase, is key in the pathogenesis of RAPK. The gene typically works in the ectodomain shedding of membrane proteins with L1-CAM, CD44, E-cadherin, N-cadherin, IL-6 receptor and CD30 acting as substrates -10.The differential diagnosis for RAPK includes other inherited reticulate pigmentary disorders and pigmented skin lesions such as reticulate acropigmentation of Dohi (RAPD) ,10. ThesReticulate acropigmentation of Kitamura is a member of an extremely rare family of skin dyschromatoses that may arise during the second and third decades of life. RAPK shares overlapping features with other hyperpigmentation disorders in addition to having extra-dermatological manifestations which make the initial diagnosis challenging. Thus, it is important for clinicians to be aware of the nature, pathology, and treatment options when encountering RAPK as well as the distress the pathology may have on the patient. While the management of RAPK may prove daunting and the efficacy of treatment options is uncertain, the continued research and experimentation with novel immunotherapy may pave the way for improved outcomes.


Artificial intelligence (AI), cognitive computing, machine learning, and brain-inspired computing are among the most trending research focuses in cyber physical systems (CPSs). Brain inspiration computing leads to faster more efficient threat detection in CPSs. This has resulted in the development of brain-inspired computing algorithms including nature-inspired algorithms, genetic algorithms, swarm algorithms, and pattern recognition algorithms, for addressing hard computational problems and CPS research challenges. Cognitive cyber-physical systems (CCPSs) are witnessing a rapid transformation as an interdisciplinary technology that blends physical components and computing devices to enable AI-based solutions. CCPS is integrating machine learning/AI with brain-inspired computing in realizing smart systems. This era is witnessing a rapid transformation in digital technology, AI with brain-inspired computing-based solutions will play a vital role in industrial informatics. The application of CCPSs with brain-inspired computing in the industrial revolution of Industry 4.0 has made smart factories in the industrial evolution. Other applications like smart household devices, medical systems, autonomous driving systems, robotic systems use in connected devices, data analytics, cloud computing, and artificial intelligence automate the process further. These enabling technologies have full capabilities to provide interoperability, information transparency, technical assistance, and decentralized decisions. The fifth industrial revolution is expected to pair humans and machines to further utilize human brainpower and creativity to increase process efficiency by combining workflows with intelligent systems. In Industry 5.0, robots will not only be a programmable machine but will also transform into an ideal human companion for some scenarios. With recent enlargements in brain inspiration computing and AI, it is now possible to create even more realistic and brain intelligence level algorithms. The purpose of this editorial is to explore the research output in enabling CPS technologies and their state-of-the-art approaches, introduce recent advances, and, therefore, show the potential of brain inspiration computing in CCPSs. In this special issue, the published papers have shown comprehensive overviews/methodological approaches to brain-inspired learning and computing, with a focus on applications of interest to CCPSs.Senthilkumar et al. proposed a methodology for a remote authentication scheme with smart card–based healthcare information using the ECC algorithm. The authors have performed an informal analysis to substantiate the claim that the proposed scheme provides sufficient security while maintaining usability. Maintaining user anonymity also ensures that others cannot access data without prior approval of the file owner. It also supports file integrity with the help of an elliptic curve digital signature algorithm. Furthermore, this research shows that the proposed protocol is effective in terms of the communication and computation cost in secure cloud storage of smart card–based healthcare information.The first paper authored by Huang et al., they employed a CNN algorithm to realize the early prediction of refractory epilepsy in children. The results showed that after data preprocessing, CNN can predict and diagnose early refractory epilepsy in children accurately, and had a favorable effect on magnetic resonance imaging (MRI) processing of the patient's brain. This algorithm has high guiding significance in the early diagnosis and treatment of refractory epilepsy in children, and it is worthy of clinical adoption. However, this work does not subdivide the types of refractory epilepsy in children and does not evaluate the specific effects of the proposed algorithm to assist in the treatment.In the next paper by Li et al. has established a CNN algorithm model and applied it to the MRI image segmentation of patients with acute cerebral infarction to evaluate the effect of butylphthalide combined with edaravone treatment on the neurological function of patients. The results showed that MRI images based on the CNN algorithm could clearly show the lesions of patients with acute cerebral infarction. In addition, it was observed that after the treatment of butylphthalide combined with edaravone, the lesion of cerebral infarction became smaller and the condition of artery stenosis gradually improved. These results indicated that CNN-based MRI image segmentation had a high application value in the evaluation of acute cerebral infarction after drug treatment. However, the shortcomings of this study are that the included sample size is small, the source is a single center, and the classification and comparison of patients with acute cerebral infarction at different stages are not completed.The third paper by Peng et al., they proposed a novel OCT-based CCA method for target identification to perform reaching tasks of a 7-DOF robotic arm in the 3D space. An offline experiment and online experiment were designed to confirm the improvements of the OCT-CCA method and the control performance of the robotic arm in the 3D space. The offline comparison results demonstrated that the classification accuracy of the OCT-CCA method outperforms the CCA and IT-CCA methods regardless of the time window lengths. The online experiment was completed by a controlled 7-DOF robotic arm. By focusing gaze on the flickering targets corresponding to the control command, subjects can manipulate the robotic arm as desired. The results showed that all five subjects can complete the designated reaching tasks within the appropriate time window. The success of the online experiment with five subjects demonstrates the simplicity and flexibility of the robotic arm control system in SSVEP-based BCI, which will be a practicable and promising application for disabled individuals in their daily lives.In the last paper by Both authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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Spinal pain predisposes patients to a more sedentary lifestyle, a major risk factor for cardiovascular disease and other comorbidities. There is little recent evidence of the current prevalence of spinal pain and associated risk factors in Wales. This analysis addresses this gap in knowledge.This retrospective e-cohort study used linked National Survey for Wales (NSW) data and Welsh Demographic Services data held in the Secure Anonymised Information Linkage (SAIL) Databank. All years of the annual NSW data from 2016 to 2020  were used to determine the prevalence of spinal pain in Wales. The likelihood of developing spinal pain was quantified by multivariate regression cross-sectional analysis, adjusting for the presence of the same person in multiple years of the survey data. Predictors included socio-demographic and health status, including mental health and cardiovascular disease.Spinal pain affected 5% of people who took part in the NSW. This analysis also shows that spinal pain disproportionally affects some sub-populations of Wales. Factors associated with a greater likelihood of spinal pain were cardiovascular disease, presence of at least one mental health condition, living in a more deprived area, and education level. This is especially pertinent as the burden of cardiovascular risk is disproportionately elevated in the Welsh population and Wales represents a distinctive demographic, characterised by geographical constraints and low socio-economic status. These factors will be presented and discussed in detail.The prevalence of spinal pain and associated risk factors in Wales was quantified. This work will help inform public health action to encourage interventional and prevention strategies to improve the quality of life for those suffering with spinal pain across Wales.