The emergence of cross-modal perception and deep learning technologies has had a profound impact on modern robotics. This study focuses on the application of these technologies in the field of robot control, specifically in the context of volleyball tasks. The primary objective is to achieve precise control of robots in volleyball tasks by effectively integrating information from different sensors using a cross-modal self-attention mechanism.Our approach involves the utilization of a cross-modal self-attention mechanism to integrate information from various sensors, providing robots with a more comprehensive scene perception in volleyball scenarios. To enhance the diversity and practicality of robot training, we employ Generative Adversarial Networks (GANs) to synthesize realistic volleyball scenarios. Furthermore, we leverage transfer learning to incorporate knowledge from other sports datasets, enriching the process of skill acquisition for robots.To validate the feasibility of our approach, we conducted experiments where we simulated robot volleyball scenarios using multiple volleyball-related datasets. We measured various quantitative metrics, including accuracy, recall, precision, and F1 score. The experimental results indicate a significant enhancement in the performance of our approach in robot volleyball tasks.The outcomes of this study offer valuable insights into the application of multi-modal perception and deep learning in the field of sports robotics. By effectively integrating information from different sensors and incorporating synthetic data through GANs and transfer learning, our approach demonstrates improved robot performance in volleyball tasks. These findings not only advance the field of robotics but also open up new possibilities for human-robot collaboration in sports and athletic performance improvement. This research paves the way for further exploration of advanced technologies in sports robotics, benefiting both the scientific community and athletes seeking performance enhancement through robotic assistance. With the rapid advancement of technology, robotics is gradually permeating various fields, including sports. This study aims to enhance robotic skills in volleyball through deep learning and multimodal sensing technology, injecting innovation, and vitality into the realm of sports  to synthesize immersive cyclic motion scenarios is showcased. Through the generative and discriminative processes of GANs, we fabricate authentically textured virtual environments, imbuing robot skill training with heightened challenge and practicality. This augmentation not only fosters skill adaptability but also furnishes an expanded pool of training data, further propelling the prowess of robots.The study maximizes the philosophy of transfer learning, funneling insights gleaned from alternate cyclic motion datasets into the enhancement of robotic skills. This knowledge infusion expedites the robot's mastery of cyclic motion domains, facilitating swift adaptation to competitive settings and accelerated skill growth. This method not only introduces fresh paradigms for robot training but also widens the horizons of transfer learning's applicability in the realm of robotics.The logical structure of this article is as follows. In Section 2, methods, the technical methods used in this study are introduced in detail, including cross-modal self-attention mechanism, adversarial network, and transfer learning. In Section 3, experiments, the experimental environment and data are described, and the evaluation indicators are introduced. At the same time, the experimental results were analyzed in detail, the performance of different methods and data sets were compared, and the effectiveness of the technical method was verified. In Section 4, discussion and conclusion, the research results are summarized, the significance and contribution of the research are evaluated, the limitations of the research are pointed out, and prospects for future work are proposed.In the method part of Chapter 3, we will introduce the overall algorithm flow of this research in detail, and show how to improve the spiking skills of volleyball robots through key technologies such as cross-modal self-attention mechanism, adversarial network, and transfer learning. This comprehensive algorithm process will provide the basis for subsequent experiments and comparative analysis, and also present the overall framework of this study for readers. The overall algorithm flow chart is shown in When dealing with multimodal data, attention mechanisms are powerful tools that allow the model to focus on the most relevant information from different modalities. We leverage a cross-modal self-attention mechanism to effectively integrate data from various sensors for enhancing the skills of our volleyball robot , key vectors (K), and value vectors (V), it can compute attention weights by the following formula:dk is the dimension of the query and key vectors. The dot product operation in this formula expresses the similarity between the query and the key, and then normalizes using the softmax function to get the attention weights. Finally, the weighted values are obtained by multiplying the attention weights with the value vector.where In our study, we further apply the attention mechanism to multimodal data. To synthesize information from different sensors, we introduce a cross-modal self-attention mechanism. In this approach, we take the feature representations of different modalities as queries, keys and values, so that the model can automatically learn the correlation between different modalities.M1 and M2 with corresponding queries, keys, and values Q1,K1,V1 and Q2,K2,V2, respectively. We can compute the cross-modal self-attention weights as follows:Formally, suppose we have two modalities M2 to modality M1.Similarly, we can calculate the attention weight of modality In practical applications, we also need to consider optimization methods such as loss function and gradient descent to train our model. A commonly used optimization function is the cross-entropy loss function, which has good results in multi-classification tasks. For neural network training, we usually use the backpropagation algorithm to calculate gradients and perform parameter updates. Its formula is as follows:p is the actual probability distribution, q is the probability distribution predicted by the model, and i represents the index of the category. By minimizing the cross-entropy loss, the model can better fit the training data, thus improving the accuracy of predictions.where During the training process of the neural network, we use the backpropagation algorithm to calculate the gradient Zhang, , and useThrough the cross-modal self-attention mechanism, we can extract key information from different sensor data, realizing the organic fusion and collaboration of multi-modal data. This provides a more solid foundation for our subsequent Generative Adversarial Network and transfer learning. Next, we will detail how to further improve the skills of volleyball robots with the help of Generative Adversarial Network.Generative Adversarial Networks (GANs) are a deep learning framework that consists of two neural networks called a generator and a discriminator  to extract powerful video features. We divide each video into segments and label each segment indicating whether the segment contains a smashing action. We regard the clips containing the smashing action as positive samples and the clips not containing the smashing action as negative samples.GANs are trained. We used a Conditional Generative Adversarial Networks to train our model  is the objective function of GANs,D(x) is the probability that the discriminator gives the input x is real data, G(z) is the data generated by the generator from the noise vector z, pdata(x) is the real data distribution, and pz(z) is the noise vector distribution. y is extra information, such as category labels. In our method, we use a textual description as additional information, indicating the requirement of the smashing action, such as “the smashing angle is 45 degrees, and the force is 80%”. The training process of GANs can be regarded as a zero-sum game, that is, the discriminator and the generator compete with each other so that the objective function reaches the Nash equilibrium, namely:Among them, 3. GANs application. We use a decoder to restore the sequence of feature vectors of the video clips produced by the generator to a sequence of images, which are stitched into a single video. We compare the generated videos with real volleyball match videos to evaluate their quality and authenticity. We also use the generated videos as training data for the volleyball robot to improve its spiking skills. The output of the decoder can be expressed as:fdec is the decoder function, and ht is the feature vector output by the generator at the t-th moment.Among them, V, while the discriminator tries to maximize V. This leads to a dynamic balancing process at which the samples generated by the generator are realistic enough that the discriminator cannot effectively distinguish real samples from generated samples. In terms of optimization functions, for the generator G, we can use the following optimization functions to update the parameters of the generator:During training, the generator and discriminator are optimized through adversarial learning, specifically, the generator tries to minimize In practical applications, through methods such as backpropagation and gradient descent, the parameters of the generator and discriminator can be gradually optimized to achieve the goal of training GANs.By introducing GANs, we can further improve the skills of volleyball robots and generate more realistic and diverse game scenes, thus laying a more solid foundation for the improvement of robot skills. Next, we explore how transfer learning can be applied to skill improvement for volleyball robots.We use a transfer learning method called domain adaptation :Assuming we have source domain data Among them, Another common approach is Domain Adversarial Neural Network (DANN)  is the domain classifier, f(.) is the feature extractor, and E is the sample. By minimizing Ldomain, we can make features more consistent across domains, enabling transfer learning.Among them, In addition, there is a common method of transfer learning by training an initial model on the source domain, then using the parameters of this model as the initial parameters of the target domain model, and then fine-tuning the model parameters on the target domain. This can be achieved by minimizing a loss function over the target domain:ftarget is the model on the target domain, Dtarget is the data distribution of the target domain,  is the sample of the target domain, and ℓ represents the loss function.Among them, Optimization methods for transfer learning usually consist of two steps: feature extraction and fine-tuning. In the feature extraction stage, we can extract general feature representations from the source domain through pre-trained models. Then, in the fine-tuning stage, we train the extracted feature representations together with data from the target domain to further adapt to the target domain. Specifically, the fine-tuning optimization function can be expressed as:Lsource represents the loss function on the source domain, and λ is a hyperparameter that weighs the two losses.Among them, Through transfer learning, we can make full use of the knowledge of the existing modality in the task of volleyball robot and improve the performance of the model in the new modality.In the Section 2 of this chapter, we propose a method that comprehensively applies attention mechanisms, GANs, and transfer learning to improve the skills of volleyball robots. First, we introduce a cross-modal self-attention mechanism, which effectively integrates multi-modal sensor data, enabling the model to automatically learn the correlation between different modalities. By calculating attention weights, we are able to extract key information from different sensor data, laying a solid foundation for the subsequent steps. Then, we introduced the application of GAN. Through domain adaptation and domain confrontation neural network, the knowledge transfer between the source domain and the target domain is realized, thereby improving the generalization ability of the model in the target domain. Finally, we explore how to train the initial model on the source domain and fine-tune the parameters on the target domain to fit the data distribution of the target domain through transfer learning. The comprehensive application of these methods provides strong support for our experimental part. In the next chapter, we will introduce the experimental design and result analysis in detail to verify the effectiveness and performance improvement of our proposed method in improving the skills of volleyball robots.The experimental process of this paper is shown in In this research, we rely on an advanced computing platform as the hardware environment, which is equipped with a high-performance AMD Ryzen 7 5800X processor, equipped with 64GB ultra-high-speed DDR4 memory, and configured with 2 NVIDIA GeForce RTX 3080 10GB graphics card. This excellent hardware configuration endows us with powerful computing and storage capabilities, especially suitable for training and inference of deep learning tasks. In addition, we also use multi-channel SSD hard disk to ensure the high efficiency of data reading and storage. Such a hardware environment provides strong support for the smooth progress of the experiment, making the training process of the model more efficient, stable, and reliable.Hardware EnvironmentIn this study, we used Python and PyTorch to implement a method for improving the spiking skills of volleyball robots based on deep learning. As the main deep learning framework, PyTorch provides us with powerful model building and training tools, allowing us to flexibly design and optimize our spiking skill model. In the experiment, we made full use of PyTorch's efficient computing power and automatic differentiation function to speed up the model training process, so that our model can converge faster and achieve better results.Software EnvironmentVolleyball Dataset is a video action recognition dataset proposed by Ibrahim et al. of Simon Fraser University in Canada in 2016. The data set consists of 55 volleyball game videos, in which 4830 key frames mark the player's position, individual action and group behavior. Single action includes 9 categories, such as smash, block, pass, etc. Group behavior includes 8 categories, such as passing the ball to the left, scoring from the right, and both sides scrimmage. This dataset aims to provide a challenging scenario for studying the recognition and understanding of human actions and group activities in videos. It can be used for a variety of video analysis tasks, such as action recognition, group activity recognition, person tracking, etc. This dataset has been used and cited by several research papers, demonstrating its value and influence in the field of video analysis.Volleyball DatasetVREN is a video volleyball game dataset proposed by Xia et al. at the University of California, Santa Barbara in 2022. This dataset contains video clips from professional and NCAA Div-I indoor volleyball matches, where each round is annotated with a volleyball description language. This language can completely describe the player's action, position, and volleyball trajectory in the volleyball game. This dataset aims to provide a rich and high-level benchmark for studying the skills of robots in volleyball games. Based on the language, this dataset proposes three tasks for automated volleyball action and tactical analysis: (1) volleyball round prediction, which aims to predict the outcome of rounds and help players and coaches improve decision-making in practice; (2) setter type and Smash type prediction, helping athletes, and coaches to prepare for the game more effectively; (3) Volleyball tactics and offensive zone statistics, providing advanced volleyball statistics to help coaches better understand the game and opponent's tactics. The authors conduct a case study showing how experimental results can provide insight to the volleyball analysis community. Furthermore, experimental evaluations on real data establish a baseline for future research and applications. The research bridges the gap between the field of indoor volleyball and computer science.VREN: Volleyball Rally Dataset with Expression Notation LanguageThe UCF101 dataset is a video action recognition dataset proposed by Soomro et al. at the University of Central Florida in 2012. The dataset consists of 13,320 real action videos from YouTube, covering 101 action categories. These action categories can be divided into five types: human-object interaction, body movement, human-human interaction, playing musical instruments, and sports, some of which are related to volleyball, such as smashing, blocking, passing, etc. This dataset is an extension of the UCF50 dataset, which has only 50 action categories. The UCF101 dataset is highly diverse and challenging because there are a large number of changes in camera motion, object appearance and pose, object scale, viewing angle, background clutter, and lighting conditions in the video. This dataset aims to facilitate further research in the field of action recognition by learning and exploring new categories of real actions.UCF101The MultiSports dataset is a video multiplayer sports action detection dataset, which was proposed by Li et al. of Nanjing University in 2021. The dataset consists of 3200 video clips of sports games from YouTube, covering 4 sports categories: aerobics, basketball, football, and volleyball. The dataset annotates 37,701 action instances and 902k bounding boxes, and each action instance has a fine-grained action category label, such as smashing, blocking, passing, etc. This dataset aims to provide a rich and challenging benchmark for studying multi-person video action detection. The dataset has the characteristics of high diversity, high density, and high quality, and can reflect real sports competition scenes.MultiSports datasetIn the assessment process of this research, in order to comprehensively and objectively measure the effectiveness and performance of the proposed sports teaching method, a series of key evaluation metrics were employed. These metrics not only facilitate a quantitative evaluation of the model's performance across various tasks but also provide us with in-depth insights to better comprehend the strengths and limitations of the method. In the following section, we will provide a detailed introduction and analysis of the following key metrics: accuracy, recall, precision, and F1 score. These metrics will assist us in objectively evaluating the efficacy of the proposed method in the context of sports teaching, thereby providing robust support for the reliability of the research and the feasibility of its practical application.In the skill improvement task of the volleyball robot, the hitting rate is a critical evaluation metric used to measure the performance of the proposed method. The hitting rate is defined as the ratio between the number of events correctly predicted by the model and the total number of samples. It provides an intuitive reflection of the model's prediction accuracy, aiding in the assessment of its performance. The hitting rate can be calculated using the following formula:Hit rateIn the context of skill enhancement tasks for the volleyball robot, the hitting rate is a pivotal evaluation metric used to gauge the performance of the proposed method. The hitting rate is defined as the ratio between the number of correctly predicted positive samples , indicating the number of instances where skill improvement was accurately identified, and the total number of samples. Similarly, the correctly predicted negative samples  represent instances where the absence of skill improvement was accurately recognized. Conversely, the false positives (FP) correspond to instances where the model erroneously predicted positive samples when they were, in fact, negative. The false negatives (FN) denote cases where the model inaccurately predicted negative samples as positive.By calculating the hitting rate, we gain insights into the model's accuracy in predicting skill levels, thereby evaluating the practicality and effectiveness of this approach in real-world sports teaching scenarios. In our research, the hitting rate will serve as a critical evaluation metric, assisting us in conducting a thorough analysis of model performance and providing robust support for subsequent experimental findings.In the skill enhancement task of the volleyball robot, recall is a critical evaluation metric used to assess the effectiveness of the proposed attention-based mechanism in capturing the skill level of volleyball players. Recall measures the model's ability to correctly identify actual positive samples, i.e., the proportion of samples that the model correctly predicts out of all actual positive samples. This is of significant importance for evaluating the model's overall performance in sports education. Recall can be calculated using the following formula:RecallIn the context of skill enhancement tasks for the volleyball robot, recall is a crucial evaluation metric used to assess the model's ability to correctly identify positive samples. Specifically, it measures the proportion of samples that the model accurately predicts as skill level improvements out of all actual positive samples in the volleyball skill enhancement task. Conversely, false negatives (FN) represent the positive samples that the model fails to predict accurately, indicating instances where skill level improvements were missed.By computing the recall rate, we gain insights into the model's capacity to recognize positive samples, thus evaluating the effectiveness of the attention-based mechanism in enhancing the volleyball robot's skills. In our research, recall will serve as a vital evaluation metric, enabling us to conduct an in-depth analysis of model performance, providing a comprehensive assessment, and supporting subsequent experimental results.In the context of skill enhancement tasks for the volleyball robot, precision is a critical evaluation metric used to measure the accuracy of the attention-based method in predicting the skill level of volleyball players. Precision assesses the proportion of samples that the model predicts as positive samples, which are indeed positive samples in reality. This is of paramount importance for evaluating the reliability and accuracy of the model in sports education. Precision can be calculated using the following formula:PrecisionTP (True Positives): The number of positive samples correctly predicted by the model, indicating the instances where skill level improvement was accurately identified. FP : The number of positive samples incorrectly predicted by the model, signifying the instances where the model erroneously predicted negative samples as positive.By calculating precision, we gain insights into the model's accuracy when predicting positive samples, thereby evaluating the effectiveness of the attention-based method in the volleyball robot's skill enhancement task. In our research, precision will serve as a crucial evaluation metric, aiding us in analyzing model performance, providing a dependable assessment, and supporting our experimental results.In our study of skill enhancement in volleyball robots, the F1 score serves as a critical evaluation metric employed for the comprehensive assessment of the method's performance in skill improvement. This score takes into account both precision and recall, thus facilitating the equilibrium between the model's accuracy and comprehensiveness in identifying skill improvement instances. Consequently, it provides a more comprehensive performance measurement metric. The formula for calculating the F1 score is as follows:F1 ScoreIn this formula, we introduce previously discussed precision and recall as parameters. Precision measures the accuracy of the model in identifying positive samples as positive samples, while recall gauges the model's comprehensive recognition capability of positive samples.The F1 score combines the accuracy and comprehensiveness of the model in skill improvement cases, making it a crucial evaluation metric in the volleyball skill enhancement study. By calculating the F1 score, we can gain a more comprehensive understanding of the method's performance, ensuring that the model achieves accurate and comprehensive results in skill improvement.In the preceding sections, we provided a comprehensive introduction to the design and implementation of the multimodal perception-based deep learning approach for enhancing volleyball robot spiking skills. In this chapter, our focus shifts toward a comparative analysis of experimental results, aiming to comprehensively evaluate the effectiveness and superiority of the proposed methods. By conducting experiments on multiple datasets, our goal is to delve into the contributions of different models and their combinations in enhancing volleyball robot skills, as well as to validate the applicability of our approach across various scenarios. This process of experimental comparison and analysis not only directly showcases the practical effectiveness of our approach but also provides deeper insights, guiding us toward optimizing and advancing the technological trajectory of sports robots.Through comparing experimental results across different datasets, we will uncover the performance of the multimodal perception-based deep learning approach in varying contexts. Simultaneously, we will integrate the evaluation metrics introduced earlier, such as hit rate, recall rate, precision, and F1 score, to conduct a comprehensive assessment of the overall model performance. We will also analyze the introduction of different modules, exploring the specific roles of cross-modal self-attention mechanisms, GANs, transfer learning, and other methods in enhancing volleyball robot skills. In-depth analysis of the experimental results will allow us to understand the interplay between different modules and their impact on enhancing robot skills.Furthermore, we will compare the experimental results with those of the baseline models to quantify and illustrate the superiority of our approach. Through comparative analysis, we can accurately evaluate the performance improvement brought about by the multimodal perception-based deep learning approach in enhancing volleyball robot skills. These comparative and analytical results will further validate the feasibility and practicality of our approach, providing robust support and references for research and applications in the field of sports robotics.Next, we will meticulously dissect the experimental results, comprehensively showcasing the performance of our model across different datasets and metrics, providing readers with a comprehensive understanding of the model's capabilities and its potential value in real-world applications.From the data in According to the comparative data of Hit Rate, Recall, Precision, and F1 Score of different methods on the two datasets in According to the data in From the data in In conclusion, the multimodal deep learning-based robot action recognition method proposed in this study demonstrates significant advantages in experiments conducted on multiple classic volleyball datasets and a large-scale diverse action dataset. By leveraging attention mechanisms to integrate visual and motion features, along with the incorporation of deep adversarial mechanisms to enhance model generalization, the accuracy and recall rate of action recognition have both been notably improved. Particularly, with the integration of the optimized model structure, our method achieves impressive recognition performance across all tested datasets, thus fully validating the reliability and potential of this approach in action recognition tasks.Through detailed data comparison and analysis, we can clearly witness how the seamless integration of various modules within the model's structure drives the continuous enhancement of recognition capabilities. This not only underscores the correctness of the deep learning architectural approach but also confirms the vital roles of attention mechanisms and adversarial learning in multimodal feature learning. While rooted in the context of volleyball robot requirements, experimental results indicate its promising applicability to other action recognition tasks, further showcasing the method's versatility.In summary, this work successfully designs and implements a deep multimodal learning algorithm to optimize action recognition capabilities, laying down a methodological foundation for the advancement of robotic sports skills.In preceding chapters, we provided an extensive account of the application of multimodal deep learning methods to enhance robotic cyclic motion skills. In this chapter, we delve into a comprehensive discussion of research outcomes, summarizing key findings from experiments, exploring the significance and contributions of this study, analyzing the strengths and limitations of our approach, and outlining potential avenues for future research.Through meticulous experimentation and analysis, we observed substantial accomplishments in enhancing robotic skills via multimodal deep learning. The introduction of the cross-modal self-attention mechanism proficiently fuses information from distinct sensors, culminating in comprehensive scene perception. Leveraging Generative Adversarial Networks (GANs) imbues the model with superior data generation and training capabilities, enriching the diversity and practicality of skill training. The implementation of transfer learning further expedites skill augmentation, minimizing the temporal cost of relearning in new environments. The confluence of these modules facilitates remarkable skill enhancement across several pivotal metrics, presenting a positive contribution to the realm of sports robotics.The significance of this study resides in its insightful and empirical contribution to the progression of cyclic motion robotics. The seamless integration of multimodal perception and deep learning not only elevates robotic prowess in volleyball matches but also ushers in novel prospects for intelligent sports competition and human-robot collaboration. Our research not only theoretically validates this approach but also substantiates its practical efficacy, offering a valuable reference for researchers in related domains.Throughout this study, we harnessed the inherent advantages of multimodal perception, synergizing information from diverse sensors. This multimodal data processing strategy not only heightens model performance but also enhances robot scene awareness. Simultaneously, our research introduces pivotal technologies such as self-attention mechanisms, GANs, and transfer learning, fully harnessing the potential of deep learning and providing diverse tools and avenues for skill augmentation. However, we acknowledge certain limitations, such as potential model generalization issues stemming from experimental data distribution and the possible challenges and constraints in real-world applications.Future research directions could encompass the expansion of our approach to diverse sports domains, unraveling the broader potential of multimodal perception and deep learning. Concurrently, optimizing model architectures and algorithms could enhance the efficacy and swiftness of skill augmentation. Furthermore, applying our approach to real volleyball match scenarios could authenticate its viability and efficacy in actual competition. Ultimately, we anticipate our continued research and practical efforts will contribute significantly to the advancement of sports robotics and intelligent sports competition.The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.MW: Conceptualization, Data curation, Project administration, Resources, Writing—original draft. ZL: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Resources, Writing—original draft, Writing—review & editing.


Philosophers and psychologists have debated the wisdom of using feelings as a source of information when making decisions. While not trying to solve this debate, a complementary approach is to examine how metacognitive feelings are used when generating, evaluating, and selecting ideas to solve creative problems and whether their use leads to accurate idea evaluation and selection. Hence, this conceptual article aims to explore how metacognitive feelings are used to evaluate and select creative ideas. Interestingly, while metacognitive feelings come from the perceived ease or difficulty of generating solutions to creative problems, these feelings also inform the decision to continue generating ideas or stop. Metacognitive feelings are then an integral part of the creative process of generating, evaluating, and selecting ideas. The present article briefly reviews the history of metacognitive feelings as examined in metamemory, meta-reasoning, and judgment formation in social psychology, before discussing their implications and potential for understanding the creative process. The article ends by positing directions for future research.  The examination of metacognition is an exciting field of inquiry with multiple contributions from meta-memory e.g., , meta-reCreativity scholars suggest adopting a dynamic definition of creativity where the observed originality and effectiveness of the ideas generated are in constant development and rarely truly finalized . When inUnder this dynamic conceptualization of creativity, creativity is defined as something with potential originality and effectiveness. The potential originality and effectiveness are first assessed by idea generators and sometimes, after, by an audience. Metacognitive feelings could have implications for self- and other assessments of potential originality and effectiveness, yet my focus is on self-evaluation and selection.1Even though there seems to be a general understanding that creativity mainly focuses on divergent thinking problems or ill-defined problems, the literature on creativity has not extensively addressed the influence of types of problems on metacognition. Specifically, and making an over-generalization, most problems used in meta-memory and meta-reasoning are problems with well-defined answers and with single correct answers. Conversely, divergent thinking problems do not have single, correct solutions. This difference makes the assessment of one´s solutions to a problem more difficult for divergent thinking problems. Hence, self-assessments could be more inconsistent and less accurate for divergent thinking problems. In addition, while problems with a single, correct solution might also have external validation (a professor or software checking the correct answer), they do not need to. Individuals might self-assess the correctness of an answer with high levels of accuracy. Conversely, the solutions to ill-defined problems almost always need the validation of an audience. This additional validation, which is almost always needed, increases the uncertainty of any judgment of potential originality and effectiveness with important metacognitive consequences. Combining the discussion of the types of problems found in most creativity research with the definition of creativity emphasizing potential originality and effectiveness sets the stage for pointing out the main similarities and differences between metacognitive processes in meta-memory, meta-reasoning, judgment formation in social psychology, and creativity. I emphasize the role of metacognitive feelings and focus on suggesting implications for creativity research. The mind is capable of generating outputs in the form of answers to memory questions, judgments about self-qualities, answers to reasoning problems, and solutions to creative problems. In addition, the mind can also monitor the quality of its own outputs. The distinction between generating and monitoring cognitive processes has been conceptualized as object- and meta-level processes . This diTo provide an example, in memory research, one of the most used experimental tasks is to ask participants to study a list of items and then make an estimate of the likelihood of recalling the studied items in a subsequent test . ResultsSimilarly, in meta-reasoning research, one of the most often used experimental tasks is solving syllogisms, in which participants are asked to estimate the validity of a conclusion based on a set of implicit rules of logic. Individuals should pay attention to the rules of logic without considering whether the conclusion is believable or not. Empirical findings suggest that individuals do pay attention to how believable the conclusion is even when the conclusion is invalid , when reasoning about the validity of a conclusion (meta-reasoning), and when self-evaluating how assertive they are by recalling examples of assertiveness  from their personal past. The main differences, as explained earlier, are that creativity problems have more uncertainty and more ambiguous criteria. Consequently, the work on education, memory, reasoning, decision-making, and social psychology has served to develop our understanding of how metacognition functions with the main difference that creative problems do not have single, correct solutions and have more ambiguous evaluative criteria. Creativity scholars have used previous work on metacognition to draw implications for creativity research see , yet morGoing back to the basic question that idea generators have to answer about the potential originality and effectiveness of the ideas generated, I point out that individuals rely on different available sources of information to make such inferences . A sourcMetacognition scholars suggest three facets of metacognition: knowledge, experiences, and monitoring and control . MetacogGiven the interaction between metacognitive knowledge, experiences, and monitoring and control, it is likely that metacognitive feelings influence and are influenced by metacognitive knowledge, control, and monitoring. Hence, I posit that knowledge, experiences, and monitoring and control are part of creative metacognition. Consequently, I expect different indicators of metacognitive knowledge, experiences, and monitoring and control to relate to each other (see Creativity scholars have paid attention to creative self-efficacy as a relevant self-belief for the creative process, given its positive relationship with the originality and effectiveness of the ideas generated . The relFor example, in one empirical study, researchers manipulated ease of recall, a form of metacognitive feeling, by asking participants to bring to mind a few versus many examples of creative idea generation from their personal past . The corRegarding the option of creative self-efficacy acting as an antecedent of metacognitive feelings, one study found a positive relationship between creative self-efficacy and metacognitive feelings . CreativGiven the promising results just explained, future studies could extend the examination of creative beliefs to include creative personality identity and creative mindsets as possible antecedents of metacognitive feelings (see The use of feelings as a source of information has been examined in metacognitive research and in research on emotional intelligence see . The proFor example, researchers conducted two studies involving the generation of ideas to solve marketing problems and then the evaluation of the ideas generated by participants and judges. In both studies, metacognitive feelings were collected right after the idea-generation task concluded and focused on assessing ease of idea generation . In studIn another empirical investigation, three studies were conducted examining metacognitive feelings . In all In one study examining consequences of metacognitive feelings, the results showed that feelings significantly informed self-evaluations and post-task creative confidence . What thAn interesting twist to the study was the result that the serial order effect found in previous investigations  only helLast, in another empirical investigation with two studies, metacognitive feelings were again a significant predictor of self-evaluations, and more importantly, they were a significant predictor of evaluative self-efficacy . EvaluatA few tentative conclusions can be drawn from the empirical studies just reviewed. First, given that significant correlations have been found between metacognitive feelings and indicators of metacognitive knowledge and monitoring and control, there is no doubt that feelings play an important role. Metacognitive feelings inform the creative process. Second, creative self-efficacy has a positive relationship with metacognitive feelings. Metacognitive knowledge interacts with metacognitive experiences, facilitating the experience of ease of idea generation when individuals have confidence in their abilities to generate original and effective ideas. Metacognitive feelings inform the process of evaluating and selecting ideas, the relevance of the strengths and weaknesses of the ideas generated, and the belief in the ability to correctly select the most creative ideas. More research is needed to replicate some of these findings and test potential moderators (see As stated at the beginning of the article, there has been a heated debate about the wisdom of using feelings when making judgments, decisions , and selBefore beginning to examine how feelings influence the creative process, it is important to explain what better performance or more accurate performance means in terms of idea generation, evaluation, and selection. The issue of intelligent use of feelings and emotions often needs a gold-standard criterion to establish whether feelings help or limit the process of generating, evaluating, and selecting creative ideas. For example, studies have conceptualized better creative potential as the generation of a greater quantity of creative ideas as rated by independent judges. Self-reports of creative performance have also been used, but using judges is considered a more valid and reliable approach. Similarly, studies have examined accurate idea evaluation and selection and conceptualized them as the match between idea generators’ evaluations and selections and judges’ evaluations and selections of the same set of ideas. I only discuss findings consistent with the conceptualization just explained, which includes judges’ evaluations and selections of creative ideas. Regarding the intelligent use of feelings, the first possibility is to assess the relationship between feelings and different indicators of idea generation, often referred to as creative potential. Empirical findings on the positive influence of emotional intelligence on creative potential have supported the idea that emotional intelligence is important for generating ideas by influencing attention allocation . In addiA second possibility is that feelings could influence the process of idea evaluation and selection. Regarding the use of feelings when evaluating and selecting ideas, I can use the studies just reviewed to draw some preliminary conclusions, focusing specifically on metacognitive feelings. First, there is no doubt that feelings inform the process of evaluating and selecting ideas. Researchers have found consistent and positive relationships between metacognitive feelings and self-evaluations of the ideas generated , the relRegarding the use of feelings in accurate idea evaluation and selection, it is more difficult to reach a conclusion. For example, metacognitive feelings were positively correlated with the overestimation of the creativity of the ideas generated, which then had a negative relationship with accurate idea selection . SimilarIn sum, more empirical studies are needed to determine with greater certainty when feelings, including metacognitive feelings, limit or facilitate idea generation, evaluation, and selection. From the empirical studies reviewed, we might conclude that metacognitive feelings inform the process of idea generation, selection, and evaluation.The work on metacognition across different disciplines is abundant. Similarly, the examination of metacognitive feelings is also vast (see The interpretation of metacognitive feelings in the form of ease of idea generation is a relatively neglected area of research. When developing ideas, it is important how individuals feel, and it is also as important how individuals interpret these metacognitive feelings. To simplify things, experiencing ease of idea generation could be interpreted as a sign of high ability or as a sign that the task is easy. This interpretation likely comes from the lay belief that good idea generators should be able to develop ideas with ease. Individuals could also experience difficulty in idea generation. This difficulty could be interpreted as a sign of low ability or as a sign that the task is difficult. Another example of how the interpretation of metacognitive feelings matters comes from social psychology. One of the first studies on metacognitive feelings found that recalling more instances of assertive behavior led participants to rate themselves as less assertive than recalling fewer instances . This fiThus far, the attention paid to metacognitive feelings has been limited, and even more limited has been the attention paid to the interpretation of these feelings. I see great potential for examining the interpretation of metacognitive feelings during the creative process.As suggested earlier, the concept of potential originality and effectiveness, along with the concept of inconclusiveness of creative outcomes, set the stage for examining additional motivational consequences of metacognitive feelings and idea evaluation and selection. Future research could examine the relationship between metacognitive feelings and persistence, effort, interpretation of negative feedback, and attributions, among others. Similarly, overestimation of the creativity of ideas as informed by metacognitive feelings could lead to higher persistence and effort in idea refinement. Future studies could test this possibility.In sum, metacognitive feelings inform the creative process of generating, evaluating, and selecting ideas. The use of feelings, as reflected in significant relationships with important outcomes, sometimes leads to adaptive and other times to not-so-adaptive outcomes. Creativity scholars should continue paying attention to metacognition and examining the intelligent use of metacognitive feelings during the creative process.


The impact of heat stress on reproduction is complex and multifactorial and is compounded by growing challenges due to climate change. Both animal welfare and fertility are vulnerable parameters easily affected by heat stress. Heat stress leads to a marked decrease in the developmental competence of oocytes and the fertilizing capacity of spermatozoa, leading to a declining reproduction rate and losses for the cattle industry. There is an urgent need to find viable methods of alleviating the effects of global warming on animal welfare and fertility and, accordingly, guard the reproductivity, productivity, and profitability of cattle farms.In recent decades, the adverse effects of global warming on all living beings have been unanimously recognized across the world. A high environmental temperature that increases the respiration and rectal temperature of cattle is called heat stress (HS), and it can affect both male and female reproductive functions. For successful reproduction and fertilization, mature and healthy oocytes are crucial; however, HS reduces the developmental competence of oocytes, which compromises reproduction. HS disturbs the hormonal balance that plays a crucial role in successful reproduction, particularly in reducing the luteinizing hormone and progesterone levels, which leads to severe problems such as poor follicle development with a poor-quality oocyte and problems related to maturity, silent estrus, abnormal or weak embryo development, and pregnancy loss, resulting in a declining reproduction rate and losses for the cattle industry. Lactating cattle are particularly susceptible to HS and, hence, their reproduction rate is substantially reduced. Additionally, bulls are also affected by HS; during summer, semen quality and sperm motility decline, leading to compromised reproduction. In summer, the conception rate is reduced by 20–30% worldwide. Although various techniques, such as the provision of water sprinklers, shade, and air conditioning, are used during summer, these methods are insufficient to recover the normal reproduction rate and, therefore, special attention is needed to improve reproductive efficiency and minimize the detrimental effect of HS on cattle during summer. The application of advanced reproductive technologies such as the production of embryos in vitro, cryopreservation during the hot season, embryo transfer, and timed artificial insemination may minimize the detrimental effects of HS on livestock reproduction and recover the losses in the cattle industry. Cattle are homeothermic animals that maintain a specific constant body temperature; however, due to variations in environmental temperatures and humidity, their body temperature changes . Cattle,Similarly, the two breeds of bulls called Angus and Nellore have different patterns of blood methylation due to HS. The methylation pattern in the Nellore breed is more focused on defensive and survival pathways in regard to HS, while the Angus breed’s methylation pattern is less focused on survival . HS has Heat stress (HS) occurs due to elevated ambient temperatures above the thermoneutral zone, along with high humidity and slow air movement ,11. The High temperatures and humidity are the main factors responsible for HS, which, in turn, adversely affect reproductive performance . RespiraThe objective of this review is to shed light on the mechanisms of heat stress in regard to the fertility of cattle. We also attempt to cover the available strategies employed to relieve the effects of HS on reproduction in the changing climate scenario.Cattle production losses from HS were estimated to represent 98% of the value of the production of meat and milk in 2005 . In dairThe sympathetic–adrenomedullary system (SAM) and the hypothalamic–pituitary–adrenocortical axis (HPA) constitute the sympathetic autonomic and adrenal medulla, and this whole system is activated by HS. The hypothalamus is the regulatory point that responds to HS in cows. When the SAM system is activated, there is a higher secretion of catecholamines, adrenaline (A), and noradrenaline (NA) in the bloodstream, which, in turn, affects the functions of the internal organs. This system is activated on exposure to HS to cope with its detrimental effects . The higHS affects fertility and inhibits livestock reproductive performance through hormonal imbalance. The main critical factors that control ovarian activity are the hypothalamic gonadotropin-releasing hormone (GnRH) and the anterior pituitary gonadotropins (FSH and LH). The effect of HS on gonadotropins is controversial . HS suppThe estrous cycle refers to the cyclic pattern of ovarian activity that enables female animals to establish pregnancy following mating, while the term estrus refers to the phase when a female is sexually receptive to males. A significant reduction in the fertility of cattle was reported during summer due to the effect of HS in increasing body temperature . MoreoveLactating cows are very sensitive to low fertility because lactation is associated with increased metabolic heat, which reduces the timing and strength of estrus, reduces the conception rate, and increases embryo mortality . The estMOS, GDF9, and POUF51) involved in the development of oocytes and their competence in various cell stages [The quality of oocytes is reduced during summer due to HS, causing great losses for dairy producers . The oocl stages . Poor-qul stages , leadingl stages . Bovine l stages . During l stages .HS also alters the hormonal balance of cattle, which reduces oocyte quality . In warmThe reproductive capacity of cows declines due to the detrimental effect of HS on the process of oogenesis. When cattle are exposed to HS, abnormal hormones are released from the hypothalamus, leading to poor follicles and low-quality oocytes. These low-quality oocytes compromise fertility and reproduction .Males are at a higher risk of the adverse effects of high environmental temperatures and relative humidity, which can reduce sperm production and decrease male fertility rates . The proProperties like morphology, motility, plasma membrane integrity, metabolic activity, and the capacity for acrosome reaction define the quality of semen . In bullThe ability of spermatozoa to penetrate an oocyte and activate it to develop an embryo is called fertilization . SuccessHS not only affects fertilization and the reproduction rate in vivo but also reduces embryo production in vitro by reducing the quality of oocytes obtained from ovaries recovered from slaughterhouses, resulting in a sharp decline in the in vitro production of cattle embryos . FertiliIn cattle, the activation of the embryo genome takes place after the first stage of cleavage (after the four-cell stage); hence, in this stage, the embryo is highly susceptible to any kind of stress, including HS . The gen2O2) and superoxide anion (O2−) were increased in vitro [HS increases the concentration of ROS, which leads to damage to the developing embryo . It was in vitro , which rin vitro ,94. HS iin vitro . In hot in vitro . In Louiin vitro . In addiin vitro .A decreased gestation length has been reported following exposure to HS during gestation . The expIn cattle, the embryonic period starts with the fertilization of the ovum by the sperm and lasts until differentiation 42 days), while fetal development ranges from day 42 to the birth of the fetus. Pregnancy loss is usually observed on day 35, before the fetal development stage , and the days, whLower reproductive efficiency under heat stress can be minimized by adopting appropriate scientific strategies involving physical amendments to the environment and the genetic improvement of heat-stress-tolerant breeds ,110. MorThe effects of HS on the estrous cycle and the reproductive efficiency of cattle can be reduced by providing shade and air conditioning during the hot summer season to minimize losses to the cattle industry . Three mRecent studies indicated that in summer, HS can alter gonadotropin, depress LH secretion, and decrease cow fertility . A potenThe exposure of animals to HS during summer reduces the intensity and length of estrus and consequently increases the incidences of silent ovulation and anestrous females. Therefore, the use of ovulation synchronization and timed AI protocols are practiced to improve fertility and overall pregnancy rates in summer because all cows are inseminated without estrus detection . FurtherGiven that the exposure of oocytes to HS hastens germinal vesicle breakdown and leads to rushed oocyte aging , fertiliCattle are an indispensable milk and meat production resource. Heat stress (HS) is a strong barrier to cattle reproduction and, hence, poses an alarming threat to normal life. The primary targets of HS are the pituitary gland and hormonal balance, changes in which, in turn, negatively affect the estrous cycle, follicle synthesis, and oocyte maturity and, ultimately, reduce the reproduction rates of cattle in the hot season . AlthougImmediate and future priorities must be defined to mitigate the adverse effects of HS on livestock production. A wide range of available options, including proper housing, new approaches to shading, advanced cooling systems, and advanced biotechnological strategies, are required to reduce environmental stresses. The use of genome-wide association studies to identify the relationships of DNA markers linked to production and reproduction traits with HS would be a strategic approach to alleviate the effects of HS on the productivity and selection of animals with greater adaptive capability. One of the most critical research issues is to elucidate the mechanisms of HSP and the relationship between HSP tissue concentrations and livestock fertility. Additional research will be needed for the incorporation of new technologies, such as transgenesis, which could enable the genetic improvement of livestock in the future through the knock-out of undesirable genes or the knock-in of desirable genes to reduce the impact of HS on animal productivity.


One of the most popular and effective orthopedic surgical interventions for treating a variety of hip diseases is total hip arthroplasty. Despite being a radical procedure that involves replacing bone and cartilaginous surfaces with biomaterials, it produces excellent outcomes that significantly increase the patient’s quality of life. Patient factors and surgical technique, as well as biomaterials, play a role in prosthetic survival, with aseptic loosening  being linked to the quality of biomaterials utilized. Over the years, various biomaterials have been developed to limit the amount of wear particles generated over time by friction between the prosthetic head  and the insert fixed in the acetabular component (polyethylene or ceramic). An ideal biomaterial must be biocompatible, have a low coefficient of friction, be corrosion resistant, and have great mechanical power. Comprehensive knowledge regarding what causes hip arthroplasty failure, as well as improvements in biomaterial quality and surgical technique, will influence the survivability of the prosthetic implant. The purpose of this article was to assess the benefits and drawbacks of various biomaterial and friction couples used in total hip arthroplasties by reviewing the scientific literature published over the last 10 years. Total hip arthroplasty (THA) significantly changed the treatment of patients handicapped by arthritis in the 1960s, producing favorable long-term results and thus becoming one of the most successful orthopedic surgical interventions .Nowadays, it is estimated that, annually, more than one million patients require an artificial hip to replace the affected joint  and, in The prosthetic hip implant includes two metal components fixed in the bone: the stem inserted into the femoral canal after its preparation with specific rasps and the acetabular shell fixed in the pelvis after reaming with consecutive acetabular reamers .The prosthetic head attached to the femoral stem articulates with the liner inside the metal acetabular implant, thus causing movement of the hip joint. The prosthetic articular surfaces of the hip can be made of different materials: metal or ceramic head; ceramic, metal, or polyethylene acetabular insert. The mobility between these articular surfaces creates a frictional element that causes wear of the acetabular insert over time and the release of particles in the joint ,13,14. WThe incidence of total hip arthroplasty revision is estimated to increase from 43 to 70% in the 2014–2030 period ,16. SomeWith the increase in the patient’s quality of life, we are witnessing an increase in the indication for surgery, with age no longer being a contraindication or a limitation of the intervention; thus, the indication for THA is addressed to an increasingly younger age, this type of patient having the risk of multiple revisions throughout life. The need for the survival of the prosthetic implant for as long as possible has led to changes in surgical technique and multiple biomechanical studies, as well as the discovery and development of new biomaterials and implants ,20.In 1987, Donaruma et al.  defined The first data on degenerative changes of the hip appeared in archaeological and paleontological research ,23,24. IThe first arthroplasty that replaced the articular surface was performed by Pierre Delbet in 1919 ,24, usinThe father of modern hip arthroplasty was Sir John Charnley, who introduced the concept of low friction arthroplasty—metal on polyethylene (MoP) . The conDifferent authors have started using different combinations of materials for both cemented and non-cemented components: Peter Ring used an uncemented prosthesis with a metal-on-metal friction couple (MoM) , and theHip arthroplasties vary in terms of component design and biomaterials used . An impoPolymers are used in hip arthroplasty in the liner, inside the metal acetabular cup. The use of different types of polymers has an impact on the wear, over time, of the mobile implant and subsequently on the stability of the prosthetic implant .Polymethyl methacrylate (PMMA) was introduced by Charnley in the 1960s ,49,50 asPolytetrafluoroethylene (Teflon) (PTFE) is a hydrophobic and thermally stable fluoropolymer of tetrafluoroethylene that has a very high wear coefficient; this was used for the first time by Charnley et al.  as an alUltra-high molecular weight polyethylene (UHMWPE) is an engineering polymer that was launched in THA in the middle of the 1960s as a replacement for the unsuccessful PTFE . It has It is concerning how often THA fails over time because of wear problems that shorten UHMWPE’s longevity, and the release of polyethylene particles may result in peri-implant osteolysis and aseptic loosening. UHMWPE wear is one of the most serious post-surgical concerns and the development of UHMWPE is essential for prolonging survival time after THA ,63,64,65Today, the primary problem of the oxidation of UHMWPE has been significantly decreased by replacing the air with gas or low oxygen conditions during radiation. At the same time, in sterilizing methods, wear is controlled by cross-linking ,61. AlsoHighly cross-linked polyethylene [HXLPE] was developed in the 1990s to decrease the wear of UHMWPE when manufacturers such as Stryker, Zimmer Biomet, Kyocera, DePuy Synthes, and Smith & Nephew placed on the market first generation trade-marks like Crossfire, ArCom XL, Aeonian, Marathon and XLPE, respectively, which were produced by 50–100 kGy radiation and stabilization with remelting or annealing. Later, the HXLPE second generation was produced by using sequential radiation and annealing ,68. It iLater, the combination of cross-linking and heat treatment was proposed, which led to a decrease in free radicals and an increase in resistance to oxidation and wear ,72,73,74It should be mentioned that Devane and colleagues ,79 demonUntil now, the most-used bearing coupling is the cobalt-chromium femoral head that articulates with an HXLPE liner, since it shows extended durability and reduced wear rates with good safety in various longitudinal inspections ,81.Vitamin E-blended UHMWPE or HXLPE arose from the need to decrease the production of free radicals. Vitamin E is a biocompatible antioxidant, with multiple beneficial roles , that protects the polymer from oxidative degradation ,83,84. APolyether-ether-ketone [PEEK] is a biocompatible polymer that promises a much lower release of wear particles when used as a bearing surface ,91 but wPoly 2-methacryloyloxyethyl phosphorylcholine [PMPC] is formed by grafting poly (2-methacryloyloxyethyl phosphorylcholine) (MPC) onto an HXLPE using photoinduced polymerization . The artPolycarbonate-urethane [PCU] is a hydrophilic implant with an elasticity close to that of human cartilage. The advantages are as follows: biostability, high resistance to hydrolysis, oxidation, and calcification, absent biodegradation, low wear rate, and high corrosion resistance ,54,94.Metals are used in THA both for the fixed components  as well as for the mobile components . It should be mentioned that MoM THA is no longer utilized ,46,95, bStainless steel is a carbon-based iron alloy that contains Cr, Ni, Mo, Mn and C . It is aCobalt chromium molybdenum alloys (CoCrMo) are composed of 60–70% Co, 25–30% Cr, and 5–7% Mo  and are Titanium alloys (Ti-6Al-4 V) are used especially in femoral stems and acetabular cups due to their biocompatibility and mechanical properties . Their dZirconium alloy (Zr-2.5Nb) is a new alloy used in the production of the prosthetic head. Oxidized zirconium implants with lower wear can improve the longevity of total hip implants ,100. OxiIn order to decrease the release of metal ions during the friction of the joint surfaces, different metal alloy surface coatings were tested. All these covers, no matter if they are Titanium nitride (TiN) , SiliconCeramic materials were introduced in THA approximately 50 years ago  with theAlumina is a ceramic with high biocompatibility. The commercial product is Biolox, with a high elastic modulus (400 GPa) overpassing that of the cortical bone (300 GPa); also, it has low deformation values . The advZirconia has the same advantages as alumina but with good resistance to breaking ,134. Zirconia-toughened alumina (ZTA) is a combination of two materials: Zirconium is incorporated into the aluminium matrix to increase hardness . This prOxidized zirconium head-on crosslinked polyethylene is a modern bearing coupling but more studies are needed due to in vivo lower wear parameters .Sapphire is a mineral that contains 99.99% aluminium oxide and traces of chromium, titanium, iron, vanadium, and magnesium . A few sSilicon nitride, silicon carbide and diamond-like carbon as non-oxide ceramics are considered to be the new generation of materials used in hip prosthetics, particularly in the manufacture of acetabular cups, due to their excellent biocompatibility, osteointegration, and tribological and mechanical properties, but all three materials need more study. However, silicon nitride is the nearest to commercialization, through businesses such as Amedica Corp. and SyntX Technologies .The use of bearing surfaces in total hip arthroplasty for young and active patients remains controversial. Despite the popularity of polyethylene among surgeons due to its ease of use, the risk of wear and aseptic loosening has led to increased interest in researching the best bearing surfaces. As an alternative to conventional metal-on-polyethylene (MoP), metal-on-metal (MoM), ceramic-on-high cross-linked polyethylene (CoHXLPE), or ceramic-on-ceramic (CoC) have become possibilities when choosing the most suitable ported surfaces .MoP is the most-used bearing couple combination in hip arthroplasty, developed by Sir John Charnley . In thisMultiple studies have shown a decrease in the release of polyethylene particles in the cases of XLPE and HXLPE compared to the case of UHMWPE  Figure A,B. KuzyVitamin E-supplemented cross-linked polyethylene (VE-HXLPE) has been implemented recently in total hip arthroplasty due to its improved tribological properties by the decrease of liners oxidation ,141. ® analysis software. At 5-year follow-up, wear rates of non-vitamin E-supplemented liners and vitamin-E supplemented liners were comparable  is a new metal alloy that is transformed to ceramic using a complex process; it is considered an alternative bearing surface and is used for femoral heads in total hip arthroplasty E. RecentThe metal–metal couple (MoM) used as metal heads in metal inserts focused the interest of research groups and orthopaedic surgeons. Literature data report lower osteolysis and wear rates due to the decreased diameter of particles and lower values of friction . In 2006However, a few research groups highlighted significant concerns regarding biocompatibility. Adverse reactions to the metal particles released by wear processes were noted due to the destruction of the periprosthetic soft tissues by lymphocytes ; these lCeramic manufacturing has significantly improved in the last 20 years, while the introduction of cross-linked polyethylene was associated with significantly better biomechanical and clinical results. The introduction of aluminium femoral heads reduced rates of linear and volumetric wear in vivo. Kusaba  studied In vivo studies that have evaluated the wear of ceramic on polyethylene fall into two broad groups—those that evaluate only the ceramic–polyethylene couple and those that compare with other biomaterial couples. Urban  conducteStudies comparing ceramic-polyethylene versus metal-polyethylene coupling results have produced mixed results. Two larger studies ,171 highCeramic-ceramic has lower wear rates when compared to ceramic-polyethylene. However, medium-term studies using alumina-type ceramics with cross-linked polyethylene reported similar osteolysis or patient satisfaction at 5 years .The ceramic-ceramic tribological couple (ceramic head in a ceramic acetabular liner) combines the properties of a high scratch resistance material with very low friction coefficients, thus reducing the risk of wear, osteolysis, and loosening C,F. HernAlthough the release of wear particles is the smallest of all tribological couples, the ceramic-ceramic couple also has some disadvantages and risks: squeaking and ceramic fracture. Hernigou et al.  continueIf squeaking does not have a major functional impact on the survival of the implant over time, the fracture of the head or the ceramic liner is a major complication that requires prosthetic revision. Among the causes of ceramic fracture are the imperfections of the ceramic material, the malpositioning of the insert in the metal cup and of the cup in the acetabulum . With thMalpositioning of the ceramic insert causes difficult intraoperative reduction and excessive wear with risk of fracture of the ceramic insert without trauma . The verThe fracture of the ceramic implant must be recognized and operated on early due to the significant metallosis occurring at the contact between the metal neck and the acetabular metalback .In brief, the success of THA depends on the orthopaedic surgeon, who not only performs the operation but also chooses the best substitute so that the patient can function properly longer without it being rejected. The choosing process can be affected by the patient’s age, health condition, weight, how the materials behave, and how active the patient is after surgery. As a result, for THA to be successful, the biomaterial employed must be biomechanically compatible and have a modulus comparable to the bone, ranging from 4 to 30 GPa . ConsequTotal hip arthroplasty, although very successful, is not without possible complications. Survival over time depends on factors related to the patient and the surgeon’s experience and surgical technique, but not least on the quality and combination of biomaterials used. The characteristics of the different bearing surfaces and the controversial studies in the literature make it difficult to choose the best implant. The CoC bearing surface shows the least wear, but at a high cost, with the risk of fracture and squeaking. CoP has a higher wear rate than CoC; however, it is cheaper but more expensive when compared to MoP. MoP has the lowest price but the highest wear rate, higher than that of MoM. MoM has a high cost, and the risk of pseudotumors and high levels of metal ions in serum and urine means it is no longer recommended.There is no such thing as a perfect implant, but there is an ideal implant for each patient. Implant-to-patient matching and implant selection is a difficult task that should consider multiple factors like bone quality and general health status. A good initial choice of implant will decide its survival rate and, consequently, the patient’s satisfaction, and will minimize both social and economic costs generated by the subsequent revision of the total hip prosthesis.The development of new biomaterials combining the use of new nanoparticles with antimicrobial activity to reduce the risk of infection, among other improvements, will increase the success of these complex surgical interventions and the long-term survival of the implant.


Its best characterized role lies in mineral ion homeostasis via regulation of parathyroid hormone (PTH) secretion and calcium reabsorption in the kidneys . In addirtension . This murtension . The 6 rIamartino and Brandi have reviewed several studies on the role of the CaSR in inducing and modulating pro-inflammatory stimuli in various organs and disease settings, namely, in immune cells, immune check-points, in the nervous system, specifically in the context of Alzheimer’s disease, in the respiratory, cardiovascular, and digestive systems, in adipose tissue, the kidneys, in the context of viral infection, etc. They also examined the possibility of treating such afflictions with negative allosteric CaSR modulators, calcilytics. Fittingly, Werner and Wagner have contributed an insightful review emphasizing CaSR-related effects on monocytes in rheumatoid arthritis. The authors propose that in this disease setting, calciprotein particles are formed due to a combination of increased local calcium concentrations and elevated fetuin-A levels. Together with increased extracellular Ca2+ levels and elevated levels of pro-inflammatory cytokines, these particles could lead to a “vicious cycle of inflammation and bone destruction” and targeting this vicious circle may provide a new therapeutic avenue against this disease. In an original research article, Gushchina et al. have shown that activation of the CaSR induces the PGE2 pathway in in vitro and in vivo models of colitis. Interestingly, the observed induction of PGE2 pathway-specific genes was different between the in vitro and in vivo settings. On the basis of this and previous results, the authors suggested that calcilytics may constitute a novel way of treating inflammatory bowel disease.The role of the CaSR in inflammatory processes is currently of particular interest, as demonstrated by three of the articles in this Research Topic dealing with this subject. Centeno et al., described the role of extracellular phosphate and intracellular phosphorylation in inhibiting and modulating CaSR activity. They illustrate how extracellular phosphate modulates PTH secretion via CaSR inhibition. The authors lead through this topic via an explanation of the structure of the CaSR and its binding sites for various ligands and ions, and progress via a detailed account of what is known on the complex interaction of CaSR and extracellular phosphate as well as intracellular CaSR phosphorylation and CaSR activity. Intracellular phosphorylation of the CaSR is also a key feature of yet another non-calciotropic role of the CaSR, namely, that of a temperature sensor. In a pivotal study, Brennan et al. demonstrated that the C-terminal domain of the CaSR mediates its temperature-sensing capabilities. Changes in temperature directly influence CaSR induced intracellular Ca2+ oscillation frequency. The anterior preoptic nucleus, a key temperature sensing organ, expresses the CaSR. This organ has been linked to a genetic disorder of thermoregulation in patients with autosomal dominant hypocalcemia with hypercalciuria (ADH) type 1, a disease caused by activating mutations in the CaSR gene. As calcilytics are already being tested for the treatment of ADH, they might also prove beneficial in managing infantile febrile convulsions seen in some ADH children.The other three articles of this Research Topic deal with specific features and action modes of the CaSR that highlight the versatility of this protein: in an elegant minireview, Lindner et al., investigated in a research article the CaSR-independent role of the positive allosteric CaSR modulator cinacalcet on voltage-gated sodium channels in neocortical neurons via a yet unknown GPCR other than the CaSR. Using electrophysiological approaches, the authors demonstrated that cinacalcet inhibits these channels and thus neuronal action potentials, especially when the channels are in their fast-inactivated state. The authors conclude that cinacalcet could serve as a template molecule for the development of a new class of sodium channel inhibitors. At the same time, due to its action on neuronal activity, cinacalcet may interact with brain function in patients treated with this drug.Finally, To conclude, the up-to-date and state-of the-art understanding of CaSR pathophysiology presented in this Research Topic would be expected to lead to the identification of novel therapeutic strategies for treating a variety of conditions, including inflammatory diseases and thermoregulation.


Given the importance of this, we have launched this Research Topic named “Food, Nutrition and Microecological Health.” The topic is aimed at addressing the effects of specific food intake and specific food-derived compounds on microbiota alterations in human body, and their potential role in optimizing human health status, preventing and improving non-communicable diseases such as cardiac-cerebral vascular malfunctions, immunosuppression, hyperlipidemia, and hyperglycemia, hopefully to present some examples of “food dependent healthy microecological system.”Food nutrition and microecological status play important roles in maintaining physical and psychological health throughout the entire human life. Daily food intake provides us with nutrients, which are processed in the digestive tract and absorbed by intestinal epithelial cells (IECs). Some of the nutrients and the corresponding metabolites interact with the gut microbiota, a key factor for the homeostasis of gastrointestinal microenvironment, and are assimilated by the human body for the energy to run cellular processes and for the building blocks of proteins, lipids, nucleic acids, and carbohydrates. Therefore, understanding bioactive components from food and their influence on microecological health Frontiers in Nutrition, including 24 research articles and two comprehensive reviews. All the reported scientific discoveries addressed the gist of the topic from multiple aspects, ranging from bioactive natural products to toxic chemicals, with the purpose to elucidate the mechanisms of the network where food, nutrition, and microecological health are intensively interlacing. These contributions have provided new evidence on food-related changes in microbiota and the ensuing malfunctions and diseases, which will further promote the scope of precision nutrition and related studies. Here, we selected several papers with outstanding scientific discoveries, in hope of sharing the viewpoints with vast audience from the perspective of microecological health.After 8 months' call for contributions, 26 papers of pertinence to the topic were accepted as publications on Ding et al. that dietary NTs are able to slow down the senescence progress of SAMP8 mouse by promoting the constitution of gut microbiota. They added NTs to the basal diet of mice, and analyzed the intestinal microbiome and metabolites after 10 months when aging was observed. The findings showed that the supplementation of NTs enhanced the diversity of gut microbiota, while inhibited the bad bacteria  and increased the good  ones. As a result, the risk of intestinal microbiota dysbiosis that usually happens to senescent mice was reduced by the intervention of dietary supplementation. Further metabonomics studies revealed that the metabolism processes of histidine, vitamin B6, and linoleic acid were involved in the NT-mediated microecological improvement. Those biological events were closely related to the vitality of Lactobacillus casei, a well-characterized probiotic, and its antagonism against intestinal pathogens. Finally, they concluded that NTs is an overlooked prebiotic, which is able to regulate the imbalance of gut microbiota caused by aging.Nucleotides (NTs), the building blocks constituting DNA and RNA that account for more than 30% dry weight of human cells, are once considered as the conditional nutrients specially for infants, elderly, and patients in recovery. However, a new discovery has been made by Wallingford et al. discussed the effects of oligosaccharides on healthy infants born in the USA and Honduras. The project was conducted jointly by researchers from Denmark and the US, who added the 2-fucosyllactose (2′ FL), a type of oligosaccharides rich in breast milk, to the infant formula to check if there was any changes in the intestinal microbiome of the infants. They found that, although the addition of 2′ FL failed to promote the growth of the infants, no adversary effects were observed on the formula-fed infants supplemented with level physiologic of 2′ FL. The oligosaccharides mediated modest changes in gut microbiome of the formula-fed infants, toward the direction of the infants fed with breast milk. Bifidobacterium, which has genes that allow intracellular metabolism of 2′ FL, was selectively enriched with the addition of 2′ FL, supporting the prebiotic property of 2′FL when used as a supplementation in infant formula. This study elucidated the nutritional functions of 2′ FL in infants lacking of breastfeeding, shedding the light on the importance of exogenous and endogenous provision of oligosaccharides that could be used as prebiotics.A clinical study led by Yu et al. including researchers coming from several institutions across China dissected the low-carbohydrate diet-induced weight loss from the perspective of microecological nutrition. They applied 16S rRNA and ITS rRNA sequencing techniques to analyze the changes of gut bacteria and fungi of overweight and obese adults before and after being subjected to the low-carbohydrate dietary intervention . More than 90% of the participants achieved weight loss of at least 5% over the course of the diet. The diversity of gut bacteria and fungi increased after a weight loss of 5% and kept stable thereafter, featured by depletion of Lachnoclostridium and Ruminococcus from Firmicutes phylum and increasing of Parabacteroides and Bacteroides from Bacteroidetes phylum. The inter-kingdom analysis found an intensive covariation between gut fungi and bacteria, more than half of them associated with weight loss. The study discovered the links between fungi and bacteria in the diet-caused weight loss, confirming the fact that gut microbiota is a key player in the development of dietary-related metabolic disorders such as obesity.Another clinical study by Schisandra chinensis, a berry fruit native to far east region including the territories of China, Japan, Korea, and Russia, has long been used as tea or prescription of decoctions in traditional Chinese medicine. In alcohol-caused liver diseases featuring with liver steatosis and fibrosis, alcoholic hepatitis (AH) is of high incidence and accounts for more than 50% of short-term mortality. Xiang et al. characterized the components of Schisandra chinensis extract (SCE) using UHPLC-QE-MS, and assayed their hepatoprotective effects on AH mice. They found that SCE significantly ameliorated inflammation and oxidative stress of AH mice, along with fortifying the intestinal barrier function by improving gut microbiota and the corresponding metabolites. Specifically, the abundance of Lactobacillus plantarum and Bifidobacterium breve, serving as the producers of short-chain fatty acids (SCFAs) were increased by the administrations of SCE both in vitro and in vivo. Meanwhile, Escherichia-Shigella, which was markedly enriched in AH mice, was inhibited by SCE, partially contributing to the mitigation of hepatic inflammation, lipid accumulation, and intestinal dysfunction. This study suggested that S. chinensis might be an effective dietary supplement for prevention and treatment of alcohol-caused liver diseases. Another investigation on the alcohol-related liver disease by Zhang et al. was also selected under the current topic in terms of microecological health. They found that folic acid (FA), also known as vitamin B9, is able to mitigate alcohol-induced liver injury via gut-liver axis. FA accelerated lipid deposition, and inhibited alcohol-caused inflammation as evidenced by the decreased the levels of LPS (Lipopolysaccharide), ALT (Alanine aminotransferase), AST (Aspartate transaminase), and TG (Triacylglycerol) in the serum of mice. Besides, Verrucomicrobia, Lachnospiraceae_NK4A136_group, and Akkermansia, which significantly decreased in the mice exposed to the alcohol consumption, were increased when FA was applied. Further correlation analysis showed that the levels of the inflammation-inducing cytokines in liver were highly related to the alteration of gut bacteria that were responsive to the FA supplementation. Bacteroidota, Firmicutes, and unclassified_Lachnospiraceae mainly accounted for the FA-mediated liver restoration, suggesting the pivotal role of gut-liver axis in the progress of alcohol-induced liver damage.Lu et al., who contributed a paper titled “The antidepressant effect of deoiled sunflower seeds on chronic unpredictable mild stress in mice through regulation of microbiota-gut-brain axis”. In their study, the deoiled sunflower seeds (DSFS) which are rich in tryptophan, a precursor of serotonin with antidepressant potential, were used as the supplementation to the chow diet of the mice. The results showed that the elevated plasma corticosterone and the reduced hippocampal serotonin, two indexes for the depression-related symptoms, were recovered by the DSFS diet. Besides, DSFS significantly elevated the abundance of the bacteria that were inversely associated with depressive behaviors. Some of them, such as R. flavefaciens, C. scindens, and O. massiiensis were positively related to the production of indoleacetaldehyde, contributing to the delayed consumption of L-tryptophan in the microenvironment of gut. The other work discussing the gut-brain axis in this topic was contributed by Huang et al. from China. They found that P. histicola, an emerging probiotic by recent studies, was able to ameliorate the depression state of the ovariectomized mice by improving the structure of intestinal microbiota. P. histicola significantly increased the abundance of gut microbiota, especially Lactobacillus and Akkermansia. Meanwhile, the cohoused mice were observed with better emotional state and neutral structure compared with the ovariectomized mice, suggesting the estrogen deficiency-induced depression was related to gut-brain axis. Further in-depth investigations showed that P. histicola helped repair intestinal leakage and promoted the expression of neurotrophic factors (BDNF and Ki-67) for hippocampal neurogenesis. The two studies have provided new insights of using nutrients or probiotics to relieve psychiatric disorders without resorting to the chemotherapies that are often accompanied by unpredictable side effects.Apart from gut-liver axis, gut-brain axis is also an emerging hotspot for researchers dealing with micronutrition and psychological health. Two papers that fall into this category were enrolled by the current topic. One of them is coming from Tu et al. from the US investigated whether a black raspberry (BRB)-rich diet could ameliorate the inflammatory bowel disease in mice. Using a mouse model of DSS-induced intestinal inflammation, they found that the intervention of BRB was able to delay and even reverse the inflammation progression in the small intestine. The anti-inflammatory effects were closely related to the modulation of the gut microbiota, especially to those bacteria that could produce AHR ligands in response to the BRB dietary intervention. This study demonstrated again that nutrients from natural products have great potentials to relieve inflammations by restoring the imbalanced gut microecology. Apart from the study on inflammatory bowel disease, two independent research groups both discussed the protective effects of food ingredients on renal damage. Wang et al. found that Oat β glucan, one of the major bioactive substances from oat, was able to modulate the composition of intestinal flora by regulating several metabolism processes, in turn alleviate the inflammatory response, and finally contribute to the postponed progression of nephropathy caused by diabetes. Zhu et al. from Fudan University of China used α-ketoacid as a supplement to low protein diet to assay the effects on the nephrectomized mice. The results showed that the low protein supplemented with α-ketoacid diet (LKD) could delay the adverse effects caused by the renal failure. The mice fed with LKD were observed with increased α-diversity and decreased F/B ratio of gut microbiota compared with that of mice in the control group. Further multi-omics analysis revealed that specific metabolites involving in multiple biosyntheses  were associated with the amelioration effects of LKD on renal damage, which could be ascribed to the regulation of affecting the gut microbiome and fecal metabolic profiles. Results from the three studies put forward a notion of using food-derived interventions to exert prophylactic and therapeutic effects on chronic diseases via affecting intestinal flora and gut homeostasis.Li et al. found that, the addition of GFB in daily diet contributes to the restorations of gut microbiota and colonic barrier integrity of mice subjected to antibiotic perturbation. The mice were exposed to certain amount of ciprofloxacin and metronidazole once a day for 2 weeks, followed by GBF intervention for another 2 weeks. Compared with the natural recovery, GBF decreased the antibiotic-induced gut permeability by increasing the secretion of mucin, and promoted the growth of Bacteroidales S24-7, Lachnospiraceae, Bacteroidaceae, and Porphyromonadaceae that have beneficial effects on gastrointestinal homeostasis. The current study demonstrated that GBF could be used to alleviate the negative effects of antibiotics on gut microenvironment, paving the way of using GBF as a functional food ingredient to shield the gut microbiota and the intestinal barrier from being perturbed by antibiotics. Cui et al. from China contributed a paper investigating the effects of whole-grain diet (WGD) on gut microbiota of elderly individuals. Although they did not observe any changes in the α-diversity of the gut microbiota, WGD affected the abundance of Verrucomicrobia and Firmicutes. The influence of WGD varied significantly in terms of weight and gender, yet the decreased Firmicutes/Bacteroidetes ratio, which is conducive to the homeostasis of the gut microbiota, was observed. Hence, they concluded that WG could improve the microbial composition and promote the growth of beneficial microbes, which may be beneficial to the elderly individuals.Green banana flour (GBF) is a powder made of unripe bananas that are peeled, chopped, dried, and then ground. GBF has been used as a cheaper alternative to wheat flour in Africa, Jamaica, and some countries in South America. Recent studies show that GBF can be used as a gluten-free replacement for wheat flour, as well as a source of resistant starch, which has been promoted as a prebiotic to exert beneficial effects on gut microbiota. In summary, the studies above-mentioned provided enormous amount of emerging findings on the cross-talk between food components and gut microbe, contributing to beneficial effects on human health and guidelines and further research perspective in terms of precise nutrition. Granted, bad effects from both plant- and animal-derived food should also be discussed and investigated by taking microecological nutrition into consideration. The total 26 papers are certainly not able to cover all the aspects of the current topic. More and more good works with robustness and novelty are expected from researchers worldwide, some of which might be designed and conducted in the following angles:a. Interactions between specific diet and gut microbiota and the corresponding effects on cardiac-cerebral vascular health, immune activation, arthrosis, hyperlipidemia, hyperglycemia, and hypertension.b. Bioactive food compounds and their derivatives over the course of digestion, and their functions on gut microbiota and related metabolic processes.c. Regional speciality food, the particular functional compounds inside and the interplays with gut microbiota.d. Bioactive substances in food delivery systems, targeting specific intestinal bacteria and the in-depth molecular mechanism.XY: organizing, writing, and editing. XL, GT, and HL: writing and revising. All authors contributed to the article and approved the submitted version.