The output feedback controller is designed for a class of stochastic nonlinear systems that satisfy uncertain function growth conditions for the first time. The multivariate function growth condition has greatly relaxed the restrictions on the drift and diffusion terms in the original stochastic nonlinear system. Here, we cleverly handle the problem of uncertain functions in the scaling process through the function maxima theory so that the Ito differential system can achieve output stabilization through Lyapunov function design and the solution of (...) stochastic nonlinear system objects satisfies the existence of uniqueness, ensuring that the system is globally asymptotically stable in the sense of probability. Furthermore, it is concluded that the system is inversely optimally stable in the sense of probability. Finally, we apply the theoretical results to the practical subsea intelligent electroexecution robot control system and obtain good results. (shrink)

The adaptive object model method is an effective way to develop dynamic and configurable adaptive software. It has the characteristics of metamodel, description drive, and runtime reflection. First, the core idea of the adaptive object model is explained; then, the five modes of establishing the metamodel in the adaptive object model architecture, the model engine, and supporting tools are analyzed; and the basketball tracking algorithm of the adaptive object model is discussed. Secondly, a two-dimensional joint information strategy is proposed to (...) improve the tracking effect. When the basketball is in a very complex environment, there will always be some color information in the background that is the same as the target, which affects the effect of basketball tracking. Therefore, this paper proposes a Camshift tracking method based on the significance of histograms, through real time. The basketball movement is compared with the background histogram to continuously adjust the basketball movement tracking model. These two methods can better establish the tracking model of the basketball adaptive object, reduce the interference of background information, and achieve the effect of stable tracking of the target. The simulation experiment results show that the method proposed in this paper can effectively improve the accuracy of the basketball goal model and achieve stable tracking of the goal. (shrink)

Learning a deep structure representation for complex information networks is a vital research area, and assessing the quality of stereoscopic images or videos is challenging due to complex 3D quality factors. In this paper, we explore how to extract effective features to enhance the prediction accuracy of perceptual quality assessment. Inspired by the structure representation of the human visual system and the machine learning technique, we propose a no-reference quality assessment scheme for stereoscopic images. More specifically, the statistical features of (...) the gradient magnitude and Laplacian of Gaussian responses are extracted to form binocular quality-predictive features. After feature extraction, these features of distorted stereoscopic image and its human perceptual score are used to construct a statistical regression model with the machine learning technique. Experimental results on the benchmark databases show that the proposed model generates image quality prediction well correlated with the human visual perception and delivers highly competitive performance with the typical and representative methods. The proposed scheme can be further applied to the real-world applications on video broadcasting and 3D multimedia industry. (shrink)

In the present study, we tested the effectiveness of color coding on the programming learning of students who were learning from video lectures. Effectiveness was measured using multimodal physiological measures, combining eye tracking and electroencephalography. Using a between-subjects design, 42 university students were randomly assigned to two video lecture conditions. The participants’ eye tracking and EEG signals were recorded while watching the assigned video, and their learning performance was subsequently assessed. The results showed that the color-coded design was more beneficial (...) than the grayscale design, as indicated by smaller pupil diameter, shorter fixation duration, higher EEG theta and alpha band power, lower EEG cognitive load, and better learning performance. The present findings have practical implications for designing slide-based programming learning video lectures; slides should highlight the format of the program code using color coding. (shrink)

This research topic (RT) focused on the impact of fitness on cognitive function and development in adolescents and elderly adults from the standpoint of lifespan neuroscience. Adolescent brain development is characterized by multimodal integration of brain anatomical features and function, according to accumulating evidence. The elderly, on the other hand, suffer from age-related cognitive deterioration. Fitness may be a major factor influencing brain growth and cognitive performance throughout these two critical times for neurological development. It is a multidimensional notion that (...) includes cardiovascular fitness, muscular strength and endurance, flexibility, and body composition, as well as motor fitness (balance, agility, speed, power, and coordination). Adolescents and older people may be responsive to intervention trials aimed at improving fitness levels, such as outdoor activities, cardiovascular exercise, and mind-body practice since brain network integration and neural efficiency are rapidly altered during this period. This RT investigates how fitness influences structural and functional brain development, particularly cognitive functions, and emotional health in adolescents and elderly people, as well as training strategies that may assist cognitive progress throughout this time. It includes a clinical trial (1) and original research papers (4) on the influence of fitness on cognitive function and development in adolescents and elderly adults from a lifespan neu... (shrink)

This paper proposes a new robotic fish which avoids the complex mechanical structure and reduces the model complexity comparing to the existing bioinspired robotic fish, giving rise to a semibiomimetic robotic fish. The generalized Lagrange equation is adopted to establish the dynamic model of the robotic fish. The controllability of the system is analyzed, upon which a trajectory tracking control algorithm is designed by using the feedback linearization technique. The simulation results show that the dynamic model adopted in this paper (...) can achieve better control performance. (shrink)

The rapid acceleration of societal change has subjected contemporary individuals to prolonged periods of diverse pressures, leading to substantial psychological strain, resulting in anxiety, depression, and compromised mental well-being. Within this context, the home has evolved into a vital refuge for modern individuals, offering both physical and psychological respite. Through experimental intervention, this study examines two distinct residential groups: those adhering to traditional housing and those residing in characteristic folk houses, specifically Gannan Hakka architecture. Analysing the psychological state of contemporary (...) individuals and integrating Gannan Hakka architectural elements into folk house design through a psychologically informed approach, this research aims to enhance residents’ aesthetic experiences and alleviate psychological distress. The study involved 120 volunteers with varying psychological stress levels, categorised into characteristic and traditional folk house groups. Psychological assessments evaluated stress, self-efficacy, and quality of life. Findings reveal significantly improved psychological well-being, self-efficacy, and quality of life among the characteristic residential group, affirming the benefits of Gannan Hakka architecture integration. This research underscores the importance of addressing modern individuals’ environmental needs and proposes the integration of Gannan Hakka cultural elements into residential design to enhance well-being. Contribution: This study demonstrates the application of Hakka culture in contemporary housing profoundly influences residents’ lives, enabling both relaxation and a deeper cultural connection. This integration facilitates a comprehensive understanding of Hakka culture, promoting its preservation. Notably recognised for hospitality and diligence, Hakka culture enhances individuals’ appreciation of tradition, fostering physical and mental rejuvenation. These findings offer valuable insights for practical theology scholars and practitioners exploring the impact of religious aspects on modern residential design from a psychological perspective. (shrink)

Using core self-evaluation theory, the current study assesses the effect of internal work locus of control and bricolage on social entrepreneurship orientation. We adopted the cross-sectional survey design using a sampling frame to engage 400 top executives of social enterprises in mainland China. Three hundred and seventy-two of the executives replied, presenting a response rate of 93%. Results of structural equation modeling analysis show significant positive relationships between internal work locus of control, bricolage, and social entrepreneurship orientation. The positive mediating (...) effect of bricolage on the relationship between internal work locus of control and social entrepreneurship orientation was also found to be true. Consequently, to foster social entrepreneurship orientation, top executives of social enterprises need to gather available resources for bricolage tasks. These findings contribute new knowledge to how internal work locus of control affects social entrepreneurship orientation through the bricolage activity of Chinese social enterprises. Through core self-evaluation theory, we demonstrate the effect of internal work locus of control as a preceding factor in the relationship between bricolage and social entrepreneurship orientation. (shrink)

Consumers play an important role as one of the main actors in food safety social co-governance. To create a pattern of food safety social co-governance, the active and effective participation of consumers is critical. To encourage consumers to participate in food safety social co-governance voluntarily and positively, we attempted to develop and preliminarily validate a multidimensional questionnaire on consumer psychological capital that could be used to measure the degree of consumer participation in food safety social co-governance. The aim of the (...) initial sample and test sample 2 was to investigate the factor structure of a preliminary measure of consumer psychological capital. A 4-factor model with 23 items explained 61.05% of the total variance in item scores. The aim of test sample 3 was to measure the retest reliability. Test sample 4 was randomly allocated to the modeling sample and validation sample to verify questionnaire reliability and validity. Convergent validity, discriminant validity, and the internal inconsistency coefficients of the questionnaire were assessed in the modeling sample. While processing CFA, we deleted 9 items with small standardized factor loadings. The remaining 14 items in the final revised 4-factor model included self-efficacy, resilience, hope, and optimism. The fit indices of the revised four-factor model and second-order factor model in the modeling sample revealed an acceptable model fit. The convergent validity and discriminant validity of the revised model were good and acceptable, respectively. A cross-validation procedure confirmed the appropriateness of the revised four-factor model and second-order factor model in the validation sample. The cross-validation results confirmed that the fit indices of the revised four-factor model fitted the data well and the second-order factor model in the validation sample reached acceptable values. We concluded that the questionnaire developed in this study had good reliability and stable and acceptable construct validity. It could provide a theoretical basis for measuring psychological capital in food safety co-governance. (shrink)

Interpersonal responsibility is an indigenous Chinese personality construct, which is regarded to have positive social functions. Two studies were designed to explore the relationship among interpersonal responsibility, proposal allocation ratio, and responders’ hostile decisions in an ultimatum game. Study 1 was a scenario study using a hypothetical ultimatum game with a valid sample of 551 high school students. Study 2 was an experimental study which recruited 54 undergraduate students to play the incentivized ultimatum game online. The results of the two (...) studies showed a significantly negative correlation between interpersonal responsibility and responders’ rejection responses only when the proposal allocation ratio was 3:7. In addition, in study 2, interpersonal responsibility had negative effects on responders’ rejection responses under the offer of 3:7, even after controlling for the Big Five personality traits. Taken together, proposal allocation ratio might moderate the effects of interpersonal responsibility on hostile decision-making in the ultimatum game. The social function of interpersonal responsibility might be beyond the Big Five. Keywords: interpersonal responsibility, proposal allocation ratio, hostile decision-making, moderator, ultimatum game, Big Five personality. (shrink)

Conflicts in land exploration are incisive social problems which have been the subject in many studies. Risk assessment of land conflicts is effective to resolve such problems. Specifically, fuzzy mathematics and the analytic hierarchy process were combined together to evaluate risk in land conflicts in our work, which is proved useful to solve uncertainty and imprecision problems. Based on the analysis of the principles for the risk assessment of a land conflicts index system, a set of risk assessment indexes using (...) the fuzzy analytic hierarchy process was presented. The results show that the overall risk is at medium level, and the risk of the feasibility index and controllability index need to be paid more attention to. The contribution of this article is reflected in two aspects: the application of FAHP in risk assessments of land conflicts is effective and valid; it is helpful for governments to establish a stricter management system of work safety for conflicts in land exploration based on the risk assessment results. (shrink)

Linear regression and its variants have been widely used for classification problems. However, they usually predefine a strict binary label matrix which has no freedom to fit the samples. In addition, they cannot deal with complex real-world applications such as the case of face recognition where samples may not be linearly separable owing to varying poses, expressions, and illumination conditions. Therefore, in this paper, we propose the kernel negative ε dragging linear regression method for robust classification on noised and nonlinear (...) data. First, a technique called negative ε dragging is introduced for relaxing class labels and is integrated into the LR model for classification to properly treat the class margin of conventional linear regressions for obtaining robust result. Then, the data is implicitly mapped into a high dimensional kernel space by using the nonlinear mapping determined by a kernel function to make the data more linearly separable. Finally, our obtained KNDLR method is able to partially alleviate the problem of overfitting and can perform classification well for noised and deformable data. Experimental results show that the KNDLR classification algorithm obtains greater generalization performance and leads to better robust classification decision. (shrink)

An integrated hog futures price forecasting model based on whale optimization algorithm, LightGBM, and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise is proposed to overcome the limitations of a single machine learning model with low prediction accuracy and insufficient model stability. The simulation process begins with a grey correlation analysis of the hog futures price index system in order to identify influencing factors; after that, the WOA-LightGBM model is developed, and the WOA algorithm is used to optimize the LightGBM (...) model parameters; and, finally, the residual sequence is decomposed and corrected by using the CEEMDAN method to build a combined WOA-LightGBM-CEEMDAN model. Furthermore, it is used for comparison experiments to check the validity of the model by using data from CSI 300 stock index futures. Based on all experimental results, the proposed combined model shows the highest prediction accuracy, surpassing the comparative model. The model proposed in this study is accurate enough to meet the forecasting accuracy requirements and provides an effective method for forecasting future prices. (shrink)

Autophagy promotes both health and disease, depending on tissue types and genetic contexts, yet the regulatory mechanism remain incompletely understood. Our recent publication has uncovered a coherent FOXO‐SNAI feed‐forward loop in autophagy, which is evolutionarily conserved from Drosophila to human. In addition, it's revealed that DNA binding plays a critical role in intracellular localization of nucleocytoplasmic shuttling proteins. Based on these findings, herein we further integrate mechanistic insights of FOXO‐SNAI regulatory interplay in autophagy and unravel the potential link of FOXO‐induced (...) autophagy with SNAI in diseases. Besides, the generality of DNA‐retention mechanism on transcription factor nuclear localization is illustrated with wide‐ranging discussion, and more functions potentially regulated by FOXO‐SNAI feedforward loop are provided. Elucidation of these unsolved paradigms will expand the understanding of FOXO‐SNAI interplay and facilitate the development of new therapeutics targeting FOXO‐SNAI axis in diseases. (shrink)

IntroductionTranscranial direct current stimulation is a noninvasive brain stimulation technique that applied to modulate brain activity and enhance motor recovery. However, the neurobiological substrates underlying the effects of tDCS on brain function remain poorly understood. This study aimed to investigate the central mechanisms of tDCS on improving the athletic performance of male rowing athletes.MethodsTwelve right-handed male professional rowing athletes received tDCS over the left primary motor cortex while undergoing regular training. The resting-state functional magnetic resonance imaging data were acquired before (...) and after tDCS. Measures of amplitude of low-frequency fluctuation and regional homogeneity were calculated and compared between baseline and follow-up, as well as topological measures including global and local efficiency of functional brain networks constructed by graph theoretical analysis.ResultsMale rowing athletes showed increased isokinetic muscle strength of the left knee and left shoulder after tDCS. Increased ALFF values were found in the right precentral gyrus of male rowing athletes after tDCS when compared with those before tDCS. In addition, male rowing athletes showed increased ReHo values in the left paracentral lobule following tDCS. Moreover, increased nodal global efficiency was identified in the left inferior frontal gyrus of male rowing athletes after tDCS.ConclusionThe findings suggested that simultaneous tDCS-induced excitation over the primary motor cortex might potentially improve the overall athletic performance in male rowing athletes through the right precentral gyrus and left paracentral lobule, as well as left inferior frontal gyrus. (shrink)

Residual useful lifetime prediction plays a key role of failure prediction and health management in equipment. Aiming at the problems of residual life prediction without comprehensively considering multistage and individual differences in equipment performance degradation at present, we explore a prediction model that can fit the multistage random performance degradation. Degradation modeling is based on the random Wiener process. Moreover, according to the degradation monitoring data of the same batch of equipment, we apply the expectation maximization algorithm to estimate the (...) prior distribution of the model. The real-time remaining life distribution of the equipment is acquired by merging prior information of real-time degradation data and historical degradation monitoring data. The accuracy of the proposed model is demonstrated by analyzing a practical case of metalized film capacitors, and the result shows that a better RUL estimation accuracy can be provided by our model compared with existing models. (shrink)

Prior studies demonstrate the role of resources in shaping a firm’s entrepreneurial orientation from the resource-based view. We expand this line of research by theorising and testing the impact of resource bricolage on entrepreneurial orientation. Based on the data of 295 start-ups, we find that when start-ups face resource constraints, the strategy of resource bricolage has a significant positive effect on entrepreneurial orientation, and the relationship is positively moderated by top management team heterogeneity. Meanwhile, the relationship is negatively moderated by (...) TMT behavioral integration. The results are expected to provide theoretical guidance for start-ups to overcome resource constraints and achieve smooth survival and growth. (shrink)

Recurrent neural network has been widely applied to many sequential tagging tasks such as natural language process and time series analysis, and it has been proved that RNN works well in those areas. In this paper, we propose using RNN with long short-term memory units for server load and performance prediction. Classical methods for performance prediction focus on building relation between performance and time domain, which makes a lot of unrealistic hypotheses. Our model is built based on events, which is (...) the root cause of server performance. We predict the performance of the servers using RNN-LSTM by analyzing the log of servers in data center which contains user’s access sequence. Previous work for workload prediction could not generate detailed simulated workload, which is useful in testing the working condition of servers. Our method provides a new way to reproduce user request sequence to solve this problem by using RNN-LSTM. Experiment result shows that our models get a good performance in generating load and predicting performance on the data set which has been logged in online service. We did experiments with nginx web server and mysql database server, and our methods can been easily applied to other servers in data center. (shrink)

A medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health. Description: The Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data (...) relating to AEs arising subsequent to medical interventions, as well as to support computer-assisted reasoning. OAE has over 3,000 terms with unique identifiers, including terms imported from existing ontologies and more than 1,800 OAE-specific terms. In OAE, the term ‘adverse event’ denotes a pathological bodily process in a patient that occurs after a medical intervention. Causal adverse events are defined by OAE as those events that are causal consequences of a medical intervention. OAE represents various adverse events based on patient anatomic regions and clinical outcomes, including symptoms, signs, and abnormal processes. OAE has been used in the analysis of several different sorts of vaccine and drug adverse event data. (shrink)

This study examines why and when negative workplace gossip promotes self-serving behaviors by the employees being targeted. Using conservation of resources theory, we find that targets tend to increase their political acts as a result of ego depletion triggered by negative gossip. We also show that sensitivity to interpersonal mistreatment and moral disengagement moderate this process. Specifically, we demonstrate that targets with high levels of sensitivity to interpersonal mistreatment are more likely to experience ego depletion, and that targets with high (...) levels of moral disengagement will find it easier to persuade themselves to engage in political acts. We conducted a three-wave time-lagged survey of 265 employees in Guangdong, China, to test our hypotheses. The results support our theoretical model and indicate that COR theory can be used to explain the impacts of negative workplace gossip. Alongside our important and timely theoretical contributions, we provide new perspectives on how managers can avoid or mitigate these political acts. (shrink)

Abundant evidence has proved an association between peer victimization and problematic online game use. However, the underlying mechanisms of this relation are still under-investigated. Grounded in the ecological system theory, this study examined whether deviant peer affiliation and school connectedness mediated the association between peer victimization and adolescent POGU. A sample of 698 Chinese adolescents completed questionnaires regarding peer victimization, problematic online game use, DPA, and school connectedness, of which 51.58% were boys. Path analyses indicated that peer victimization was positively (...) associated with problematic online game use, and this link could be mediated by deviant peer affiliation and school connectedness. The findings identify the potential underlying mechanism by which peer victimization is associated with adolescent problematic online game use, which has important implications for theory and prevention. (shrink)

This paper makes a quantitative analysis of the comprehensive influence of music networks. Firstly, 11 music features are selected from energy, popularity, and other aspects to build a comprehensive evaluation index of music influence, and the PageRank algorithm is used to quantify the music influence. Secondly, the multiobjective logistic regression is used to construct the music similarity measurement model and, combined with music influence and music similarity, to judge whether the influence of different musicians is the actual influence. Thirdly, the (...) influence and similarity of the same music genre and different music genres are analyzed by using the two-way cluster analysis method. Finally, the lasso region is used for feature selection to obtain the change factors in the process of music evolution and analyze the dynamic changes in the process of music development. Therefore, this paper uses network science to build a dynamic network to analyze the similarity of music, the evolution process, and the impact of music on culture, which has certain research significance and practical value in the fields of music, history, social science, and practice. (shrink)

The complexity of language is usually reflected in the complexity of sentences. At present, the research of sentence complexity mainly focuses on the analysis of syntactic complexity. In this paper, from the perspective of Leech's theory of sentence semantic structure, the predication structure is taken as the semantic unit to explore the sentence semantic complexity. The predication structures are extracted based on the result of sentence-based syntactic analysis, and then the linear expression sequence of a sentence is converted into a (...) semantic hierarchy based on predicate semantic frameworks; the universality of predicate semantic frameworks is obtained by using the spectral clustering algorithm; and the sentence semantic complexity depends on the universality of predicate semantic frameworks at various layers. The experimental results show that the measurement method of sentence sematic complexity based on predicate semantic frameworks is more effective by comparing with the method that only considers the semantic categories of words in the sentence. (shrink)

哲學的有限性問題涉及認識論、生存論等維度，中國哲學在有限性問題上的認識複雜多端。書稿揭示了中國哲學史上有限性概念的主要內涵、流變及其消失。主要論述了先秦儒道兩家（包括孔子、思孟學派、《周易》、荀子、莊 子）對界限的認可，及宋明理學、內丹學等後世儒道學派對這一維度的轉變。並分析了中國思想史上有限性維度的困境及其消失，包括墨家的反對等等，進而論證了中國古代傳統中有限性維度消失在思維方式上的原因，包括中國 哲學宋代以後整體轉向內省的思維向度等。.

The increase of ETC vehicles on expressways has changed the proportion of ETC/MTC lanes at toll stations. Based on a driving simulator, three toll gate lane warning sign schemes were proposed in this study. Driving simulation experiments were conducted to study the influence of figures in warning signs at the manual toll station on the lane change timing of drivers. It was found that the addition of arrows to the warning signs can significantly shorten the response time and guide the (...) driver to make lane change decisions earlier to reduce the congestion between MTC vehicles and the mainline ETC vehicles at the toll plaza, thereby improving the traffic capacity and safety. (shrink)

Photovoltaic power forecasting can provide strong support for the safe operation of the power system. Existing forecasting methods are ineffective for grid scheduling decisions or risk analysis. The novel multicluster interval prediction method is proposed to consider the volatility and randomness of PV power output. First, this method utilizes the sparse autoencoder and Bayesian regularized NARX network for point forecasting of PV power. Second, density peak clustering improved by kernel Mahalanobis distance is applied to classify the dataset into multiple clusters, (...) including forecasting error and meteorological factors. Finally, the joint probability density is established by multivariate kernel density estimation to accomplish the PV power interval prediction. The proposed hybrid method is applied for the interval prediction of PV power at Yulara, Australia. Comparative research of point forecasting is implemented to evaluate the machine learning and deep learning methods, with the proposed SAE-BRNARX under four different periods. Results shows that the average values of nRMSE, MRE, nMAE, and R2 for the four periods are 4.45%, 0.90%, −0.15%, 3.39%, and 95.93%, respectively. Moreover, the results of interval prediction obtained by the other interval prediction approaches are compared with the proposed KMDDPC-MKDE. It shows that the average values of PICP, PINAW, ACE, and nMPICD for four periods are 93.93%, 9.50%, 3.93%, and 7.10% at 90% confidence level, respectively. Outcomes demonstrate that the proposed method can obtain more accuracy, a higher coverage rate, narrower average bandwidth, and a closer distance between the middle of interval and actual value than other methods. (shrink)