Y Li

This chapter provides an analysis of emerging GenAI tools and techniques that are transforming cybersecurity and ethical AI capabilities. It explores tools with innovative solutions across application security, data privacy, threat detection, governance, observability, and bias detection. The chapter analyzes how natural language processing, neural networks, reinforcement learning, and other GenAI technologies are being applied in purpose-built platforms to boost security, optimize workflows, and uphold transparency. Focus areas include leveraging GenAI tools to strengthen resilience, improve security posture, and promote responsible AI development.

Cellular reprogramming can manipulate the identity of cells to generate the desired cell types1– 3. The use of cell intrinsic components, including oocyte cytoplasm and transcription factors, can enforce somatic cell reprogramming to pluripotent stem cells4– 7. By contrast, chemical stimulation by exposure to small molecules offers an alternative approach that can manipulate cell fate in a simple and highly controllable manner8– 10. However, human somatic cells are refractory to chemical stimulation owing to their stable epigenome2,11,12 and reduced plasticity13,14; it is therefore challenging to induce human pluripotent stem cells by chemical reprogramming. Here we demonstrate, by creating an intermediate plastic state, the chemical reprogramming of human somatic cells to human chemically induced pluripotent stem cells that exhibit key features of embryonic stem cells. The whole chemical reprogramming trajectory analysis delineated the induction of the intermediate plastic state at the early stage, during which chemical-induced dedifferentiation occurred, and this process was similar to the dedifferentiation process that occurs in axolotl limb regeneration. Moreover, we identified the JNK pathway as a major barrier to chemical reprogramming, the inhibition of which was indispensable for inducing cell plasticity and a regeneration-like program by suppressing pro-inflammatory pathways. Our chemical approach provides a platform for the generation and application of human pluripotent stem cells in biomedicine. This study lays foundations for developing regenerative therapeutic strategies that use well-defined chemicals to change cell fates in humans.

In this paper, we propose a dynamic epistemic framework to capture the knowledge evolution in multi-agent systems where agents are not able to observe. We formalize multi-agent conformant planning with group knowledge, and reduce planning problems to model checking problems. We prove that multi-agent conformant planning with group knowledge is Pspace -complete on the size of dynamic epistemic models. We also consider the alternative Kripke semantics, and show that for each Kripke model with perfect recall and no miracles, there is an equivalent dynamic epistemic model and vice versa.

This study aims to assess the level and determinants of the general public's willingness to organ donation. We conducted a population-based cross-sectional study of 4261 participants in China. The primary outcome was the willingness to donate organs. Logistic regression modelling was used to determine the factors that affect willingness to donate organs. Overall, the proportion of participants who showed a willingness to donate organs was 47.45% (95%CI: 0.46, 0.49) in this study. Logistic regression modelling showed participants from Western (OR = 1.33, 95%CI = 1.11-1.59) and Eastern China (OR = 1.40, 95%CI = 1.19-1.65) were more willing to donate organs compared with those from Central China. The odds of being willing to donate organs was higher in females than males (OR = 1.35, 95%CI = 1.17-1.55); and was higher in those participants with experience of organ donation (OR = 1.58, 95%CI = 1.13-2.21), experience of caring for organ transplant patients (OR = 1.45, 95%CI = 1.01-2.07), and those undertaking related voluntary activities (OR = 1.67, 95%CI = 1.45-1.94), than those without. The general public's level of willingness to organ donation was not high in this study. Geographical region, gender, experience of organ donation related activities, taking care of organ transplant patients and volunteering in related activities were independently associated with participants' willingness to donate organs.

In special application scenarios, such as portable anesthesia depth monitoring, portable emotional state recognition and portable sleep monitoring, electroencephalogram (EEG) signal acquisition equipment is required to be convenient and easy to use. It is difficult to remove electrooculogram (EOG) artifacts when the number of EEG acquisition channels is small, especially when the number of observed signals is less than that of the source signals, and the overcomplete problem will arise. The independent component analysis (ICA) algorithm commonly used for artifact removal requires the number of basis vectors to be smaller than the dimension of the input data due to a set of standard orthonormal bases learned during the convergence process, so it cannot be used to solve the overcomplete problem. The empirical mode decomposition method decomposes the signal into several independent intrinsic mode functions so that the number of observed signals is more than that of the source signals, solving the overcomplete problem. However, when using this method to solve overcompleteness, the modal aliasing problem will arise, which is caused by abnormal events such as sharp signals, impulse interference, and noise. Aiming at the above problems, we propose a novel EEG artifact removal method based on discrete wavelet transform, complete empirical mode decomposition for adaptive noise (CEEMDAN) and ICA in this paper. First, the input signals are transformed by discrete wavelet (DWT), and then CEEMDAN is used to solve the overcomplete and mode aliasing problems, meeting the a priori conditions of the ICA algorithm. Finally, the components belonging to EOG artifacts are removed according to the sample entropy value of each independent component. Experiments show that this method can effectively remove EOG artifacts while solving the overcomplete and modal aliasing problems.

Leadership is considered as a significant antecedent of knowledge hiding in SMEs, but the differential dimension of leadership has been evidently neglected in both theoretical and empirical areas. Drawing on conservation of resource theory and social cognitive theory, this research investigates whether and how SME differential leadership influences subordinate knowledge hiding. Specifically, we analyze the underlying mechanisms of a chain-mediator—job insecurity and territorial consciousness and a boundary condition—leadership performance expectation. Multi-wave and multi-source data were collected from a sample of 704 Chinese SME employees and 140 relevant leaders and applied HLM meso-mediational frameworks, and Bootstrap technique with non-parametric percentile residuals for deviation correction. The results show that differential leadership plays a potential role in promoting subordinate knowledge hiding through the serial intervening mechanism of job Insecurity and territorial consciousness in SMEs. Furthermore, the positive relationship between SME differential leadership and job insecurity becomes stronger among subordinates under higher leadership performance expectation; the positive indirect relationship between SME differential leadership and subordinate knowledge hiding is stronger with higher levels of leadership performance expectation. This study contributes to the existing academic literature by empirically analyzing the under-investigated correlation between differential leadership and subordinate knowledge hiding in SMEs, and by exploring the underlying mechanisms and a boundary condition.

Systemic lupus erythematosus is an inflammatory autoimmune disease with depression as one of its most common symptoms. The aim of this study is to establish a nomogram prediction model to assess the occurrence of depression in patients with SLE. Based on the Hospital Anxiety and Depression Scale cutoff of 8, 341 patients with SLE, recruited between June 2017 and December 2019, were divided into depressive and non-depressive groups. Data on socio-demographic characteristics, medical history, sociopsychological factors, and other risk factors were collected. Between-group differences in clinical characteristics were assessed with depression as the dependent variable and the variables selected by logistic multiple regression as predictors. The model was established using R language. Marital status, education, social support, coping, and anxiety predicted depression. The nomogram prediction model showed that the risk rate was from 0.01 to 0.80, and the receiver operating characteristic curve analysis showed that the area under the curve was 0.891. The calibration curve can intuitively show that the probability of depression predicted by the nomogram model is consistent with the actual comparison. The designed nomogram provides a highly predictive assessment of depression in patients with SLE, facilitating more comprehensive depression evaluation in usual clinical care.

Live streaming shopping, the streaming of real-time videos promoting products that consumers can purchase online, has recently been a booming area of e-commerce, especially during the COVID-19 pandemic. The success of live streaming e-commerce largely relies on the extent to which the broadcaster can get consumers engaged by the live stream. Thus, it is important to discover the antecedents of consumer engagement in such a context. Drawing on consumer engagement and neuroscience literature, this study used electroencephalography inter-subject correlation to explore how broadcasters' entrepreneurial passion during live streaming videos influenced consumers' neural engagement as they watched the live streaming videos. We used the framework of displayed passion and preparedness from the entrepreneurial passion literature to predict consumer engagement. We found significant ISC for strong displayed passion, while preparedness had partially significant effects on the first, second, and summed components of ISC. The interaction effects of these two factors on the first and summed components of ISC were partially significant. Strong displayed passion and preparedness activated the left and right prefrontal regions of the consumers' brains. These findings indicate that broadcasters' displayed passion and preparedness can influence consumer engagement in live streaming e-commerce settings. Our findings suggest that a scientific approach could be used to improve a broadcaster's performance by testing ISC during rehearsals before live streaming.

It has been assumed sometimes that plagiarism is traditionally accepted in Confucian-heritage cultures such as China. In this paper we provide evidence to counter such a view. Focusing on a corpus of editorial statements on plagiarism cases published in Chinese journals in the decade of the early 1950s-the early 1960s, we present an integrated genre analysis and discourse analysis of this data. We illuminate 12 rhetorical move types in the focal genre and intertextual links between the genre and two related genres (readers’ disclosure reports and plagiarizers’ apologies) and demonstrate how plagiarism is construed as a transgressive practice and is imbued with the post-revolutionary Communist discourse of its historical period. The implications of the study apply to the academic community in terms of teaching and learning, on the one hand, and publication practices, on the other. We end the paper by emphasizing the importance of employing a contextualized approach to the study of plagiarism and the power of a triangulated genre and discourse analytic approach in the case of both the present research and the investigation of language use in the real-world more generally.

Third-party punishment (TPP) has been shown to be an effective mechanism for maintaining human cooperation. However, it is puzzling how third-party punishment can be maintained, as punishers take on personal costs to punish defectors. Although there is evidence that punishers are preferred as partners because third-party punishment is regarded by bystanders as a costly signal of trustworthiness, other studies show that this signaling value of punishment can be severely attenuated because third-party helping is viewed as a stronger signal of trustworthiness than third-party punishment. Third-party helpers donate their payoffs to victims of defection in games instead of punishing defectors as third-party punishers do. Then, under what circumstances can third-party punishment be maintained by costly signaling when helping is also present? We show that punishers are preferred over helpers by fourth-party individuals as their delegates to deter potential exploitation. This suggests that costly signaling can facilitate the maintenance of third-party punishment in partner choice with delegation interactions.

Entrepreneurial intention is an important condition for promoting substantive entrepreneurial behavior, which in turn alleviates employment pressure and promotes sustainable economic and social development. Based on national survey data of university students, descriptive statistical analysis of variables and binary logistic regression analysis were used to empirically analyze the factors influencing university students’ entrepreneurial intentions in five aspects, including innate endowment, acquired characteristics, entrepreneurship courses, and entrepreneurial practice, and social support. The regression results showed that both the factors of innate endowment and acquired characteristics passed the significance test. The entrepreneurship course factor had a significant impact on entrepreneurial intention, with the mean value of the number of entrepreneurship courses hitting 1.80, which is much lower than the other subdivision factors, indicating that there is a greater demand for entrepreneurship courses offered by university students, while the actual situation is less than satisfactory. The entrepreneurial practice factor is also an important factor, with an overall mean of 3 or more, and has a significant impact on entrepreneurial intentions, but in comparison, the factor of having an off-campus practice base for entrepreneurial practice has the lowest mean score, which shows that there is some room for improvement in the construction of off-campus practice bases. The social support factor significantly influences the willingness to start a business, and the mean score for each factor is above the medium level. By understanding which students are more willing to start a business and which factors are more likely to influence their willingness to start a business, we can further consider what kind of entrepreneurial skills and entrepreneurship education can lead to high-quality entrepreneurship and employment.

The theory of embodied semantics holds that verbal metaphors are strongly grounded in sensorimotor experience. Many studies have proven that besides sensorimotor simulation, the comprehension of verbal metaphors also requires semantic abstraction. But the interaction between simulation and abstraction, as well as the time course of metaphorical meaning integration, is not well understood. In the present study, we aimed to investigate whether embodiment or abstraction, or both, is employed in the processing of Chinese verbal metaphor. Participants were asked to read subject-verb metaphorical, verb-object metaphorical, literal-concrete and literal-abstract sentences, and the target words were measured at the verb and the object of each sentence. The results revealed that a similar N400 effect was elicited by the target verbs in the verb-object metaphorical and the literal-concrete sentences, and a similar P600/LPC effect was induced by the target verbs in the subject-verb metaphorical and the literal-abstract sentences, reflecting that the verb-object metaphors trigger a simulation process, while the subject-verb metaphors trigger an abstraction process in the verb processing stage. Moreover, the subject-verb metaphors elicited a stronger P600/LPC effect by the target verbs than the verb-object metaphors, but there was no difference of the P600/LPC caused by the target objects between the two kinds of metaphors, revealing that the metaphorical meaning of a subject-verb metaphor is integrated in the verb processing stage, while that of a verb-object metaphor is reanalyzed in the object processing stage. These results suggest that a verbal metaphor is processed both by simulation and abstraction, and the metaphorical meaning is integrated immediately with the unfolding of the sentence meaning. The position where the semantic conflict lies in a sentence modulates the time course of metaphor sentence comprehension.

Financial literacy is essential for every individual concerned with public welfare and household portfolio choices. In this study, we investigate the impact of household financial literacy on individuals’ financial behavior using the China Household Financial Survey Data of 2015 and 2017. The results show that financial knowledge has significant current, long-term, and dynamic effects on financial behavior. This finding suggests that financial literacy is an important factor in shaping and improving financial behavior. Second, financial literacy can improve residents’ limited attention, and residents with high attention tend to have formal bank accounts, participate in the stock market, and engage in financial behaviors in situations such as risky financial markets. High attention also helps to improve residents’ financial behavior. This relationship suggests that financial literacy positively impacts formal bank account holding, participation in financial markets, participation in commercial insurance, participation in pension plans, and credit card holdings through limited attention channels that facilitate access to specific financial information. In addition, heterogeneity analysis showed that the impact of financial literacy on financial behavior differs significantly between urban and rural households, between men and women, and between high and low education levels. The study provides valuable insights for policy implications to enhance financial literacy, such as carrying out financial training to improve residents’ knowledge about financial aspects, which further helps to optimize household financial decision-making.

It is interesting to explore the effects of second language acquisition on anatomical change in brain at different stages for the neural structural adaptations are dynamic. Short-term Chinese training effects on brain anatomical structures in alphabetic language speakers have been already studied. However, little is known about the adaptations of the gray matter induced by acquiring Chinese language for a relatively long learning period in adult alphabetic language speakers. To explore this issue, we recruited 38 Indian overseas students in China as our subjects. The learned group included 17 participants who had learned Mandarin Chinese for an average of 3.24 years and achieved intermediate Chinese language proficiency. The control group included 21 subjects who had no knowledge about Chinese. None of the participants had any experience in learning logographic and tonal language before Chinese learning. We found that the learned group had significantly greater gray matter volume in the left lingual gyrus compared with the control group; the Chinese characters’ reading accuracy was significantly and positively correlated to the GMV in the left LG and fusiform gyrus across the two groups; and in the learned group, the duration of Chinese learning was significantly and positively correlated with the GMV in the left inferior frontal gyrus after correction for multiple comparisons with small volume corrections. Our structural imaging findings are in line with the functional imaging studies reporting increased brain activation induced by Chinese acquisition in alphabetic language speakers. The regional gray matter changes reflected the additional requirements imposed by the more difficult processing of Chinese characters and tones. The present study also show that the biological bases of the adaptations induced by a relatively long period of Chinese learning were limited in the common areas for first and foreign language processing.

The aim of this study was to explain previous inconsistent results regarding the effects of positive affect on creative cognition based on the motivational dimensional model of affect theory and provide the underlying neural correlates of the effects of different approach-motivation intensities of positive affect on creative processes (creative idea generation and creative idea evaluation) using the functional near-infrared spectroscopy (fNIRS) technique. Sixty participants were randomly assigned to three groups (high-approach-motivated positive affect (HAM), low-approach-motivated positive affect (LAM) and affectively neutral state (NS)) to complete corresponding tasks in creative idea generation and creative idea evaluation stages. In the creative idea generation stage, the results indicated that the LAM group achieved a higher performance in flexibility and originality than the NS group. However, compared with the NS group, the LAM group exhibited a lower sensitivity in the creative idea evaluation stage. The fNIRS technique provides an ideal approach with high ecological validity for exploring the issue of affect and creativity. In current study, fNIRS results showed that the HAM group exhibited significantly more activation in the bilateral frontal lobe than the LAM group and NS group in the creative idea generation stage. This result could reflect individuals attempting to overcome a narrowed attentional scope state through the activation of bilateral frontal cortical resources in the creative process. In the creative idea evaluation stage, compared with the NS group, the LAM group showed significant deactivation in the right dorsolateral prefrontal cortex, which is a brain area associated with executive, controlled processing. Moreover, the approach-motivation intensity altered the connectivity between the left prefrontal cortex and left superior temporal gyrus in the creative idea generation stage. Thus, the influences of positive affect on creative cognitive processes (both creative performance and hemodynamic responses) were modulated by the approach-motivation intensity in the creative idea generation and creative idea evaluation stages.

This study aimed to explore the effect of parents’ education anxiety on children’s academic burnout, and the mediation effect of parental burnout and the moderating effect of family function. A total of 259 paired parents and children from two middle schools in central China participated in the survey. The questionnaire was conducted using the Educational Anxiety Scale, Parental Burnout Scale, Adolescent Student Burnout Inventory, and Family APGAR Index. Our results indicated that parental education anxiety had a positive predictive effect on children’s academic burnout. Moreover, parental burnout played a complete mediating role between parents’ education anxiety and children’s academic burnout. Finally, the relationship between education anxiety and parental burnout was moderated by family function, and higher family function buffered the effect of education anxiety on parental burnout. The results suggest the mechanism of parental education anxiety on children’s academic burnout, and the role of family function in alleviating parental burnout.

This study aimed to develop and test the reliability and validity of a multi-item nurses’ presenteeism behaviour questionnaire. Study 1 administered the Nurse Presenteeism Questionnaire to 250 Chinese nurses. Study 2, surveyed 650 nurses with the NPQ, the Sickness Presenteeism Questionnaire, the Stanford Presenteeism Scale, the General Health Questionnaire, and the Emotional Exhaustion Scale using convenience sampling. After item analysis, the subjects were randomly divided into two groups to verify the questionnaire structure. Study 1 revealed the nurses’ core symptoms when they go to work with illness, and the NPQ with 11 items was developed. Study 2’s item analysis revealed that 11 NPQ items had good discrimination and high homogeneity. Besides, the scale had good reliability and external criterion validity. Thus, the NPQ can be used to measure presenteeism behaviour in nursing.

In this paper, through research and analysis of the communication network of the physical activity monitoring system, we combine wearable technology and identification technology and design a physical health monitoring bracelet that integrates multifaceted physical data collection and effective identity matching function. We match the identity through the chip and collect the physical fitness data generated in the process of exercise and centralized test by the sensor in real-time. Finally, the data transmission is realized through the WIFI communication function to achieve the purpose of monitoring physical exercise and improving physical quality. To ensure the continuity and stability of information transmission, the joint transmission method of direct transmission and indirect transmission is essential. Besides, considering the energy causality limitation of sensor nodes and relay nodes, a collaborative transmission model of wireless body area network based on wireless cognitive network is constructed. And, a power allocation algorithm based on maximum ratio merging and wireless cognitive network is proposed, which puts forward a new idea for the future research of wireless body area network resource allocation.

Lithium-ion batteries have been widely used as energy storage systems and in electric vehicles due to their desirable balance of both energy and power densities as well as continual falling price. Accurate estimation of the state-of-charge of a battery pack is important in managing the health and safety of battery packs. This paper proposes a compact radial basis function neural model to estimate the state-of-charge of lithium battery packs. Firstly, a suitable input set strongly correlated with the package SOC is identified from directly measured voltage, current, and temperature signals by a fast recursive algorithm. Secondly, a RBF neural model for battery pack SOC estimation is constructed using the FRA strategy to prune redundant hidden layer neurons. Then, the particle swarm optimization algorithm is used to optimize the kernel parameters. Finally, a conventional RBF neural network model, an improved RBF neural model using the two stage method, and a least squares support vector machine model are also used to estimate the battery SOC as a comparative study. Simulation results show that generalization error of SOC estimation using the novel RBF neural network model is less than half of that using other methods. Furthermore, the model training time is much less than the LSSVM method and the improved RBF neural model using the two-stage method.

As the most frequently used tool for measuring empathy, the Interpersonal Reactivity Index (IRI) is often scored by researchers arbitrarily and casually. Many commonly used IRI scoring approaches and their corresponding measurement models are unverified, which may make the conclusions of subsequent variable relation studies controversial and even misleading. We make the first effort to summarize these measurement models and to evaluate rationality of the common scoring methods of the IRI by confirmatory factor analysis, focusing on model fitting, factor loading, and model-based reliability simultaneously. The results show that most of these models do not fit well, indicating that the scoring approaches of the IRI corresponding to these models may be problematic. Relatively speaking, better scoring approaches of the IRI include summing empathic concern and perspective taking as the total score of the IRI and reporting the score of perspective taking as cognitive empathy.