Ting Zhang

This study examines the effect of the CEO incentive horizon (captured by CEO pay duration) on workplace safety, a critical aspect of employee welfare. Using establishment-level data on workplace safety, we find CEO incentive horizon is negatively associated with workplace injuries and illnesses. This relation is stronger when CEOs have more career concerns or lower ability and weaker when the firm’s workers’ compensation premiums are more sensitive to injury claims or there is a greater union presence. Further, increased investments in safety and decreased employee workload are two possible channels through which the incentive horizon–injury/illness relation operates. Overall, our results suggest that increasing the CEO incentive horizon promotes employee welfare by fostering a safer work environment.

BackgroundComplex health care environments present moral dilemmas for clinical nurses and nursing students that challenge their professional development as well as their physical and mental health. Ethical sensitivity (ES) is seen as a prerequisite that enables clinical nurses to make appropriate ethical decisions when facing a dilemma; therefore, ES should be a development focus for nursing students.PurposeThe aim of this study is to conduct a systematic evaluation of existing instruments to assess moral sensitivity (MS) or ES in nursing students. We subsequently provide recommendations of the proper research tools that can be used in future studies based on our study results.MethodsA systematic literature search across nine databases from their inception to November 17, 2024 was first conducted. Two researchers then independently screened these studies, which were published in English or Chinese. The studies evaluated were designed to develop or validate a scale used to measure ES or MS among nursing students. The COnsensus-based Standards for the Selection of Health Measurement INstruments (COSMIN) guidelines were followed to evaluate both the methodological quality and the quality of the psychometric properties of the identified tools. Finally, data synthesis was performed.ResultsWe ultimately included 13 assessment tools used for the assessment of ES or MS among nursing students. Only one tool was rated A, and four tools were rated C and not recommended for use. The remaining tools were rated B, and they have potential for assessing MS and ES among nursing students.ConclusionA majority of the tools included in this study still require further revision to enhance their quality prior to their effective use in MS and ES assessments. The COSMIN guidelines indicated that future studies should describe the development and validation of measurement tools in detail and improve their current data analysis methods.

ObjectivesSeveral studies have examined the effects of repetitive transcranial magnetic stimulation (rTMS) on associative memory (AM) but findings were inconsistent. Here, we aimed to test whether twice-daily rTMS could significantly improve AM.MethodsIn this single-blind, sham-controlled experiment, 40 participants were randomized to receive twice-daily sham or real rTMS sessions for five consecutive days (a total of 16,000 pulses). The stimulation target in left inferior parietal lobule (IPL) exhibiting peak functional connectivity to the left hippocampus was individually defined for each participant. Participants completed both a picture-cued word association task and Stroop test at baseline and 1 day after the final real or sham rTMS session. Effects of twice-daily rTMS on AM and Stroop test performance were compared using two-way repeated measures analysis of variance with main factors Group (real vs. sham) and Time (baseline vs. post-rTMS).ResultsThere was a significant Group × Time interaction effect. AM score was significantly enhanced in the twice-daily real group after rTMS, but this difference could not survive the post hoc analysis after multiple comparison correction. Further, AM improvement in the twice-daily real group was not superior to a previously reported once-daily rTMS group receiving 8,000 pulses. Then, we combined the twice- and once-daily real groups, and found a significant Group × Time interaction effect. Post hoc analysis indicated that the AM score was significantly enhanced in the real group after multiple comparisons correction.ConclusionOur prospective experiment did not show significant rTMS effect on AM, but this effect may become significant if more participants could be recruited as revealed by our retrospective analysis.

From a cognitive linguistic perspective, this article delves into the polysemy between the English term sour and its Chinese counterpart suan. The research aims to achieve two key objectives: (1) To explore the similarities and differences in the polysemy of sour in English and suan in Chinese; (2) To identify the cognitive mechanisms that motivate the semantic expansion of sour in English and suan in Chinese. To this end, 《汉语大词典》(the Great Chinese Dictionary), The Oxford English Dictionary (OED), the British National Corpus (BNC), and the Centre for Chinese Linguistics (CCL) Chinese-English Parallel Corpus were used. The dictionaries are utilized to explore the polysemy of sour and suan, while the BNC and CCL Chinese-English Parallel Corpus are employed to investigate the cognitive mechanisms underlying the semantic extensions of the selected terms. Theoretically, this article draws upon the conceptual metaphor and metonymy theory proposed by Lakoff and Johnson. The findings reveal significant semantic overlap between sour in English and suan in Chinese, yet notable distinctions remain. This study has implications for vocabulary teaching as well as cross-linguistic and cross-cultural communication.

Wordsworth’s The Excursion (1814) redefines home as an evolving ecosystem of communal becoming, where fractures in language and perception foster collective renewal. The poem constructs a “logos of home” through the geological ethics of care, narrative co-presence, and sensory transformation. Dialogic narratives—from fragmented tales to epitaphic voices—transmute trauma into shared memory, while geological motifs spatialize time through labour and decay. Sensory deprivation challenges Enlightenment ocularcentrism, recasting disability as sites of ethical richness. By grounding communal being in marginalized temporalities, Wordsworth rejects teleological unity, proposing a stratified form of belonging: the dead endure as geological strata, the marginalized speak through vegetal signs, and sensory loss sustains communal resilience. Anticipating modern ecological thought, the poem redefines coexistence as cyclical remembrance rather than progress. The Excursion ultimately posits the condition of brokenness as modernity’s ethical imperative, where land, labour, and memory rewrite temporality through geological patience.

This study explores the polysemy of the word “bitter” in English and ku in Chinese. It examines the similarities and differences between their semantics and identifies the cognitive mechanisms that motivate their semantic expansion. The study attempts to answer two questions: (1) What are the similarities and differences between Chinese ku and English “bitter” in terms of meaning? (2) What cognitive mechanisms motivate meaning extensions of these two words? To this end, 汉语大词典 (Chinese Dictionary), 英汉大词典 (English-Chinese Dictionary), the British National Corpus (BNC) and BLCU Corpus Center (BCC) were employed. The two dictionaries were utilised to investigate the multiple meanings of the two terms, while the BNC and the BCC were employed to identify metaphors and metonymies in sentences. Theoretically, the study is informed by Lakoff and Johnson’s conceptual metaphor and conceptual metonymy. The results showed that half of the meanings of “bitter” and ku overlapped, but there were still some differences. Their semantic expansion is motivated by both conceptual metonymy and conceptual metaphor. In addition, the words under investigation differ in the emotions expressed. English “bitter” is more negative, while Chinese ku is more positive. The present findings have important implications for education and cross-cultural communication in language.

The electroencephalogram is the most common method used to study emotions and capture electrical brain activity changes. Long short-term memory processes the temporal characteristics of data and is mostly used for emotional text and speech recognition. Since an EEG involves a time series signal, this article mainly studied the introduction of LSTM for emotional EEG recognition. First, an ALL-LSTM model with a four-layered LSTM network was established in which the average accuracy rate for emotional classification reached 86.48%. Second, four EEG characteristics were extracted via the wavelet transform using the LSTM-based sentiment classification network. The experimental results showed that the best average classification accuracy of these four features was 73.48%. This was 13% lower than in the ALL-LSTM model, indicating that inappropriate feature extraction methods could destroy the timing of EEG signals. LSTM can be used to thoroughly examine EEG signal timing and preprocessed EEG data. The accuracy and stability of the ALL-LSTM model are significantly superior to those of the WT-LSTM model. The result showed that the process of emotion generation based on EEG is sequential. Compared with EEG emotion extraction using WT, the raw EEG signal’s timing is more suitable for the LSTM network.

Currently, the coronavirus disease 2019 pandemic experienced by the international community has increased the usage frequency of borderless, highly personalized social media platforms of all age groups. Analyzing and modeling texts sent through social media online can reveal the characteristics of the psychological dynamic state and living conditions of social media users during the pandemic more extensively and comprehensively. This study selects the Sina Weibo platform, which is highly popular in China and analyzes the subjective well-being of Weibo users during the COVID-19 pandemic in combination with the machine learning classification algorithm. The study first invokes the SWB classification model to classify the SWB level of original texts released by 1,322 Weibo active users during the COVID-19 pandemic and then combines the latent growth curve model and the latent growth mixture model to investigate the developmental trend and heterogeneity characteristics of the SWB of Weibo users after the COVID-19 outbreak. The results present a downward trend and then an upward trend of the SWB of Weibo users during the pandemic as a whole. There was a significant correlation between the initial state and the development rate of the SWB after the COVID-19 outbreak. LGMM results show that there were two heterogeneous classes of the SWB after the COVID-19 outbreak, and the development rate of the SWB of the two classes was significantly different. The larger class showed a slow growth, while the smaller class showed a rapid growth. Furthermore, the slope means across the two classes were significantly different. Therefore, the individuals with a higher growth rate of SWB exhibited stronger adaptability to the changes in their living environments. These results could help to formulate effective interventions on the mental health level of the public after the public health emergency outbreak.

Previous research studies of traffic networks are mainly based on planar networks and less considered the influence of multilayer networks, which illustrate and represent different appropriate urban traffic modes. Development of rail and road networks is inseparable from the development of a prosperous urban area; thus, research on multilayer networks has scientific potential and fulfils a real need. In this paper, a framework of complex network based integrated multilayer urban growth and optimisation model is proposed, to analyse the complex relationships between the traffic network structure, the population growth, and the urban land-use. The innovation of this paper is the combination of the traffic complex multilayer networks and the “Four Step Model”. With the multiobjective, multilayer network coevolution and optimisation model, a more efficient traffic network layout was generated based on different land-use, population density, and travel speed scenarios. Then, this paper has proved that the proposed CNIMUGOM can save the traffic network construction investment, reduce the travel cost, make the urban traffic network more efficient, and decrease the total traffic flow amount. This research has connected the recent complex multilayer network related study and traditional urban economic model based study. The findings of the study afford to improve the current land-use and traffic integrated models and can provide traffic network planning suggestions for urban agglomeration development.

The completeness of the modal logic S4 for all topological spaces as well as for the real line, the n-dimensional Euclidean space and the segment etc. was proved by McKinsey and Tarski in 1944. Several simplified proofs contain gaps. A new proof presented here combines the ideas published later by G. Mints and M. Aiello, J. van Benthem, G. Bezhanishvili with a further simplification. The proof strategy is to embed a finite rooted Kripke structure for S4 into a subspace of the Cantor space which in turn encodes. This provides an open and continuous map from onto the topological space corresponding to. The completeness follows as S4 is complete with respect to the class of all finite rooted Kripke structures.

This paper investigates the integrity of financial analysts by examining their recommendation responses to large quarterly earnings surprises. Although there is no significant difference in recommendation changes between affiliated and unaffiliated analysts in response to positive earnings surprises, affiliated analysts are more reluctant than unaffiliated analysts to downgrade stock recommendations in response to negative earnings surprises. The evidence implies that conflicts of interest undermine the integrity of financial analysts. We further examine the effects of reputation concern and the Global Research Analyst Settlement as informal and formal mechanisms, on restoring analysts’ integrity. The results show that the positive bias in recommendations remains prevalent for affiliated analysts from reputable investment banks and for the postreform period. Finally, evidence from market reactions suggests that investors fail to notice that analysts’ integrity is compromised by conflicts of interest and are misled by affiliated analysts.

The completeness of the modal logic S4 for all topological spaces as well as for the real line , the n-dimensional Euclidean space and the segment etc. was proved by McKinsey and Tarski in 1944. Several simplified proofs contain gaps. A new proof presented here combines the ideas published later by G. Mints and M. Aiello, J. van Benthem, G. Bezhanishvili with a further simplification. The proof strategy is to embed a finite rooted Kripke structure for S4 into a subspace of the Cantor space which in turn encodes . This provides an open and continuous map from onto the topological space corresponding to . The completeness follows as S4 is complete with respect to the class of all finite rooted Kripke structures