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The Communist Party of China has ruled mainland China since 1949. From Marxist revolution and class struggle to market reforms and national rejuvenation, the Party has repeatedly reinvented itself and its justification for monopolizing political power. Bringing together experts from a range of disciplines around the globe, this collection serves as a guide to understanding the Party's unparalleled durability. They examine a range of themes including the mechanics and organisation of one-party rule, the ideologies underpinning party rule, the Party's control of public discourse, technologies of social control, and adaptive policymaking. Read together, these essays provide a comprehensive understanding of the reasons for the Party's continued grip on political power in China today.
Submerged flexible aquatic vegetation exists widely in nature and achieves multiple functions mainly through fluid–structure interactions (FSIs). In this paper, the evolution of large-scale vortices above the vegetation canopy and its effect on flow and vegetation dynamics in a two-dimensional (2-D) laminar flow are investigated using numerical simulations under different bending rigidity $\gamma$ and gap distance d. According to the variation of large-scale vortex size and intensity, the evolution process is divided into four distinct zones in the streamwise direction, namely the ‘developing’ zone, ‘transition’ zone, ‘dissipation’ zone and ‘interaction’ zone, and different evolution sequences are further classified. In the ‘developing’ zone, the size and intensity of the large-scale vortex gradually increase along the array, while they decrease in the ‘dissipation’ zone. The supplement of vegetation oscillating vortices to large-scale vortices is the key to the enhancement of the latter. The most obvious dissipation of large-scale vortices occurs in the ‘transition’ zone, where the position of the large-scale vortex is significantly uplifted. The effects of $\gamma$ and d on the evolution of the large-scale vortex are discussed. In general, the features of vegetation swaying vary synchronously with those of large-scale vortices. The flow above the canopy is dominated by large-scale vortices, and the development of flow characteristics such as time-averaged velocity profile and Reynolds stress are closely related to the evolution of large-scale vortices. The flow inside the canopy, however, is mainly affected by the vortex shed by the vegetation oscillation, which leads to the emergence of negative time-averaged velocity and negative Reynolds stress.
Emotional processing difficulties represent the core psychopathology of non-suicidal self-injury (NSSI), yet the underlying neural mechanisms remain unclear.
Aims
To investigate neural alterations associated with emotion reactivity and regulation in individuals with NSSI and examine whether emotional valence is related to these neural patterns.
Method
During functional magnetic resonance imaging scans, unmedicated young adults with NSSI (n = 29) and matched controls (n = 25) completed an emotion regulation task in which they viewed pictures of different emotional categories with instructions to either attend to or regulate their emotions.
Results
Individuals with NSSI showed increased neural activation in the right superior temporal gyrus (STG), right parahippocampal gyrus and right supramarginal gyrus during negative emotion reactivity and increased activation in the right middle temporal gyrus and left STG during positive emotion reactivity. Conversely, those with NSSI exhibited reduced activation in the left supplementary motor area, left inferior frontal gyrus, right putamen, right thalamus and right STG during negative emotion regulation and reduced activation in the left ventral striatum during positive emotion regulation. Notably, both hyperactivation of the STG during negative emotion reactivity and hypoactivation of the supplementary motor area during negative emotion regulation were associated with emotion dysregulation in individuals with NSSI.
Conclusions
We observed distinct neural patterns of emotional processing among individuals with NSSI, characterised by hyperactivation during emotion reactivity and hypoactivation during emotion regulation. Our findings provide a neurophysiological basis for therapeutic interventions that facilitate adaptive emotional processing in individuals with NSSI.
The lattice walks in the plane starting at the origin $\mathbf {0}$ with steps in $\{-1,0,1\}^{2}\setminus \{\mathbf {0}\}$ are called king walks. We investigate enumeration and divisibility for higher dimensional king walks confined to certain regions. Specifically, we establish an explicit formula for the number of $(r+s)$-dimensional king walks of length n ending at $(a_1,\ldots ,a_r,b_1,\ldots ,b_s)$ which never dip below $x_i=0$ for $i=1,\ldots ,r$. We also derive divisibility properties for the number of $(r+s)$-dimensional king walks of length p (an odd prime) through group actions.
Anhedonia, a transdiagnostic feature common to both Major Depressive Disorder (MDD) and Schizophrenia (SCZ), is characterized by abnormalities in hedonic experience. Previous studies have used machine learning (ML) algorithms without focusing on disorder-specific characteristics to independently classify SCZ and MDD. This study aimed to classify MDD and SCZ using ML models that integrate components of hedonic processing.
Methods
We recruited 99 patients with MDD, 100 patients with SCZ, and 113 healthy controls (HC) from four sites. The patient groups were allocated to distinct training and testing datasets. All participants completed a modified Monetary Incentive Delay (MID) task, which yielded features categorized into five hedonic components, two reward consequences, and three reward magnitudes. We employed a stacking ensemble model with SHapley Additive exPlanations (SHAP) values to identify key features distinguishing MDD, SCZ, and HC across binary and multi-class classifications.
Results
The stacking model demonstrated high classification accuracy, with Area Under the Curve (AUC) values of 96.08% (MDD versus HC) and 91.77% (SCZ versus HC) in the main dataset. However, the MDD versus SCZ classification had an AUC of 57.75%. The motivation reward component, loss reward consequence, and high reward magnitude were the most influential features within respective categories for distinguishing both MDD and SCZ from HC (p < 0.001). A refined model using only the top eight features maintained robust performance, achieving AUCs of 96.06% (MDD versus HC) and 95.18% (SCZ versus HC).
Conclusion
The stacking model effectively classified SCZ and MDD from HC, contributing to understanding transdiagnostic mechanisms of anhedonia.
We present a simulation study based on a cognitive architecture that unifies various early language acquisition phenomena in laboratory and naturalistic settings. The model adaptively learns procedures through trial-and-error using general-purpose operators, guided by learned contextual associations to optimise future performance. For laboratory-based studies, simulated preferential focusing explains the delayed behavioural onset of statistical learning and the possible age-related decrease in algebraic processing. These findings suggest a link to continuous, implicit learning rather than explicit strategy acquisition. Moreover, procedures are not static but can evolve over time, and multiple plausible procedures may emerge for a given task. Besides, the same model provides a proof-of-concept for word-level phonological learning from naturalistic infant-directed speech, demonstrating how age-related processing efficiency may influence learning trajectories implicated in typical and atypical early language development. Furthermore, the artile discusses the broader implications for modelling other aspects of real-world language acquisition.
This paper focuses on the concept of delaying laminar–turbulent transition in hypersonic boundary layers by stabilising fundamental resonance (FR), a key nonlinear mechanism in which finite-amplitude Mack modes support the rapid growth of oblique perturbations. As a pioneering demonstration of this control strategy, we introduce surface heating applied exclusively during the nonlinear phase. Unlike traditional control methods that target the linear phase, the suppressive effect of surface heating on secondary instability modes during FR is evident across various Reynolds numbers, wall temperatures and fundamental frequencies, as confirmed by direct numerical simulations (DNS) and secondary instability analyses (SIA). To gain deeper insights into this control concept, an asymptotic analysis is conducted, revealing an almost linear relationship between the suppression effect and the heating intensity. The asymptotic predictions align overall with the DNS and SIA calculations. The asymptotic theory reveals that the suppression effect of FR is primarily influenced by modifications to the fundamental-mode profile, while mean-flow distortion has a comparatively modest yet opposing impact on this process. This research presents a promising approach to controlling transition considering the nonlinear evolution of boundary-layer perturbations, demonstrating advantages over conventional methods that are sensitive to frequency variations.
A systematic study is conducted both experimentally and theoretically on the wake-induced vibration of an inelastic or zero structural stiffness cylinder placed behind a perfectly elastic or rigid cylinder. The mass ratio m* of the inelastic cylinder is 11.1. The spacing ratio L/D is 2.0–6.0, where L is the distance between centers of the two cylinders, and D is the cylinder diameter. The range of Reynolds number Re is 1.97 × 103–1.18 × 104. It has been found that the inelastic cylinder becomes aerodynamically elastic because the cylinder and the fluctuating wake interact, inducing an effective stiffness and thus giving rise to an aeroelastic natural frequency. This frequency depends on the added mass, fluid damping and flow-induced stiffness and is always smaller than the vortex shedding frequency, irrespective of Re and L/D. The wake-induced vibration of the inelastic cylinder may be divided into a desynchronisation branch and a galloping branch. The vibration amplitude jumps greatly at the transition from desynchronisation to galloping for L/D = 2.0–4.5 but not so for L/D = 5.0–6.0. The flow-induced stiffness is linearly correlated with Re, generally higher in the reattachment regime than in the coshedding regime and smaller in galloping than in desynchronisation. Other aspects of the inelastic cylinder are also investigated in detail, including the dependence on Re of the Strouhal numbers, hydrodynamic forces, phase lag between lift and displacement and flow characteristics.
Tuberculosis (TB) remains a significant public health concern in China. Using data from the Global Burden of Disease (GBD) study 2021, we analyzed trends in age-standardized incidence rate (ASIR), prevalence rate (ASPR), mortality rate (ASMR), and disability-adjusted life years (DALYs) for TB from 1990 to 2021. Over this period, HIV-negative TB showed a marked decline in ASIR (AAPC = −2.34%, 95% CI: −2.39, −2.28) and ASMR (AAPC = −0.56%, 95% CI: −0.62, −0.59). Specifically, drug-susceptible TB (DS-TB) showed reductions in both ASIR and ASMR, while multidrug-resistant TB (MDR-TB) showed slight decreases. Conversely, extensively drug-resistant TB (XDR-TB) exhibited upward trends in both ASIR and ASMR. TB co-infected with HIV (HIV-DS-TB, HIV-MDR-TB, HIV-XDR-TB) showed increasing trends in recent years. The analysis also found an inverse correlation between ASIRs and ASMRs for HIV-negative TB and the Socio-Demographic Index (SDI). Projections from 2022 to 2035 suggest continued increases in ASIR and ASMR for XDR-TB, HIV-DS-TB, HIV-MDR-TB, and HIV-XDR-TB. The rising burden of XDR-TB and HIV-TB co-infections presents ongoing challenges for TB control in China. Targeted prevention and control strategies are urgently needed to mitigate this burden and further reduce TB-related morbidity and mortality.
This study investigates heritage speakers (HSs) of Spanish in the U.S. and potential areas of divergence in speech from homeland speakers. To examine the relative contribution of prosody and segments in perceived heritage accent, we conducted an accent rating task with speech samples of second language learners (L2s), HSs and homeland speakers presented in three conditions: original, prosody-only and segments-only. The stimuli were rated by two groups: HSs and homeland speakers. The results revealed that HSs and homeland speakers had similar global accent perceptions, rating HSs as more native-like than L2s but less native-like than homeland speakers. We found that both rater groups aligned with a dominant language ideology of Spanish; speakers who were judged as more native-like were perceived as residing in a Spanish-speaking country. Our findings also demonstrate that prosody contributes more to perceived heritage accent than segments, while segments contribute more to L2 foreign accent than prosody.
Researchers have long debated which spatial arrangements and swimming synchronisations are beneficial for the hydrodynamic performance of fish in schools. In our previous work (Seo and Mittal, Bioinsp. Biomim., Vol. 17, 066020, 2022), we demonstrated using direct numerical simulations that hydrodynamic interactions with the wake of a leading body -caudal fin carangiform swimmer could significantly enhance the swimming performance of a trailing swimmer by augmenting the leading-edge vortex (LEV) on its caudal fin. In this study, we develop a model based on the phenomenology of LEV enhancement, which utilises wake velocity data from direct numerical simulations of a leading fish to predict the trailing swimmer’s hydrodynamic performance without additional simulations. For instance, the model predicts locations where direct simulations confirm up to 20 % enhancement of thrust. This approach enables a comprehensive analysis of the effects of relative positioning, phase difference, flapping amplitude, Reynolds number and the number of swimmers in the school on thrust enhancement. The results offer several insights regarding the effect of these parameters that have implications for fish schools as well as for bio-inspired underwater vehicle applications.
Understanding the mechanisms of major depressive disorder (MDD) improvement is a key challenge to determining effective personalized treatments.
Methods
To identify a data-driven pattern of clinical improvement in MDD and to quantify neural-to-symptom relationships according to antidepressant treatment, we performed a secondary analysis of the publicly available dataset EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care). In EMBARC, participants with MDD were treated either by sertraline or placebo for 8 weeks (Stage 1), and then switched to bupropion according to clinical response (Stage 2). We computed a univariate measure of clinical improvement through a principal component (PC) analysis on the variations of individual items of four clinical scales measuring depression, anxiety, suicidal ideas, and manic-like symptoms. We then investigated how initial clinical and neural factors predicted this measure during Stage 1 by running a linear model for each brain parcel’s resting-state global brain connectivity (GBC) with individual improvement scores during Stage 1.
Results
The first PC (PC1) was similar across treatment groups at stages 1 and 2, suggesting a shared pattern of symptom improvement. PC1 patients’ scores significantly differed according to treatment, whereas no difference in response was evidenced between groups with the Clinical Global Impressions Scale. Baseline GBC correlated with Stage 1 PC1 scores in the sertraline but not in the placebo group.
Using data-driven reduction of symptom scales, we identified a common profile of symptom improvement with distinct intensity between sertraline and placebo.
Conclusions
Mapping from data-driven symptom improvement onto neural circuits revealed treatment-responsive neural profiles that may aid in optimal patient selection for future trials.
The development of childcare policy can be understood as a process shaped by conflicts across multiple, interconnected dimensions of policymaking. Whilst existing literature often emphasises tensions between established policy legacies and emerging paradigms such as work–family reconciliation and social investment, this study introduces a multi-dimensional framework that includes conflict and negotiation processes between competing policies co-existing within the policy domain but also within policies themselves, emphasising the dynamics of self-reinforcing and self-undermining feedbacks. Our analysis reveals how efforts to resolve tensions in one policy dimension can inadvertently trigger new conflicts in other dimensions. By examining the South Korean case over three decades, we demonstrate how such interwoven tensions drive long-term policy change, offering scholars a more nuanced understanding of the complex mechanisms underlying policy evolution.
Cavitation bubble pulsation and liquid jet loads are the main causes of hydraulic machinery erosion. Methods to weaken the load influences have always been hot topics of related research. In this work, a method of attaching a viscous layer to a rigid wall is investigated in order to reduce cavitation pulsations and liquid jet loads, using both numerical simulations and experiments. A multiphase flow model incorporating viscous effects has been developed using the Eulerian finite element method (EFEM), and experimental methods of a laser-induced bubble near the viscous layer attached on a rigid wall have been carefully designed. The effects of the initial bubble–wall distance, the thickness of the viscous layer, and the viscosity on bubble pulsation, migration and wall pressure load are investigated. The results show that the bubble migration distance, the normalised thickness of the oil layer and the wall load generally decrease with the initial bubble–wall distance or the oil-layer parameters. Quantitative analysis reveals that when the initial bubble–wall distance remains unchanged, there exists a demarcation line for the comparison of the bubble period and the reference period (the bubble period without viscous layer under the same initial bubble–wall distance), and a logarithmic relationship is observed that $\delta \propto \log_{10} \mu ^*$, where $\delta =h/R_{max}$ is the thickness of the viscous layer h normalised by the maximum bubble radius $R_{max}$, $\mu ^* = \mu /({R_{max }}\sqrt {{\rho }{{\mathop {P}\nolimits } _{{atm}}}})$ is the dynamic viscosity $\mu$ normalised by water density $ \rho $ and atmospheric pressure $P_{atm}$. The results of this paper can provide technical support for related studies of hydraulic cavitation erosion.
Loneliness and social isolation pose significant public health concerns globally, with adverse effects on mental health and well-being. Although the terms are often used interchangeably, loneliness refers to the subjective feeling of lacking social connections, whereas social isolation is the objective absence of social support or networks.
Aims
To investigate the prevalence of loneliness and social isolation and their associations with psychiatric disorders.
Method
This study used data from the Republic of Korea National Mental Health Survey 2021, a nationally representative survey. A total of 5511 adults aged 18–79 residing in South Korea participated in the survey. Loneliness and social isolation were assessed using the Loneliness and Social Isolation Scale, whereas psychiatric disorders were evaluated using the Korean version of the Composite International Diagnostic Interview. Multivariate logistic regressions were performed after adjustment for sociodemographic variables.
Results
Among the participants, 11.8% reported experiencing loneliness, 4.3% reported social isolation and 3.4% reported both. Co-occurrence of loneliness and social isolation was significantly associated with psychiatric disorders (adjusted odds ratio (AOR) 7.59, 95% CI: 5.48–10.52). Loneliness alone was associated with greater prevalence and higher probability of psychiatric disorders (AOR 3.12, 95% CI: 2.63–3.71), whereas social isolation did not show any significant association (AOR 0.88, 95% CI: 0.64–1.22).
Conclusion
The co-occurrence of loneliness and social isolation is particularly detrimental to mental health. This finding emphasises the need for targeted interventions to promote social connection and reduce feelings of isolation.
Researchers interested in dyadic processes increasingly collect intensive longitudinal data (ILD), with the longitudinal actor–partner interdependence model (L-APIM) being a popular modeling approach. However, due to non-compliance and the use of conditional questions, ILD are almost always incomplete. These missing data issues become more prominent in dyadic studies, because partners often miss different measurement occasions or disagree about features that trigger conditional questions. Large amounts of missing data challenge the L-APIM’s estimation performance. Specifically, we found that non-convergence occurred when applying the L-APIM to pre-existing dyadic diary data with a lot of missing values. Using a simulation study, we systematically examined the performance of the L-APIM in dyadic ILD with missing values. Consistent with our illustrative data, we found that non-convergence often occurred in conditions with small sample sizes, while the fixed within-person actor and partner effects were well estimated when analyses did converge. Additionally, considering potential convergence failures with the L-APIM, we investigated 31 alternative models and evaluated their performance on simulated and empirical data, showing that multiple alternatives may alleviate the convergence problems. Overall, when the L-APIM fails to converge, we recommend fitting multiple alternative models to check the robustness of the results.
Readability assessment has been a key research area for the past 80 years, and still attracts researchers today. The most common measures currently (2011) in use are Flesch-Kincaid and Dale-Chall. Traditional models were parsimonious, incorporating as few linguistic features as possible, and used linear regression to combine two or three surface features. Later models used psychological theory, measuring such things as coherence, density, and inference load. A variety of machine learning models were used and one neural network. Key surface linguistic features were average syllables per word and sentence length. The Machine Learning methods performed well. Machine Learning methods can improve readability estimation. The process is data-driven, requiring less manual labour, and avoiding human bias. Current research seems to focus on deep learning methods, which show great promise.
In this chapter, new computational models will focus on whether environmental health texts are suitable for parents rather than the general public. Logistic regression models will identify linguistic features that are important contributors to the prediction of the suitability of environmental health materials for parents and caregivers of young children, who are more likely to be affected by environmental health risks such as water pollution, excessive sun exposure, and radiation in natural and indoor environments.