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This paper addresses the attitude control challenge of hypersonic morphing vehicles (HMVs) with uncertainties and actuator saturation. The primary contribution of this work lies in achieving a predefined settling time while ensuring robust control performance under morphing effects, actuator saturation and disturbances. Firstly, a control-oriented model is established based on the dynamics of HMVs. Subsequently, a nonsingular multivariable sliding mode manifold, utilising a switching function, is designed to attain predefined-time convergence and prevent singularity issues. A disturbance observer with an adaptive law is developed to precisely and swiftly estimate uncertainties and error states, while a predefined-time anti-saturation compensator is implemented to alleviate actuator saturation. Furthermore, closed-loop stability is guaranteed through rigorous Lyapunov synthesis. Extensive numerical simulations confirm the algorithm’s superiority in terms of control effectiveness.
Fine particulate matter (PM2.5) exposure and unfavourable lifestyle are both significant risk factors for mental health disorders, yet their combined effects on adolescent depression and anxiety remain poorly understood. This study aims to determine whether PM2.5 exposure and lifestyle are independently associated with adolescent depression and anxiety, and whether there are joint effects between these factors on mental health outcomes.
Methods
In this cross-sectional study, 19852 participants were analysed. PM2.5 concentrations were obtained from the ChinaHighAirPollutants (CHAP) dataset. Lifestyle factors were assessed through self-reported questionnaires, and a healthy lifestyle score was developed based on eight lifestyle risk factors. Depression and anxiety were assessed using the PHQ-9 and GAD-7 scales. Restricted cubic spline analysed dose–response relationships between PM2.5 exposure and mental health outcomes. The independent and joint effects were assessed using logistic regression models. Both multiplicative and additive interactions (relative excess risk due to interaction, RERI) were examined. Multiple classification approaches were incorporated to ensure robust results.
Results
The study included 19852 participants with a mean age of 15.16 years (SD 1.60), comprising 9886 (49.8%) males and 9966 (50.2%) females. Depression and anxiety were identified in 3845 (19.37%) and 3230 (16.27%) participants, respectively. PM2.5 exposure showed a linear dose-response relationship with depression and anxiety. Joint effects analysis at the 75th percentile of PM2.5 with a lifestyle risk score of 4 revealed the strongest associations, with adjusted odds ratios of 4.49 (95% CI: 3.79–5.33) for depression, 4.01 (95% CI: 3.36–4.78) for anxiety and 4.24 (95% CI: 3.52–5.10) for their comorbidity. Simultaneously, significant additive interactions (RERI > 0) between high levels of PM2.5 exposure and unfavourable lifestyle factors were detected, suggesting synergistic effects on mental health outcomes. Subgroup and sensitivity analyses confirmed the robustness of these findings.
Conclusions
High PM2.5 exposure and unfavourable lifestyle factors demonstrated significant independent and joint effects on depression and anxiety among adolescents. These findings highlight that implementing stringent air pollution control measures, combined with promoting healthy lifestyle practices, may be crucial for protecting adolescent mental health.
For a planar analytic Hamiltonian system, which has a period annulus limited by a nilpotent center and a homoclinic loop to a nilpotent singularity, we study its analytic perturbation to obtain the number of limit cycles bifurcated from the periodic orbits inside the period annulus. By characterizing the coefficients and their properties of the high-order terms in the expansion of the first-order Melnikov function near the loop, we provide a new way to find more limit cycles. Moreover, we apply these general results to concrete systems, for instance, an $(m+1)$th-order generalized Liénard system, and an mth-order near-Hamiltonian system with a hyperelliptic Hamiltonian of degree $6$.
The COVID-19 pandemic exacerbated psychological distress, but limited information is available on the shifts in mental health symptoms and their associated factors across different stages. This study was conducted to more reliably estimate shifts in mental health impacts and to identify factors associated with symptoms at different pandemic stages.
Methods
We performed a national repeated cross-sectional study at stable (2021), recurrence (2022), and end-of-emergency (2023) stages based on representative general national population with extensive geographic coverage. Anxiety, depression, post-traumatic stress disorder (PTSD) and insomnia symptoms were evaluated by GAD-7, PHQ-9, IES-R and ISI scales, respectively, and their associated factors were identified via multivariable linear regression.
Results
Generally, 42,000 individuals were recruited, and 36,218, 36,097 and 36,306 eligible participants were included at each stage. The prevalence of anxiety, depression and insomnia symptoms increased from 13.7–16.4% at stable to 17.3–22.2% at recurrence and decreased to 14.5–18.6% at end of emergency, while PTSD symptom continuously increased from 5.1% to 7.6% and 9.2%, respectively (all significant, P < 0.001). Common factors associated with mental health symptoms across all stages included centralized quarantine, frontline work and residence in initially widely infected areas. Centralized quarantine was linked to anxiety, depression, PTSD and insomnia during the stable, recurrence and end-of-emergency stages. Frontline workers exhibited higher risks of anxiety, depression and insomnia throughout these stages. Individuals in initially widely infected areas were more likely to experience depression and PTSD, particularly during the stable and recurrence stages. Stage-specific risk factors were also identified. Lack of outdoor activity was associated with anxiety, depression and insomnia during the stable and recurrence stages. Residents in high-risk areas during the recurrence stage correlated with increased anxiety and insomnia. Suspected infection was tied to anxiety and insomnia in the recurrence and end-of-emergency stages, while the death of family or friends was linked to PTSD during recurrence and to depression, PTSD and insomnia at the end-of-emergency stage.
Conclusions
Mental health symptoms increased when pandemic recurred, and could remain after end-of-emergency, requiring prolonged interventions. Several key factors associated with mental symptoms and their variations were identified at different pandemic stages, suggesting different at-risk populations.
This work proposes an optimization approach for the time-consuming parts of Light Detection and Ranging (LiDAR) data processing and IMU-LiDAR data fusion in the LiDAR-inertial odometry (LIO) method. Two key novelties enable faster and more accurate navigation in complex, noisy environments. Firstly, to improve map update and point cloud registration efficiency, we employ a sparse voxel maps with a new update function to construct a local map around the mobile robot and utilize an improved Generalized Iterative Closest Point algorithm based on sparse voxels to achieve LiDAR point clouds association, thereby boosting both map updating and computational speed. Secondly, to enhance real-time accuracy, this paper analyzes the residuals and covariances of both IMU and LiDAR data in a tightly coupled manner, and achieves system state estimation by fusing sensor information through Gauss-Newton method, effectively mitigating localization deviations by appropriately weighting the LiDAR covariances. The performance of our method is evaluated against advanced LIO algorithms using eight open datasets and five self-collected campus datasets. Results show a 24.7–60.1% reduction in average processing time per point cloud frame, along with improved robustness and higher precision motion trajectory estimation in most cluttered and complex indoor and outdoor environments.
Schizophrenia progresses through high-risk, first-episode, and chronic stages, each associated with altered spontaneous brain activity. Resting state functional MRI studies highlight these changes, but inconsistencies persist, and the genetic basis remains unclear.
Methods
A neuroimaging meta-analysis was conducted to assess spontaneous brain activity alterations in each schizophrenia stage. The largest available genome-wide association study (GWAS) summary statistics for schizophrenia (N = 53,386 cases, 77,258 controls) were used, followed by Hi-C-coupled multimarker analysis of genomic annotation (H-MAGMA) to identify schizophrenia-associated genes. Transcriptome-neuroimaging association and gene prioritization analyses were performed to identify genes consistently linked to brain activity alterations. Biological relevance was explored by functional enrichment.
Results
Fifty-two studies met the inclusion criteria, covering the high-risk (Nhigh-risk = 409, Ncontrol = 475), first-episode (Ncase = 1842, Ncontrol = 1735), and chronic (Ncase = 1242, Ncontrol = 1300) stages. High-risk stage showed reduced brain activity in the right median cingulate and paracingulate gyri. First-episode stage revealed increased activity in the right putamen and decreased activity in the left gyrus rectus and right postcentral gyrus. Chronic stage showed heightened activity in the right inferior frontal gyrus and reduced activity in the superior occipital gyrus and right postcentral gyrus. Across all stages, 199 genes were consistently linked to brain activity changes, involved in biological processes such as nervous system development, synaptic transmission, and synaptic plasticity.
Conclusions
Brain activity alterations across schizophrenia stages and genes consistently associated with these changes highlight their potential as universal biomarkers and therapeutic targets for schizophrenia.
Based on the characteristics of the variable pivot gait during the human load-carrying, this paper proposes a double-leg coordination assistance principle for load-carrying: assisting support of the guiding leg at the heel-pivot stage by the spring to reduce the collision, which can reduce the ankle moment of the following leg that is performing the push-off at the toe-pivot stage. A novel unpowered load-carrying exoskeleton (ULE) with a double-support closed-chain configuration is designed, and the theoretical verification is carried out. Five subjects participate in the load-carrying and metabolic cost experiments for assisting and energy-saving effect evaluation, and the angle and moment of human joints, plantar pressure, spring compression and human net metabolic rate are analyzed. Compared with carrying load by the human alone, wearing the novel ULE with spring reduces the human peak ankle moment performing the push-off by up to 11.9 ± 1.6% (Mean±SE, 10 kg), average ankle moment over the support phase by up to 36.8 ± 9.1% (Mean±SE, 5 kg) and the average vertical plantar pressure by up to 8.1 ± 1%% (Mean±SE, 15 kg). Meanwhile, wearing the novel ULE reduces the human net metabolic rate by 5.6 ± 0.5% (Mean±SE, 10 kg), 4.1 ± 0.7% (Mean±SE, 15 kg) and 5.9 ± 1.6% (Mean±SE, 20 kg). The results show that the novel ULE can provide support and joint moment assistance over the whole support phase while reducing human net metabolic rate. This study can also be applied to the powered load-carrying exoskeleton, providing a new avenue.
Antimicrobial resistance (AMR) is a global health crisis exacerbated by policies like China’s Volume-Based Procurement (VBP), which may inadvertently increase antimicrobial overuse. This study evaluates a clinical pharmacist-led Antimicrobial Stewardship (AMS) program with prospective audit for special-restricted antimicrobials under VBP.
Methods:
A retrospective quasi-experimental interrupted time-series analysis compared pre-intervention (2022) and post-intervention (2023–2024) data at Tongji Hospital, a tertiary hospital in Wuhan, China. Key metrics included Antimicrobial Use Density (AUD), prescription rationality, antimicrobial costs, and multidrug-resistant infection rates.
Results:
The intervention significantly improved prescription appropriateness for special-restricted antimicrobials (80.24% vs. 93.83%, P < 0.005) and reduced AUD (47.87 vs. 34.25, P < 0.001). Total antimicrobial costs decreased by 41.26%, with a reduction in the incidence of multidrug-resistant infections from 0.084% to 0.062% (P < 0.05). Carbapenem use correlated with CRKP isolation rates (R = 0.62, P < 0.05). Clinical pharmacists rejected 10.24% of prescriptions, all accepted by physicians.
Conclusion:
Pharmacist-led prospective audits optimize antimicrobial use under VBP, mitigate resistance risks, and reduce costs, while acknowledging that concurrent infection control measures may have contributed to these trends. This model may inform similar interventions in other institutions, particularly those in resource-limited settings.
Little is known regarding the shared genetic architecture underlying the phenotypic associations between depression and preterm birth (PTB). We aim to investigate the genetic overlap and causality of depression with PTB.
Methods
Leveraging summary statistics from the largest genome-wide association studies for broad depression (Ntotal = 807,533), major depression (Ntotal = 173,005), bipolar disorder (Ntotal = 414,466), and PTB (Ntotal = 226,330), we conducted a large-scale genome-wide cross-trait analysis to assess global and local genetic correlations, identify pleiotropic loci, and infer potential causal relationships
Results
Positive genetic correlations were observed between PTB and broad depression (rg = 0.242), major depression (rg = 0.236), and bipolar disorder (rg = 0.133) using the linkage disequilibrium score regression, which were further verified by the genetic covariance analyzer. Local genetic correlation was identified at chromosome 11q22.3 (harbors NCAM1-TTC12-ANKK1-DRD2) for PTB with depression. Cross-trait meta-analysis identified two loci shared between PTB and broad depression, two loci shared with major depression, and five loci shared with bipolar disorder, among which three were novel (rs7813444, rs3132948 and rs9273363). Mendelian randomization demonstrated a significantly increased risk of PTB for genetic liability to broad depression (odds ratio [OR]=1.30; 95% confidence interval [CI]: 1.11-1.52) and major depression (OR=1.27; 95%CI: 1.08-1.49), and the estimates remained significant across the sensitivity analyses.
Conclusions
Our findings demonstrate an intrinsic link underlying depression and PTB and shed novel light on the biological mechanisms, highlighting an important role of early screening and effective intervention of depression in PTB prevention, and may provide novel treatment strategies for both diseases.
To explore the longitudinal associations between a Chinese healthy diet and the progression of cardiometabolic multimorbidity (CMM) development among Chinese adults. A prospective analysis was conducted utilising data from 18 720 participants in the China Health and Nutrition Survey, spanning from 1997 to 2018. Dietary data were collected by three consecutive 24-h dietary recalls combined with the weighing method. A Chinese healthy diet score was developed by assigning scores to various food components. CMM was defined as the coexistence of two or more cardiometabolic diseases (CMD), including myocardial infarction, stroke and type 2 diabetes, diagnosed through blood indicators and clinical diagnosis. We employed a multistate model to examine the associations between the Chinese healthy diet and the longitudinal progression from being free of CMD to first CMD and then to CMM. Quantile G-computation was utilised to evaluate the relative contribution of each food component. Over a median follow-up period of 7·3 years, 2214 (11·8 %) participants developed first CMD, and 156 (0·83 %) progressed to CMM. Comparing participants in the highest quintile of dietary scores with those in the lowest, we observed a 55 % lower risk of transitioning from baseline to CMM (HR = 0·45, 95 % CI: 0·23, 0·87) and a 60 % lower risk of transition from first CMD to CMM (HR = 0·40, 95 % CI: 0·20, 0·81). Fresh fruits contributed to 42·8 and 43·0 % for delaying CMM and transition from first CMD to CMM, respectively. Our study revealed that greater adherence to the Chinese healthy diet is negatively associated with the risk of CMM.
MicroRNAs (miRNAs) alterations in patients with bipolar disorder (BD) are pivotal to the disease’s pathogenesis. Since obtaining brain tissue is challenging, most research has shifted to analyzing miRNAs in peripheral blood. One innovative solution is sequencing miRNAs in plasma extracellular vesicles (EVs), particularly those neural-derived EVs emanating from the brain.
Methods
We isolated plasma neural-derived EVs from 85 patients with BD and 39 healthy controls (HC) using biotinylated antibodies targeting a neural tissue marker, followed by miRNA sequencing and expression analysis. Furthermore, we conducted bioinformatic analyses and functional experiments to delve deeper into the underlying pathological mechanisms of BD.
Results
Out of the 2,656 neural-derived miRNAs in EVs identified, 14 were differentially expressed between BD patients and HC. Moreover, the target genes of miR-143-3p displayed distinct expression patterns in the prefrontal cortex of BD patients versus HC, as sourced from the PsychENCODE database. The functional experiments demonstrated that the abnormal expression of miR-143-3p promoted the proliferation and activation of microglia and upregulated the expression of proinflammatory factors, including IL-1β, IL-6, and NLRP3. Through weighted gene co-expression network analysis, a module linking to the clinical symptoms of BD patients was discerned. Enrichment analyses unveiled these miRNAs’ role in modulating the axon guidance, the Ras signaling pathway, and ErbB signaling pathway.
Conclusions
Our findings provide the first evidence of dysregulated plasma miRNAs within neural-derived EVs in BD patients and suggest that neural-derived EVs might be involved in the pathophysiology of BD through related biological pathways, such as neurogenesis and neuroinflammation.
Social determinants of health (SDHs) exert a significant influence on various health outcomes and disparities. This study aimed to explore the associations between combined SDHs and mortality, as well as adverse health outcomes among adults with depression.
Methods
The research included 48,897 participants with depression from the UK Biobank and 7,771 from the US National Health and Nutrition Examination Survey (NHANES). By calculating combined SDH scores based on 14 SDHs in the UK Biobank and 9 in the US NHANES, participants were categorized into favourable, medium and unfavourable SDH groups through tertiles. Cox regression models were used to evaluate the impact of combined SDHs on mortality (all-cause, cardiovascular disease [CVD] and cancer) in both cohorts, as well as incidences of CVD, cancer and dementia in the UK Biobank.
Results
In the fully adjusted models, compared to the favourable SDH group, the hazard ratios for all-cause mortality were 1.81 (95% CI: 1.60–2.04) in the unfavourable SDH group in the UK Biobank cohort; 1.61 (95% CI: 1.31–1.98) in the medium SDH group and 2.19 (95% CI: 1.78–2.68) in the unfavourable SDH group in the US NHANES cohort. Moreover, higher levels of unfavourable SDHs were associated with increased mortality risk from CVD and cancer. Regarding disease incidence, they were significantly linked to higher incidences of CVD and dementia but not cancer in the UK Biobank.
Conclusions
Combined unfavourable SDHs were associated with elevated risks of mortality and adverse health outcomes among adults with depression, which suggested that assessing the combined impact of SDHs could serve as a key strategy in preventing and managing depression, ultimately helping to reduce the burden of disease.
While deplatforming has become an increasingly common strategy to combat online harm and far-right extremism, its effects on the followers of extremist groups—who are key supporters and play a crucial role in spreading and sustaining these ideologies—remain underexplored. On August 10, 2018, Twitter (now X) deplatformed one such far-right extremist group, the Proud Boys, along with their affiliated accounts. Leveraging this intervention, our research addresses a key knowledge gap by examining the impact of deplatforming on the cohesion of extremist group followers. Specifically, we investigate whether deplatforming leads to fragmentation or reinforces unity among the group’s followers. We assess cohesion through three theoretical lenses: task commitment, social commitment, and sense of belonging. By analyzing over 12 million tweets from approximately nine thousand Proud Boys supporters between August 1, 2017, and September 1, 2019, we find that deplatforming had a limited effect on reducing group cohesion. Instead, it may have prompted followers to seek broader networks and external interactions, leaving overall cohesion largely intact. This study offers important insights into the resilience of online extremist communities and the limitations of deplatforming as a strategy to disrupt them. Understanding these dynamics is essential for developing more effective approaches to counter online extremism and promote safer digital spaces.
Several million years of natural evolution have endowed marine animals with high flexibility and mobility. A key factor in this achievement is their ability to modulate stiffness during swimming. However, an unresolved puzzle remains regarding how muscles modulate stiffness, and the implications of this capability for achieving high swimming efficiency. Inspired by this, we proposed a self-propulsor model that employs a parabolic stiffness-tuning strategy, emulating the muscle tensioning observed in biological counterparts. Furthermore, efforts have been directed towards developing the nonlinear vortex sheet method, specifically designed to address nonlinear fluid–structure coupling problems. This work aims to analyse how and why nonlinear tunable stiffness influences swimming performance. Numerical results demonstrate that swimmers with nonlinear tunable stiffness can double their speed and efficiency across nearly the entire frequency range. Additionally, our findings reveal that high-efficiency biomimetic propulsion originates from snap-through instability, which facilitates the emergence of quasi-quadrilateral swimming patterns and enhances vortex strength. Moreover, this study examines the influence of nonlinear stiffness on swimming performance, providing valuable insights into the optimisation of next-generation, high-performance, fish-inspired robotic systems.
Kinematically redundant parallel mechanisms (PMs) have attracted extensive attention from researchers due to their advantages in avoiding singular configurations and expanding the reachable workspace. However, kinematic redundancy introduces multiple inverse kinematics solutions, leading to uncertainty in the mechanism’s motion state. Therefore, this article proposes a method to optimize the inverse kinematics solutions based on motion/force transmission performance. By dividing the kinematically redundant PM into hierarchical levels and decomposing the redundancy, the transmission wrench screw systems of general redundant limbs and closed-loop redundant limbs are obtained. Then, input, output, and local transmission indices are calculated, respectively, to evaluate the motion/force transmission performance of such mechanisms. To address the problem of multiple inverse kinematics solutions, the local optimal transmission index is employed as a criterion to select the optimal motion/force transmission solution corresponding to a specific pose of the moving platform. By comparing performance atlas before and after optimization, it is demonstrated that the optimized inverse kinematics solutions enlarge the reachable workspace and significantly improve the motion/force transmission performance of the mechanism.
Weeds significantly reduce sugarcane (Saccharum officinarum L.) production by 30% to 50% and cause complete crop loss in severe cases. Guangxi, a central sugarcane-growing region in southern China, faces significant challenges due to the proliferation of weeds severely impacting crop tillering, yield, and quality. In this study, we surveyed and identified 35 weed species belonging to 16 families in Longzhou, Nongqin, and Qufeng, with significant threats posed by purple nutsedge (Cyperus rotundus L.), bermudagrass [Cynodon dactylon (L.) Pers.], hairy crabgrass [Digitaria sanguinalis (L.) Scop.], black nightshade (Solanum nigrum L.), white-edge morningglory [Ipomoea nil (L.) Roth], and ivy woodrose [Merremia hederacea (Burm. f.) Hallier f.]. The application of 81% MCPA-ametryn-diuron achieved greater than 90% control within 15 d. Although herbicides are effective, they can unintentionally harm sugarcane, indicating a need for tolerant genotypes. Therefore, we comprehensively evaluated herbicide-induced phytotoxic responses and identified tolerant sugarcane genotypes over 3 yr of trials conducted on 222 genotypes across Guangxi. We quantified phytotoxicity by counting the number and severity of affected leaves. The ANOVA revealed statistically significant main and interaction effects among genotype, crop cycle, and location. Cluster and discriminant analyses classified the genotypes into five groups: 21 highly tolerant (HT), 68 tolerant, 75 moderately tolerant, 18 susceptible, and 40 highly susceptible. The 21 HT genotypes demonstrated strong potential to be used as parental lines for breeding herbicide-tolerant varieties, to inform precision breeding strategies, and to increase tolerance to herbicide stress in sugarcane.