Posttraumatic stress disorder (PTSD) is a heterogenous disorder with frequent diagnostic comorbidity. Research has deciphered this heterogeneity by identifying PTSD subtypes and their neural biomarkers. This review summarizes current approaches, symptom-based group-level and data-driven approaches, for generating PTSD subtypes, providing an overview of current PTSD subtypes and their neural correlates. Additionally, we systematically assessed studies to evaluate the influence of comorbidity on PTSD subtypes and the predictive utility of biotypes for treatment outcomes. Following the PRISMA guidelines, a systematic search was conducted to identify studies employing brain imaging techniques, including functional magnetic resonance imaging (fMRI), structural MRI, diffusion-weighted imaging (DWI), and electroencephalogram (EEG), to identify biomarkers of PTSD subtypes. Study quality was assessed using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. We included 53 studies, with 44 studies using a symptom-based group-level approach, and nine studies using a data-driven approach. Findings suggest biomarkers across the default-mode network (DMN) and the salience network (SN) throughout multiple subtypes. However, only six studies considered comorbidity, and four studies tested the utility of biotypes in predicting treatment outcomes. These findings highlight the complexity of PTSD’s heterogeneity. Although symptom-based and data-driven methods have advanced our understanding of PTSD subtypes, challenges remain in addressing the impact of comorbidities and the limited validation of biotypes. Future studies with larger sample sizes, brain-based data-driven approaches, careful account for comorbidity, and rigorous validation strategies are needed to advance biologically grounded biotypes across mental disorders.

Adolescents who experience bereavement following suicide are at increased risk for adverse outcomes, including depression. However, there is limited research on the heterogeneity of depressive symptoms or its long-term course among this population. Using a self-reported 3-item version of the Center for Epidemiologic Studies Depression Scale (CES-D) administered across five waves spanning from adolescence to adulthood (1994–2018, with intervals of 1, 5, 7, and 9 years), we identified trajectories of depressive symptoms over a 24-year span in a sample of adolescents (n = 236) who reported at baseline having lost a family member or friend to suicide in the last 12 months. We identified three distinct depressive symptom trajectories: Stable low symptoms (77.5%), initially high but gradually declining symptoms (16.9%), and initially low but gradually increasing symptoms (5.5%). Race, neuroticism, sleep quality, and age were significant predictors that differentiated membership among the three trajectory groups. Implications for developing personalized assessment and intervention are discussed.

Wall turbulence consists of various sizes of vortical structures that induce flow circulation around a wide range of closed Eulerian loops. Here we investigate the multiscale properties of circulation around such loops in statistically homogeneous planes parallel to the wall. Using a high-resolution direct numerical simulation database of turbulent channels at Reynolds numbers of $Re_\tau =180$, 550, 1000 and 5200, circulation statistics are obtained in planes at different wall-normal heights. Intermittency of circulation in the planes of the outer flow ($y^+ \gtrsim 0.1Re_\tau$) takes the form of universal bifractality as in homogeneous and isotropic turbulence. The bifractal character simplifies to space-filling character close to the wall, with scaling exponents that are linear in the moment order, and lower than those given by the Kolmogorov paradigm. The probability density functions of circulation are long-tailed in the outer bifractal region, with evidence showing their invariance with respect to the loop aspect ratio, while those in the inner region are closely Gaussian. The unifractality near the wall implies that the circulation there is not intermittent in character.

Hand, foot, and mouth disease (HFMD) shows spatiotemporal heterogeneity in China. A spatiotemporal filtering model was constructed and applied to HFMD data to explore the underlying spatiotemporal structure of the disease and determine the impact of different spatiotemporal weight matrices on the results. HFMD cases and covariate data in East China were collected between 2009 and 2015. The different spatiotemporal weight matrices formed by Rook, K-nearest neighbour (KNN; K = 1), distance, and second-order spatial weight matrices (SO-SWM) with first-order temporal weight matrices in contemporaneous and lagged forms were decomposed, and spatiotemporal filtering model was constructed by selecting eigenvectors according to MC and the AIC. We used MI, standard deviation of the regression coefficients, and five indices (AIC, BIC, DIC, R2, and MSE) to compare the spatiotemporal filtering model with a Bayesian spatiotemporal model. The eigenvectors effectively removed spatial correlation in the model residuals (Moran’s I < 0.2, p > 0.05). The Bayesian spatiotemporal model’s Rook weight matrix outperformed others. The spatiotemporal filtering model with SO-SWM was superior, as shown by lower AIC (92,029.60), BIC (92,681.20), and MSE (418,022.7) values, and higher R2 (0.56) value. All spatiotemporal contemporaneous structures outperformed the lagged structures. Additionally, eigenvector maps from the Rook and SO-SWM closely resembled incidence patterns of HFMD.

Spatial optimal responses to both inlet disturbances and harmonic external forcing for hypersonic flows over a blunt cone at non-zero angles of attack are obtained by efficiently solving the direct–adjoint equations with a parabolic approach. In either case, the most amplified disturbances initially take the form of localised streamwise vortices on the windward side and will undergo a two-stage evolution process when propagating downstream: they first experience a substantial algebraic growth by exploiting the Orr and lift-up mechanisms, and then smoothly transition to a quasi-exponential growth stage driven by the crossflow-instability mechanism, accompanied by an azimuthal advection of the disturbance structure towards the leeward side. The algebraic growth phase is most receptive to the external forcing, whereas the exponential growth stage relies on the disturbance frequency and can be significantly strengthened by increasing the angle of attack. The wavemaker delineating the structural sensitivity region for the optimal gain is shown to lie on the windward side immediately downstream of the inlet, implying a potent control strategy. Additionally, considerable non-modal growth is also observed for broadband high-frequency disturbances residing in the entropy layer.

Recent experiments and simulations have sparked growing interest in the study of Rayleigh–Bénard convection in very slender cells. One pivotal inquiry arising from this interest is the elucidation of the flow structure within these very slender cells. Here we employ tomographic particle image velocimetry, for the first time, to capture experimentally the full-field three-dimensional and three-component velocity field in a very slender cylindrical cell with aspect ratio $\Gamma =1/10$. The experiments cover a Rayleigh number range $5.0 \times 10^8 \leqslant Ra \leqslant 5.0 \times 10^9$ and Prandtl number 5.7. Our experiments reveal that the flow structure in the $\Gamma =1/10$ cell is neither in the multiple-roll form nor in the simple helical form; instead, the ascending and descending flows can intersect and cross each other, resulting in the crossing events. These crossing events separate the flow into segments; within each segment, the ascending and descending flows ascend or descend side by side vertically or in the twisting manner, and the twisting is not unidirectional, while the segments near the boundary can also be in the form of a donut like structure. By applying the mode decomposition analyses to the measured three-dimensional velocity fields, we identified the crossing events as well as the twisting events for each instantaneous flow field. Statistical analysis of the modes reveals that as $Ra$ increases, the average length of the segments becomes smaller, and the average number of segments increases from 2.5 to 3.9 in the $Ra$ range of our experiments.

River terraces serve as excellent indicators of the landform evolution of the Guizhou Plateau. This paper presents the results of terrace investigation and optically stimulated luminescence (OSL) dating focused on five sections along the Liujiang River of the southeastern Guizhou Plateau. The OSL ages of the terraces range from 0.21 ± 0.02 to 16.0 ± 1.4 ka for the first terraces (T1) and from 3.5 ± 0.3 to 26.5 ± 3.3 ka for the second terraces (T2), which are much younger than those of other basins on the Guizhou Plateau. These ages, considered in tandem with the results of previous investigations, enhance our understanding of the fluvial landform evolution of the Guizhou Plateau since the Late Pleistocene. On the Guizhou Plateau platform, terraces are considered to be the response of river evolution to tectonic uplift, indicating a relatively slow geomorphic process. In the slope zone, climate change has had a significant impact on the fluvial landform processes, driving the formation of the younger terraces along the Liujiang River. In the platform–slope transition zone, the evolution of terraces was driven by both tectonic uplift and climate change, where the landform processes were dominated by strong headward erosion.

Research findings based on the data of current automatic identification systems (AISs) can only be applied to some parts of navigation research owing to their insufficient mining depth. Previously, route planning research has been based on the waypoint and corresponding optimised algorithm without considering the actual navigation situation and sailing habits. The planned route considerably differs from the actual sailing route, and the application result is undesirable. A novel solution to support the route planning problem has been introduced owing to the large accumulation of AIS big data. In this study, the ship navigable route framework (SNRF) which is reflected by real data via mining AIS big data serves as the basic network for the planned maritime route. This study uses the concept of manifold distance based on AIS big data to build a maritime SNRF through high-density searching. It can provide basic theoretical support for actual navigation distance calculation, route planning and route accessibility inspection in the future.

The Arabic development of Syrian refugee children (N = 133; mean age = 9;4 at Time 1) was examined over 3 time periods during their first five years in Canada. Children were administered sentence repetition and receptive vocabulary tasks in English and Arabic, and information about age-of-arrival (AOA), schooling in Arabic and language environment factors was obtained via parent report. Older AOA was associated with superior Arabic abilities across time, but regardless of AOA, children showed plateau/attrition patterns in Arabic and shifts to English dominance by Time 3. Increases in English over Arabic were observed for language use at home and language-rich activities overtime. Stronger Arabic Time 3 outcomes were predicted by more Arabic and less English use with siblings, more schooling in Arabic, more frequent listening-speaking and extra-curricular activities in Arabic, and more Arabic use with friends. We conclude that the heritage language can be vulnerable even for first-generation bilinguals.

Glaciers play a crucial role in the Asian Water Tower, underscoring the necessity of accurately assessing their mass balance and ice volume to evaluate their significance as sustainable freshwater resources. In this study, we analyzed ground-penetrating radar (GPR) measurements from a 2020 survey of the Xiao Dongkemadi Glacier (XDG) to determine ice thickness, and we extended the glacier’s volume-change record to 2020 by employing multi-source remote-sensing data. Our findings show that the GPR-derived mean ice thickness of XDG in 2020 was 54.78 ± 3.69 m, corresponding to an ice volume of 0.0811 ± 0.0056 km3. From 1969 to 2020, the geodetic mass balance was −0.19 ± 0.02 m w.e. a−1, and the glacier experienced area and ice volume losses of 16.38 ± 4.66% and 31.01 ± 4.59%, respectively. The long-term mass-balance reconstruction reveals weak fluctuations occurred from 1967 to 1993 and that overall mass losses have occurred since 1994. This ongoing shrinkage and ice loss are mainly associated with the temperature increases in the warm season since the 1960s. If the climate trend across the central Tibetan Plateau follows to the SSP585 scenario, then XDG is at risk of disappearing by the end of the century.

This work investigates the spatio-temporal evolution of coherent structures in the wake of a generic high-speed train, based on a three-dimensional database from large eddy simulation. Spectral proper orthogonal decomposition (SPOD) is used to extract energy spectra and energy ranked empirical modes for both symmetric and antisymmetric components of the fluctuating flow field. The spectrum of the symmetric component shows overall higher energy and more pronounced low-rank behaviour compared with the antisymmetric one. The most dominant symmetric mode features periodic vortex shedding in the near wake, and wave-like structures with constant streamwise wavenumber in the far wake. The mode bispectrum further reveals the dominant role of self-interaction of the symmetric component, leading to first harmonic and subharmonic triads of the fundamental frequency, with remarkable deformation of the mean field. Then, the stability of the three-dimensional wake flow is analysed based on two-dimensional local linear stability analysis combined with a non-parallelism approximation approach. Temporal stability analysis is first performed for both the near-wake and the far-wake regions, showing a more unstable condition in the near-wake region. The absolute frequency of the near-wake eigenmode is determined based on spatio-temporal analysis, then tracked along the streamwise direction to find out the global mode growth rate and frequency, which indicate a marginally stable global mode oscillating at a frequency very close to the most dominant SPOD mode. The global mode wavemaker is then located, and the structural sensitivity is calculated based on the direct and adjoint modes derived from a local spatial analysis, with the maximum value localized within the recirculation region close to the train tail. Finally, the global mode shape is computed by tracking the most spatially unstable eigenmode in the far wake, and the alignment with the SPOD mode is computed as a function of streamwise location. By combining data-driven and theoretical approaches, the mechanisms of coherent structures in complex wake flows are well identified and isolated.