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The variable stator vanes (VSV) are a set of typical spatial linkage mechanisms widely used in the variable cycle engine compressor. Various factors influence the angle adjustment precision of the VSV, leading to the failure of the mechanism. The reliability analysis of VSV is a complex task due to the involvement of multiple components, high dimensionality input and computational inefficiency. Considering the hierarchical characteristics of VSV structure, we propose a novel multi-layer Kriging surrogate (MLKG) for the reliability analysis of VSV. The MLKG combines multiple Kriging surrogate models arranged in a hierarchical structure. By breaking the problem down into more minor problems, MLKG works by presenting each small problem as a Kriging model and reducing the input dimension of the sub-layer Kriging model. In this way, the MLKG can capture the complex interactions between the inputs and outputs of the problem while maintaining a high degree of accuracy and efficiency. This study proves the error propagation process of MLKG. To evaluate MLKG’s accuracy, we test it on two typical high-dimensional non-linearity functions (Rosenbrock and Michalewicz function). We compared MLKG with some contemporary KG surrogate modeling techniques using mean squared error (MSE) and R square (${R^2}$). Results show that MLKG achieves an excellent level of accuracy for reliability analysis in high-dimensional problems with a small number of sample points.
Bird strike accidents are critical threats for aviation safety especially in airport airspaces. Environment friendly solutions are preferred for wildlife managements to achieve harmonic coexistence between airports and surrounding environments. Avian radar systems are the most effective remote sensing approach for long-range and all-weather birds monitoring. Massive historical avian radar datasets and other data sources provide an opportunity to explore relevance between bird behaviour and environments. This paper proposes a bird behaviour characterisation and prediction method to reveal bird behaviour dependency with weather parameters. Bird behaviours are modelled as indices and grades from selected avian radar datasets. Weather dependence are studied from single parameter to multivariable parameters. The random forest model is selected as a behaviour grade prediction model taking four weather parameters as system inputs. Radar datasets for diurnal and nocturnal birds are constructed to validate their behaviour characters and prediction performance, respectively. Experiment results verify the feasibility of bird behaviour prediction using weather parameters, but also reflect some insufficiencies within the proposed method. Data sufficiency and severe weather considerations are also discussed to analyse their impact on prediction accuracy. A more comprehensive prediction model with standardised avian radar data quality and enhanced weather information accuracy is promising to further elevate the application significance of the proposed method.
Adolescence is a period marked by highest vulnerability to the onset of depression, with profound implications for adult health. Neuroimaging studies have revealed considerable atrophy in brain structure in these patients with depression. Of particular importance are regions responsible for cognitive control, reward, and self-referential processing. However, the causal structural networks underpinning brain region atrophies in adolescents with depression remain unclear.
Objectives
This study aimed to investigate the temporal course and causal relationships of gray matter atrophy within the brains of adolescents with depression.
Methods
We analyzed T1-weighted structural images using voxel-based morphometry in first-episode adolescent patients with depression (n=80, 22 males; age = 15.57±1.78) and age, gender matched healthy controls (n=82, 25 males; age = 16.11±2.76) to identify the disease stage-specific gray matter abnormalities. Then, with granger causality analysis, we arranged the patients’ illness duration chronologically to construct the causal structural covariance networks that investigated the causal relationships of those atypical structures.
Results
Compared to controls, smaller volumes in ventral medial prefrontal cortex (vmPFC), dorsal anterior cingulate cortex (dACC), middle cingulate cortex (MCC) and insula areas were identified in patients with less than 1 year illness duration, and further progressed to the subgenual ACC, regions of default, frontoparietal networks in longer duration. Causal network results revealed that dACC, vmPFC, MCC and insula were prominent nodes projecting exerted positive causal effects to regions of the default mode and frontoparietal networks. The dACC, vmPFC and insula also had positive projections to the reward network, which included mainly the thalamus, caudate and putamen, while MCC also exerted a positive causal effect on the insula and thalamus.
Conclusions
These findings revealed the progression of structural atrophy in adolescent patients with depression and demonstrated the causal relationships between regions involving cognitive control, reward and self-referential processes.
Syphilis remains a serious public health problem in mainland China that requires attention, modelling to describe and predict its prevalence patterns can help the government to develop more scientific interventions. The seasonal autoregressive integrated moving average (SARIMA) model, long short-term memory network (LSTM) model, hybrid SARIMA-LSTM model, and hybrid SARIMA-nonlinear auto-regressive models with exogenous inputs (SARIMA-NARX) model were used to simulate the time series data of the syphilis incidence from January 2004 to November 2023 respectively. Compared to the SARIMA, LSTM, and SARIMA-LSTM models, the median absolute deviation (MAD) value of the SARIMA-NARX model decreases by 352.69%, 4.98%, and 3.73%, respectively. The mean absolute percentage error (MAPE) value decreases by 73.7%, 23.46%, and 13.06%, respectively. The root mean square error (RMSE) value decreases by 68.02%, 26.68%, and 23.78%, respectively. The mean absolute error (MAE) value decreases by 70.90%, 23.00%, and 21.80%, respectively. The hybrid SARIMA-NARX and SARIMA-LSTM methods predict syphilis cases more accurately than the basic SARIMA and LSTM methods, so that can be used for governments to develop long-term syphilis prevention and control programs. In addition, the predicted cases still maintain a fairly high level of incidence, so there is an urgent need to develop more comprehensive prevention strategies.
Inhibitory control plays an important role in children’s cognitive and socioemotional development, including their psychopathology. It has been established that contextual factors such as socioeconomic status (SES) and parents’ psychopathology are associated with children’s inhibitory control. However, the relations between the neural correlates of inhibitory control and contextual factors have been rarely examined in longitudinal studies. In the present study, we used both event-related potential (ERP) components and time-frequency measures of inhibitory control to evaluate the neural pathways between contextual factors, including prenatal SES and maternal psychopathology, and children’s behavioral and emotional problems in a large sample of children (N = 560; 51.75% females; Mage = 7.13 years; Rangeage = 4–11 years). Results showed that theta power, which was positively predicted by prenatal SES and was negatively related to children’s externalizing problems, mediated the longitudinal and negative relation between them. ERP amplitudes and latencies did not mediate the longitudinal association between prenatal risk factors (i.e., prenatal SES and maternal psychopathology) and children’s internalizing and externalizing problems. Our findings increase our understanding of the neural pathways linking early risk factors to children’s psychopathology.
With many non-human primates (NHPs) showing continued population decline, there is an ongoing need to better understand their ecology and conservation threats. One such threat is the risk of disease, with various bacterial, viral and parasitic infections previously reported to have damaging consequences for NHP hosts. Strongylid nematodes are one of the most commonly reported parasitic infections in NHPs. Current knowledge of NHP strongylid infections is restricted by their typical occurrence as mixed infections of multiple genera, which are indistinguishable through traditional microscopic approaches. Here, modern metagenomics approaches were applied for insight into the genetic diversity of strongylid infections in South-East and East Asian NHPs. We hypothesized that strongylid nematodes occur in mixed communities of multiple taxa, dominated by Oesophagostomum, matching previous findings using single-specimen genetics. Utilizing the Illumina MiSeq platform, ITS-2 strongylid metabarcoding was applied to 90 samples from various wild NHPs occurring in Malaysian Borneo and Japan. A clear dominance of Oesophagostomum aculeatum was found, with almost all sequences assigned to this species. This study suggests that strongylid communities of Asian NHPs may be less species-rich than those in African NHPs, where multi-genera communities are reported. Such knowledge contributes baseline data, assisting with ongoing monitoring of health threats to NHPs.
Adverse factors in the psychosocial work environment are associated with the onset of depression among those without a personal history of depression. However, the evidence is sparse regarding whether adverse work factors can also play a role in depression recurrence. This study aimed to prospectively examine whether factors in the psychosocial work environment are associated with first-time and recurrent treatment for depression.
Methods
The study included 24,226 participants from the Danish Well-being in Hospital Employees study. We measured ten individual psychosocial work factors and three theoretical constructs (effort–reward imbalance, job strain and workplace social capital). We ascertained treatment for depression through registrations of hospital contacts for depression (International Statistical Classification of Diseases and Related Health Problems version 10 [ICD-10]: F32 and F33) and redeemed prescriptions of antidepressant medication (Anatomical Therapeutic Chemical [ATC]: N06A) in Danish national registries. We estimated the associations between work factors and treatment for depression for up to 2 years after baseline among those without (first-time treatment) and with (recurrent treatment) a personal history of treatment for depression before baseline. We excluded participants registered with treatment within 6 months before baseline. In supplementary analyses, we extended this washout period to up to 2 years. We applied logistic regression analyses with adjustment for confounding.
Results
Among 21,156 (87%) participants without a history of treatment for depression, 350 (1.7%) had first-time treatment during follow-up. Among the 3070 (13%) participants with treatment history, 353 (11%) had recurrent treatment during follow-up. Those with a history of depression generally reported a more adverse work environment than those without such a history. Baseline exposure to bullying (odds ratio [OR] = 1.72, 95% confidence interval [95% CI]: 1.30–2.32), and to some extent also low influence on work schedule (OR = 1.27, 95% CI: 0.97–1.66) and job strain (OR = 1.24, 95% CI: 0.97–1.57), was associated with first-time treatment for depression during follow-up. Baseline exposure to bullying (OR = 1.40, 95% CI: 1.04–1.88), lack of collaboration (OR = 1.31, 95% CI: 1.03–1.67) and low job control (OR = 1.27, 95% CI: 1.00–1.62) were associated with recurrent treatment for depression during follow-up. However, most work factors were not associated with treatment for depression. Using a 2-year washout period resulted in similar or stronger associations.
Conclusions
Depression constitutes a substantial morbidity burden in the working-age population. Specific adverse working conditions were associated with first-time and recurrent treatment for depression and improving these may contribute to reducing the onset and recurrence of depression.
To examine the effectiveness of Self-Help Plus (SH+) as an intervention for alleviating stress levels and mental health problems among healthcare workers.
Methods
This was a prospective, two-arm, unblinded, parallel-designed randomised controlled trial. Participants were recruited at all levels of medical facilities within all municipal districts of Guangzhou. Eligible participants were adult healthcare workers experiencing psychological stress (10-item Perceived Stress Scale scores of ≥15) but without serious mental health problems or active suicidal ideation. A self-help psychological intervention developed by the World Health Organization in alleviating psychological stress and preventing the development of mental health problems. The primary outcome was psychological stress, assessed at the 3-month follow-up. Secondary outcomes were depression symptoms, anxiety symptoms, insomnia, positive affect (PA) and self-kindness assessed at the 3-month follow-up.
Results
Between November 2021 and April 2022, 270 participants were enrolled and randomly assigned to either SH+ (n = 135) or the control group (n = 135). The SH+ group had significantly lower stress at the 3-month follow-up (b = −1.23, 95% CI = −2.36, −0.10, p = 0.033) compared to the control group. The interaction effect indicated that the intervention effect in reducing stress differed over time (b = −0.89, 95% CI = −1.50, −0.27, p = 0.005). Analysis of the secondary outcomes suggested that SH+ led to statistically significant improvements in most of the secondary outcomes, including depression, insomnia, PA and self-kindness.
Conclusions
This is the first known randomised controlled trial ever conducted to improve stress and mental health problems among healthcare workers experiencing psychological stress in a low-resource setting. SH+ was found to be an effective strategy for alleviating psychological stress and reducing symptoms of common mental problems. SH+ has the potential to be scaled-up as a public health strategy to reduce the burden of mental health problems in healthcare workers exposed to high levels of stress.
In order to investigate the three-dimensional effects on the flow characteristics of the thin water film for the three-dimensional wings, the numerical simulation of the droplet impingement and film flow on the MS-0317 wing is implemented based on the open-source package OpenFOAM. The simulation focuses on the effects of the angle-of-attack and the angle of sweepback. The movement and impingement of the droplets are calculated using the Lagrangian method, and the film flow is simulated using the thin film assumption and the finite area method. The simulation of the water film flow of the three-dimensional MS-0317 wing shows that there is a spanwise flow of the water film due to the three-dimensional effects. This suggests that more research should be conducted on the warm glaze ice with surface water film of three-dimensional ice accretion on three-dimensional geometries.
The chemistry of Al transformation has been well documented, though little is known about the mechanisms of structural perturbation of Al precipitates by carbonates at a molecular level. The purpose of the present study was to investigate the structural perturbation of Al precipitates formed under the influence of carbonates. Initial carbonate/Al molar ratios (MRs) used were 0, 0.1, and 0.5 after aging for 32 days, then the samples were analyzed by X-ray absorption near edge structure spectroscopy (XANES), X-ray diffraction (XRD), Fourier-transform infrared absorption spectroscopy (FTIR), and chemical analysis. The XRD data were in accord with the FTIR results, which revealed that as the carbonate/Al MR was increased from 0 to 0.1, carbonate preferentially retarded the formation of gibbsite and had relatively little effect on the formation of bayerite. As the carbonate/Al MR was increased to 0.5, however, the crystallization of both gibbsite and bayerite was completely inhibited. The impact of carbonate on the nature of Al precipitates was also evident in the increase of adsorbed water and inorganic C contents with increasing carbonate/Al MR. The Al K- and L- edge XANES data provide the first evidence illustrating the change in the coordination number of Al from 6-fold to mixed 6- and 4-fold coordination in the structural network of short-range ordered (SRO) Al precipitates formed under the increasing perturbation of carbonate. The fluorescence yield spectra of the O K-edge show that the intensity of the peak at 534.5 eV assigned to σ* transitions of Al-O and O-H bonding decreased with increasing carbonate/Al MR. The XANES data, along with the evidence from XRD, FTIR, and chemical analysis showed clearly that carbonate caused the alteration of the coordination nature of the Al-O bonding through perturbation of the atomic bonding and structural configuration of Al hydroxides by complexation with Al in the SRO network of Al precipitates. The surface reactivity of an Al-O bond is related to its covalency and coordination geometry. The present findings were, therefore, of fundamental significance in understanding the low-temperature geochemistry of Al and its impacts on the transformation, transport, and fate of nutrients and pollutants in the ecosystem.
Strong gas-mineral interactions or slow adsorption kinetics require a molecular-level understanding of both adsorption and diffusion for these interactions to be properly described in transport models. In this combined molecular simulation and experimental study, noble gas adsorption and mobility is investigated in two naturally abundant zeolites whose pores are similar in size (clinoptilolite) and greater than (mordenite) the gas diameters. Simulated adsorption isotherms obtained from grand canonical Monte Carlo simulations indicate that both zeolites can accommodate even the largest gas (Rn). However, gas mobility in clinoptilolite is significantly hindered at pore-limiting window sites, as seen from molecular dynamics simulations in both bulk and slab zeolite models. Experimental gas adsorption isotherms for clinoptilolite confirm the presence of a kinetic barrier to Xe uptake, resulting in the unusual property of reverse Kr/Xe selectivity. Finally, a kinetic model is used to fit the simulated gas loading profiles, allowing a comparison of trends in gas diffusivity in the zeolite pores.
COVID-19 lockdowns increased the risk of mental health problems, especially for children with autism spectrum disorder (ASD). However, despite its importance, little is known about the protective factors for ASD children during the lockdowns.
Methods
Based on the Shanghai Autism Early Developmental Cohort, 188 ASD children with two visits before and after the strict Omicron lockdown were included; 85 children were lockdown-free, while 52 and 51 children were under the longer and the shorter durations of strict lockdown, respectively. We tested the association of the lockdown group with the clinical improvement and also the modulation effects of parent/family-related factors on this association by linear regression/mixed-effect models. Within the social brain structures, we examined the voxel-wise interaction between the grey matter volume and the identified modulation effects.
Results
Compared with the lockdown-free group, the ASD children experienced the longer duration of strict lockdown had less clinical improvement (β = 0.49, 95% confidence interval (CI) [0.19–0.79], p = 0.001) and this difference was greatest for social cognition (2.62 [0.94–4.30], p = 0.002). We found that this association was modulated by parental agreeableness in a protective way (−0.11 [−0.17 to −0.05], p = 0.002). This protective effect was enhanced in the ASD children with larger grey matter volumes in the brain's mentalizing network, including the temporal pole, the medial superior frontal gyrus, and the superior temporal gyrus.
Conclusions
This longitudinal neuroimaging cohort study identified that the parental agreeableness interacting with the ASD children's social brain development reduced the negative impact on clinical symptoms during the strict lockdown.
Phytosterols/phytostanols are bioactive compounds found in vegetable oils, nuts and seeds and added to a range of commercial food products. Consumption of phytosterols/phytostanols reduces levels of circulating LDL-cholesterol, a causative biomarker of CVD, and is linked to a reduced risk of some cancers. Individuals who consume phytosterols/phytostanols in their diet may do so for many years as part of a non-pharmacological route to lower cholesterol or as part of a healthy diet. However, the impact of long term or high intakes of dietary phytosterols/phytostanols has not been on whole-body epigenetic changes before. The aim of this systematic review was to identify all publications that have evaluated changes to epigenetic mechanisms (post-translation modification of histones, DNA methylation and miRNA expression) in response to phytosterols/phytostanols. A systematic search was performed that returned 226 records, of which eleven were eligible for full-text analysis. Multiple phytosterols were found to inhibit expression of histone deacetylase (HDAC) enzymes and were also predicted to directly bind and impair HDAC activity. Phytosterols were found to inhibit the expression and activity of DNA methyl transferase enzyme 1 and reverse cancer-associated gene silencing. Finally, phytosterols have been shown to regulate over 200 miRNA, although only five of these were reported in multiple publications. Five tissue types (breast, prostate, macrophage, aortic epithelia and lung) were represented across the studies, and although phytosterols/phytostanols alter the molecular mechanisms of epigenetic inheritance in these mammalian cells, studies exploring meiotic or transgenerational inheritance were not found.
Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph–based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly “Question-of-the-Month (QotM) Challenge” series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.
Three wave resonant triad interactions in two space and one time dimensions form a well-known system of first-order quadratically nonlinear evolution equations that arise in many areas of physics. In deep water waves, they were first derived by Simmons in 1969 and later shown to be exactly solvable by Ablowitz & Haberman in 1975. Specifically, integrability was established by introducing a system of six wave interactions whose symmetry reduction leads to the well-known three wave equations. Here, it is shown that the six wave interaction and classical three wave equations satisfying triad resonance conditions in finite-depth gravity waves can be derived from the non-local integro-differential formulation of the free surface gravity wave equation with surface tension. These quadratically nonlinear six wave interaction equations and their reductions to the classical and non-local complex as well as real reverse space–time three wave interaction equations are integrable. Limits to infinite and shallow water depth are also discussed.
The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.
We present the development and characterization of a high-stability, multi-material, multi-thickness tape-drive target for laser-driven acceleration at repetition rates of up to 100 Hz. The tape surface position was measured to be stable on the sub-micrometre scale, compatible with the high-numerical aperture focusing geometries required to achieve relativistic intensity interactions with the pulse energy available in current multi-Hz and near-future higher repetition-rate lasers ($>$kHz). Long-term drift was characterized at 100 Hz demonstrating suitability for operation over extended periods. The target was continuously operated at up to 5 Hz in a recent experiment for 70,000 shots without intervention by the experimental team, with the exception of tape replacement, producing the largest data-set of relativistically intense laser–solid foil measurements to date. This tape drive provides robust targetry for the generation and study of high-repetition-rate ion beams using next-generation high-power laser systems, also enabling wider applications of laser-driven proton sources.
Prior evidence indicates that negative symptom severity and cognitive deficits, in people with schizophrenia (PSZ), relate to measures of reward-seeking and loss-avoidance behavior (implicating the ventral striatum/VS), as well as uncertainty-driven exploration (reliant on rostrolateral prefrontal cortex/rlPFC). While neural correlates of reward-seeking and loss-avoidance have been examined in PSZ, neural correlates of uncertainty-driven exploration have not. Understanding neural correlates of uncertainty-driven exploration is an important next step that could reveal insights to how this mechanism of cognitive and negative symptoms manifest at a neural level.
Methods
We acquired fMRI data from 29 PSZ and 36 controls performing the Temporal Utility Integration decision-making task. Computational analyses estimated parameters corresponding to learning rates for both positive and negative reward prediction errors (RPEs) and the degree to which participates relied on representations of relative uncertainty. Trial-wise estimates of expected value, certainty, and RPEs were generated to model fMRI data.
Results
Behaviorally, PSZ demonstrated reduced reward-seeking behavior compared to controls, and negative symptoms were positively correlated with loss-avoidance behavior. This finding of a bias toward loss avoidance learning in PSZ is consistent with previous work. Surprisingly, neither behavioral measures of exploration nor neural correlates of uncertainty in the rlPFC differed significantly between groups. However, we showed that trial-wise estimates of relative uncertainty in the rlPFC distinguished participants who engaged in exploratory behavior from those who did not. rlPFC activation was positively associated with intellectual function.
Conclusions
These results further elucidate the nature of reinforcement learning and decision-making in PSZ and healthy volunteers.
Avian radar systems are effective for wide-area bird detection and tracking, but application significances need further exploration. Existing radar data mining methods provide long-term functionalities, but they are problematic for bird activity modelling especially in temporal domain. This paper complements this insufficiency by introducing a temporal bird activity extraction and interpretation method. The bird behaviour is quantified as the activity degree which integrates intensity and uncertainty characters with an entropy weighing algorithm. The method is applicable in multiple temporal scales. Historical radar dataset from a system deployed in an airport is adopted for verification. Temporal characters demonstrate good consistency with understandings from local observers and ornithologists. Daily commuting and roosting characters of local birds are well reflected, evening bat activities are also extracted. Night migration activities are demonstrated clearly. Results indicate the proposed method is effective in temporal bird activity modelling and interpretation. Its integration with bird strike risk models might be more useful for airport safety management with wildlife interference.