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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.
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.
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.
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.
The dual-user training system is essential for fostering motor skill learning, particularly in complex operations. However, the challenge lies in the optimal tradeoff between trainee ability and engagement level. To address this problem, we propose an intelligent agent that coordinates trainees’ control authority during real task engagement to ensure task safety during training. Our approach avoids the need for manually set control authority by expert supervision. At the same time, it does not rely on pre-modeling the trainee’s skill development. The intelligent agent uses a deep reinforcement learning (DRL) algorithm based on trainee performance to adjust adaptive engagement during the training process. Our investigation aims to provide reasonable engagement for trainees to improve their skills while ensuring task safety. Our results demonstrate that this system can seek the policy to maximize trainee participation while guaranteeing task safety.
Hydrodynamic approaches that treat granular materials as a continuum via the homogenization of discrete flow properties have become viable options for efficient predictions of bulk flow behaviours. However, simplified boundary conditions in computational fluid dynamics are often adopted, which have difficulty in describing the complex stick–slip phenomenon at the boundaries. This paper extends the lattice Boltzmann method for granular flow simulations by incorporating a novel frictional boundary condition. The wall slip velocity is first calculated based on the shear rate limited by the Coulomb friction, followed by the reconstruction of unknown density distribution functions through a modified bounce-back scheme. Validation is performed against a unique plane Couette flow configuration, and the analytical solutions for the flow velocity profile and the wall slip velocity, as functions of the friction coefficient, are reproduced by the numerical model. The transition between no-slip and partial-slip regimes is captured well, but the convergence rate drops from second order to first order when slip occurs. The rheological parameters and the basal friction coefficient are calibrated further against the discrete element simulation of a square granular column collapsing over a horizontal bottom plane. It is found that the calibrated continuum model can predict other granular column collapses with different initial aspect ratios and slope inclination angles, including the basal slip and the complex internal flow structures, without any further adjustments to the model parameters. This highlights the generalization ability of the numerical model, which has a wide range of application in granular flow predictions and controls.
Inflammation plays a critical role in the progression of chronic liver diseases, and diet can modulate inflammation. Whether an inflammatory dietary pattern is associated with higher risk of hepatic steatosis or fibrosis remains unclear. We aimed to investigate the associations between inflammatory dietary pattern and the odds of hepatic steatosis and fibrosis.
In this nationwide cross-sectional study, diet was measured using two 24-h dietary recalls. Empirical dietary inflammatory pattern (EDIP) score was derived to assess the inflammatory potential of usual diet, which has been validated to highly predict inflammation markers in the study population. Controlled attenuation parameter (CAP) and liver stiffness measurement (LSM) were derived from FibroScan to define steatosis and fibrosis, respectively.
US National Health and Nutrition Examination Survey.
4171 participants aged ≥18 years.
A total of 1436 participants were diagnosed with S1 steatosis (CAP ≥ 274 dB/m), 255 with advanced fibrosis (LSM ≥ 9·7 kPa). Compared with those in the lowest tertile of EDIP-adherence scores, participants in the highest tertile had 74 % higher odds of steatosis (OR: 1·74, 95 % CI (1·26, 2·41)). Such positive association persisted among never drinkers, or participants who were free of hepatitis B and/or C. Similarly, EDIP was positively associated with CAP in multivariate linear model (P < 0·001). We found a non-significant association of EDIP score with advanced fibrosis or LSM (P = 0·837).
Our findings suggest that a diet score that is associated with inflammatory markers is associated with hepatic steatosis. Reducing or avoiding pro-inflammatory diets intake might be an attractive strategy for fatty liver disease prevention.
During the COVID-19 pandemic, there was an increase in online gaming behaviour among college students. This study aimed to examine the impact of online self-help interventions consisting of different components within the Acceptance and Commitment Therapy (ACT) framework on college students’ gaming disorder and gaming frequency. Additionally, it evaluated the effectiveness of both interventions in addressing psychological distress among college students during the COVID-19 pandemic. One intervention was a full ACT program, which consists of six core components, while the other intervention focused on the engaged components of ACT (specifically targeting value-based actions). The study employed a 2 conditions (Full ACT vs. Engaged ACT) × 3 times (pre-, mid- and post-program) design to examine the effectiveness of these interventions. Each intervention consisted of 10 sessions, delivered at a frequency of five sessions per week over a 2-week period for both groups. The participants in this study were enrolled in two online classes. Participants with gaming disorder scores in the top 20% were selected and assigned to either the Full group (N = 49) or the Engaged group (N = 41) for the interventions. The study assessed outcome variables, including gaming disorder, psychological flexibility, daily gaming hours, weekly gaming days and psychological distress, at pre-intervention, mid-intervention, post-intervention and one-month follow-up for both groups. No significant differences were observed between the two groups on these outcomes at the pre-intervention stage. The findings of this study indicate that both interventions effectively reduced gaming disorder and weekly gaming frequency, while enhancing psychological flexibility. Nonetheless, the Engaged group exhibited a significant reduction in daily gaming hours. There was no substantial change in psychological distress in either group during and after the intervention. The implications and limitations of this study were also reported.
SARS-CoV-2 rapidly spreads among humans via social networks, with social mixing and network characteristics potentially facilitating transmission. However, limited data on topological structural features has hindered in-depth studies. Existing research is based on snapshot analyses, preventing temporal investigations of network changes. Comparing network characteristics over time offers additional insights into transmission dynamics. We examined confirmed COVID-19 patients from an eastern Chinese province, analyzing social mixing and network characteristics using transmission network topology before and after widespread interventions. Between the two time periods, the percentage of singleton networks increased from 38.9$ \% $ to 62.8$ \% $$ (p<0.001) $; the average shortest path length decreased from 1.53 to 1.14 $ (p<0.001) $; the average betweenness reduced from 0.65 to 0.11$ (p<0.001) $; the average cluster size dropped from 4.05 to 2.72 $ (p=0.004) $; and the out-degree had a slight but nonsignificant decline from 0.75 to 0.63 $ (p=0.099). $ Results show that nonpharmaceutical interventions effectively disrupted transmission networks, preventing further disease spread. Additionally, we found that the networks’ dynamic structure provided more information than solely examining infection curves after applying descriptive and agent-based modeling approaches. In summary, we investigated social mixing and network characteristics of COVID-19 patients during different pandemic stages, revealing transmission network heterogeneities.
The age-related heterogeneity in major depressive disorder (MDD) has received significant attention. However, the neural mechanisms underlying such heterogeneity still need further investigation. This study aimed to explore the common and distinct functional brain abnormalities across different age groups of MDD patients from a large-sample, multicenter analysis.
The analyzed sample consisted of a total of 1238 individuals including 617 MDD patients (108 adolescents, 12–17 years old; 411 early-middle adults, 18–54 years old; and 98 late adults, > = 55 years old) and 621 demographically matched healthy controls (60 adolescents, 449 early-middle adults, and 112 late adults). MDD-related abnormalities in brain functional connectivity (FC) patterns were investigated in each age group separately and using the whole pooled sample, respectively.
We found shared FC reductions among the sensorimotor, visual, and auditory networks across all three age groups of MDD patients. Furthermore, adolescent patients uniquely exhibited increased sensorimotor-subcortical FC; early-middle adult patients uniquely exhibited decreased visual-subcortical FC; and late adult patients uniquely exhibited wide FC reductions within the subcortical, default-mode, cingulo-opercular, and attention networks. Analysis of covariance models using the whole pooled sample further revealed: (1) significant main effects of age group on FCs within most brain networks, suggesting that they are decreased with aging; and (2) a significant age group × MDD diagnosis interaction on FC within the default-mode network, which may be reflective of an accelerated aging-related decline in default-mode FCs.
To summarize, these findings may deepen our understanding of the age-related biological and clinical heterogeneity in MDD.
We document and explain the sharp performance deterioration of smart beta indexes after the corresponding exchange-traded funds (ETFs) are launched for investment. While smart beta is purported to deliver excess returns through factor exposures, the market-adjusted return of smart beta indexes drops from about 3% “on paper” before ETF listings to about −0.50% to −1% after ETF listings. This performance decline cannot be explained by variation in factor premia, strategic timing, or diminishing returns to scale. Instead, we find strong evidence of data mining in the construction of smart beta indexes, which helps ETFs attract flows, as investors respond positively to backtests.
In this study, aluminium fluoride trihydrate (AlF3⋅3H2O) was used to inhibit the sintering of calcined coal-series kaolin (CCSK). In addition, the oil absorption properties of CCSK were studied. The particle-size distribution, specific surface area and porosity of the samples were investigated as a function of calcination temperature and the addition of AlF3⋅3H2O. Moreover, the ability of AlF3⋅3H2O to improve the oil absorption of CCSK was explored. The morphology, structure and phase composition of the specimens were investigated using scanning electron microscopy and X-ray diffraction. The phase transition during heating of the samples was studied using thermogravimetric analysis. The preparation with 10 wt.% AlF3⋅3H2O had the optimal sintering inhibition effect on CCSK at 1000°C. The release of SiF4 gas during heating and the formation of mullite whiskers on the particle surface caused by AlF3⋅3H2O moderated the formation of molten-phase liquid bridges between particles and inhibited sintering of the raw material powder. Furthermore, the formation of submicron mullite whiskers on the surface of the CCSK particles enhanced the oil-absorption properties of the sample significantly.
With the aid of recently proposed word embedding algorithms, the study of semantic relatedness has progressed rapidly. However, word-level representations are still lacking for many natural language processing tasks. Various sense-level embedding learning algorithms have been proposed to address this issue. In this paper, we present a generalized model derived from existing sense retrofitting models. In this generalization, we take into account semantic relations between the senses, relation strength, and semantic strength. Experimental results show that the generalized model outperforms previous approaches on four tasks: semantic relatedness, contextual word similarity, semantic difference, and synonym selection. Based on the generalized sense retrofitting model, we also propose a standardization process on the dimensions with four settings, a neighbor expansion process from the nearest neighbors, and combinations of these two approaches. Finally, we propose a Procrustes analysis approach that inspired from bilingual mapping models for learning representations that outside of the ontology. The experimental results show the advantages of these approaches on semantic relatedness tasks.
The association between time-restricted eating (TRE) and the risk of non-alcoholic fatty liver disease (NAFLD) is less studied. Moreover, whether the association is independent of physical exercise or diet quality or quantity is uncertain. In this nationwide cross-sectional study of 3813 participants, the timing of food intakes was recorded by 24-h recalls; NAFLD was defined through vibration-controlled transient elastography in the absence of other causes of chronic liver disease. OR and 95 % CI were estimated using logistic regression. Participants with daily eating window of ≤ 8 h had lower odds of NAFLD (OR = 0·70, 95 % CI: 0·52, 0·93), compared with those with ≥ 10 h window. Early (05.00–15.00) and late TRE (11.00–21.00) showed inverse associations with NAFLD prevalence without statistical heterogeneity (Pheterogeneity = 0·649) with OR of 0·73 (95 % CI: 0·36, 1·47) and 0·61 (95 % CI: 0·44, 0·84), respectively. Such inverse association seemed stronger in participants with lower energy intake (OR = 0·58, 95 % CI: 0·38, 0·89, Pinteraction = 0·020). There are no statistical differences in the TRE-NAFLD associations according to physical activity (Pinteraction = 0·390) or diet quality (Pinteraction = 0·110). TRE might be associated with lower likelihood of NAFLD. Such inverse association is independent of physical activity and diet quality and appears stronger in individuals consuming lower energy. Given the potential misclassification of TRE based on one- or two-day recall in the analysis, epidemiological studies with validated methods for measuring the habitual timing of dietary intake are warranted.
In recent years, bat-associated pathogens, such as 2019 novel coronavirus, have been ravaging the world, and ectoparasites of bats have received increasing attention. Penicillidia jenynsii is a member of the family Nycteribiidae which is a group of specialized ectoparasites of bats. In this study, the complete mitochondrial genome of P. jenynsii was sequenced for the first time and a comprehensive phylogenetic analysis of the superfamily Hippoboscoidea was conducted. The complete mitochondrial genome of P. jenynsii is 16 165 base pairs (bp) in size, including 13 protein-coding genes (PCGs), 22 transfer RNA genes, 2 ribosomal RNA genes and 1 control region. The phylogenetic analysis based on 13 PCGs of the superfamily Hippoboscoidea known from the NCBI supported the monophyly of the family Nycteribiidae, and the family Nycteribiidae was a sister group with the family Streblidae. This study not only provided molecular data for the identification of P. jenynsii, but also provided a reference for the phylogenetic analysis of the superfamily Hippoboscoidea.
Accumulating evidence suggests that positive and negative emotions, as well as emotion regulation, play key roles in human health and disease. Recent work has shown the gut microbiome is important in modulating mental and physical health through the gut–brain axis. Yet, its association with emotions and emotion regulation are understudied. Here we examined whether positive and negative emotions, as well as two emotion regulation strategies (i.e. cognitive reappraisal and suppression), were associated with the gut microbiome composition and functional pathways in healthy women.
Participants were from the Mind-Body Study (N = 206, mean age = 61), a sub-study of the Nurses' Health Study II cohort. In 2013, participants completed measures of emotion-related factors. Two pairs of stool samples were collected, 6 months apart, 3 months after emotion-related factors measures were completed. Analyses examined associations of emotion-related factors with gut microbial diversity, overall microbiome structure, and specific species/pathways and adjusted for relevant covariates.
Alpha diversity was negatively associated with suppression. In multivariate analysis, positive emotions were inversely associated with the relative abundance of Firmicutes bacterium CAG 94 and Ruminococcaceae bacterium D16, while negative emotions were directly correlated with the relative abundance of these same species. At the metabolic pathway level, negative emotions were inversely related to the biosynthesis of pantothenate, coenzyme A, and adenosine.
These findings offer human evidence supporting linkages of emotions and related regulatory processes with the gut microbiome and highlight the importance of incorporating the gut microbiome in our understanding of emotion-related factors and their associations with physical health.
We aimed to investigate the association of metabolic obesity phenotypes with all-cause mortality risk in a rural Chinese population. This prospective cohort study enrolled 15 704 Chinese adults (38·86 % men) with a median age of 51·00 (interquartile range: 41·00–60·00) at baseline (2007–2008) and followed up during 2013–2014. Obesity was defined by waist circumference (WC: ≥ 90 cm for men and ≥ 80 cm for women) or waist-to-height ratio (WHtR: ≥ 0·5). The hazard ratio (HR) and 95 % CI for the risk of all-cause mortality related to metabolic obesity phenotypes were calculated using the Cox hazards regression model. During a median follow-up of 6·01 years, 864 deaths were identified. When obesity was defined by WC, the prevalence of participants with metabolically healthy non-obesity (MHNO), metabolically healthy obesity (MHO), metabolically unhealthy non-obesity (MUNO) and metabolically unhealthy obesity (MUO) at baseline was 12·12 %, 2·80 %, 41·93 % and 43·15 %, respectively. After adjusting for age, sex, alcohol drinking, smoking, physical activity and education, the risk of all-cause mortality was higher with both MUNO (HR = 1·20, 95 % CI 1·14, 1·26) and MUO (HR = 1·20, 95 % CI 1·13, 1·27) v. MHNO, but the risk was not statistically significant with MHO (HR = 0·99, 95 % CI 0·89, 1·10). This result remained consistent when stratified by sex. Defining obesity by WHtR gave similar results. MHO does not suggest a greater risk of all-cause mortality compared to MHNO, but participants with metabolic abnormality, with or without obesity, have a higher risk of all-cause mortality. These results should be cautiously interpreted as the representation of MHO is small.
Understanding user perceptions of interacting with the virtual world is one of the research focuses in recent years, given the rapid proliferation of virtual reality (VR) and driven to establish the metaverse. Users can generate a familiar connection between their bodies and the virtual world by being embodied in virtual hands, and hand representations can induce users’ embodiment in VR. The sense of embodiment represents the cognitive awareness of one's manifestation and includes three subcomponents: the sense of body ownership, agency and self-location. There is insufficient evidence in the literature about the effects of hand designs on the embodiment, especially based on studying its three subcomponents. This study investigates how virtual hand designs with five realism levels influence the three subcomponents of embodiment in VR. This research employs a self-report questionnaire commonly used in the literature to assess embodiment and evaluates agency and self-location by introducing implicit methods (intentional binding and proprioceptive measurement) derived from psychology. Besides, the objective data of eye tracking is used to explore the connection between embodiment and hand designs, and classifying participants’ eye tracking data to help analyze the link between embodiment and user attention. Overall, this research makes a major contribution through a systematic exploration of users’ embodied experience in VR and offers important evidence of the effects of virtual hand designs on body ownership, agency, and self-location, respectively. In addition, this study provides a valuable reference for further investigation of embodiment through implicit and objective methods, and practical design recommendations for virtual hand design in VR applications.
Computer-aided design (CAD) plays an essential role in creative idea generation on 2D screens during the design process. In most CAD scenarios, virtual object translation is an essential operation, and it is commonly used when designers simulate their innovative solutions. The degrees of freedom (DoF) of virtual object translation modes have been found to directly impact users’ task performance and psychological aspects in simulated environments. Little is known in the existing literature about the sense of agency (SoA), which is a critical psychological aspect emphasizing the feeling of control, in translation modes on 2D screens during the design process. Hence, this study aims to assess users’ SoA in virtual object translation modes on mouse-based, touch-based, and handheld augmented reality (AR) interfaces through subjective and objective measures, such as self-report, task performance, and electroencephalogram (EEG) data. Based on our findings in this study, users perceived a greater feeling of control in 1DoF translation mode, which may help them come up with more creative ideas, than in 3DoF translation mode in the design process; additionally, the handheld AR interface offers less control feel, which may have a negative impact on design quality and creativity, as compared with mouse- and touch-based interfaces. This research contributes to the current literature by analyzing the association between virtual object translation modes and SoA, as well as the relationship between different 2D interfaces and SoA in CAD. As a result of these findings, we propose several design considerations for virtual object translation on 2D screens, which may enable designers to perceive a desirable feeling of control during the design process.
Coastal eutrophication and hypoxia remain a persistent environmental crisis despite the great efforts to reduce nutrient loading and mitigate associated environmental damages. Symptoms of this crisis have appeared to spread rapidly, reaching developing countries in Asia with emergences in Southern America and Africa. The pace of changes and the underlying drivers remain not so clear. To address the gap, we review the up-to-date status and mechanisms of eutrophication and hypoxia in global coastal oceans, upon which we examine the trajectories of changes over the 40 years or longer in six model coastal systems with varying socio-economic development statuses and different levels and histories of eutrophication. Although these coastal systems share common features of eutrophication, site-specific characteristics are also substantial, depending on the regional environmental setting and level of social-economic development along with policy implementation and management. Nevertheless, ecosystem recovery generally needs greater reduction in pressures compared to that initiated degradation and becomes less feasible to achieve past norms with a longer time anthropogenic pressures on the ecosystems. While the qualitative causality between drivers and consequences is well established, quantitative attribution of these drivers to eutrophication and hypoxia remains difficult especially when we consider the social economic drivers because the changes in coastal ecosystems are subject to multiple influences and the cause–effect relationship is often non-linear. Such relationships are further complicated by climate changes that have been accelerating over the past few decades. The knowledge gaps that limit our quantitative and mechanistic understanding of the human-coastal ocean nexus are identified, which is essential for science-based policy making. Recognizing lessons from past management practices, we advocate for a better, more efficient indexing system of coastal eutrophication and an advanced regional earth system modeling framework with optimal modules of human dimensions to facilitate the development and evaluation of effective policy and restoration actions.
In the Three Gorges and adjacent areas, there are three planation surfaces and five terraces along the Yangtze River that record the evolution history of the river system. Here, we used diagnostic heavy minerals, U-Pb geochronology, and trace elements of detrital zircons from one planation surface, two terraces, and a modern point bar to reconstruct the evolution history of the upper Yangtze River, specifically the Chuan River in the Sichuan Basin. The sediments in the lowest planation surface had different felsic source rocks derived from east of the Three Gorges, which indicated that before the disintegration of the lowest planation surface (0.75 Ma), there were two paleorivers: the westward-flowing paleo-Chuan River and eastward-flowing paleo-Yangtze River separated by the Huangling Dome. At 0.75–0.73 Ma, the dominant detrital zircons from the Sichuan Basin in the sediments of terrace T5 (the highest terrace) confirmed that the paleo-Yangtze River cut through the Three Gorges and captured the paleo-Chuan River, and the Daliang Mountains became the new drainage divide. Finally, the appearance of materials from the upper Jinsha River in terrace T2 indicated that the paleo-Yangtze River progressively captured the paleo-Jinsha River, and the modern upper Yangtze River formed before 0.05 Ma. These river capture events of the upper Yangtze River confirmed the Quaternary uplift of the SE Tibetan Plateau.
In this work, a confined-doped fiber with the core/inner-cladding diameter of 40/250 μm and a relative doping ratio of 0.75 is fabricated through a modified chemical vapor deposition method combined with the chelate gas deposition technique, and subsequently applied in a tandem-pumped fiber amplifier for high-power operation and transverse mode instability (TMI) mitigation. Notably, the impacts of the seed laser power and mode purity are preliminarily investigated through comparative experiments. It is found that the TMI threshold could be significantly affected by the seed laser mode purity. The possible mechanism behind this phenomenon is proposed and revealed through comprehensive comparative experiments and theoretical analysis. Finally, a maximum output power of 7.49 kW is obtained with the beam quality factor of approximately 1.83, which is the highest output power ever reported in a forward tandem-pumped confined-doped fiber amplifier. This work could provide a good reference and practical solution to improve the TMI threshold and realize high-power high-brightness fiber lasers.