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Internet addiction (IA) refers to excessive internet use that causes cognitive impairment or distress. Understanding the neurophysiological mechanisms underpinning IA is crucial for enabling an accurate diagnosis and informing treatment and prevention strategies. Despite the recent increase in studies examining the neurophysiological traits of IA, their findings often vary. To enhance the accuracy of identifying key neurophysiological characteristics of IA, this study used the phase lag index (PLI) and weighted PLI (WPLI) methods, which minimize volume conduction effects, to analyze the resting-state electroencephalography (EEG) functional connectivity. We further evaluated the reliability of the identified features for IA classification using various machine learning methods.
Methods
Ninety-two participants (42 with IA and 50 healthy controls (HCs)) were included. PLI and WPLI values for each participant were computed, and values exhibiting significant differences between the two groups were selected as features for the subsequent classification task.
Results
Support vector machine (SVM) achieved an 83% accuracy rate using PLI features and an improved 86% accuracy rate using WPLI features. t-test results showed analogous topographical patterns for both the WPLI and PLI. Numerous connections were identified within the delta and gamma frequency bands that exhibited significant differences between the two groups, with the IA group manifesting an elevated level of phase synchronization.
Conclusions
Functional connectivity analysis and machine learning algorithms can jointly distinguish participants with IA from HCs based on EEG data. PLI and WPLI have substantial potential as biomarkers for identifying the neurophysiological traits of IA.
We aimed to validate In-Body BIA measures with DXA as reference and to describe the BC profiling of Tibetan adults.
Design:
This cross-sectional study included 855 participants (391 men and 464 women).Correlation and Bland-Altman analyses were performed for method agreement of In-Body BIA and DXA. BC were described by obesity and metabolic status.
Setting:
Bioelectrical Impedance Analysis (In-Body BIA) and Dual-energy X-ray absorptiometry (DXA) have not been employed to characterize the body composition (BC) of the Tibetan population living in the Qinghai-Tibet Plateau.
Participants:
A total of 855 Tibetan adults, including 391 men and 464 women, were enrolled in the study.
Results:
Concordance correlation coefficient for total fat mass (FM) and total lean mass (LM) between In-Body BIA and DXA were 0.91 and 0.89. The bias of In-Body BIA for percentages of total FM and total LM was 0.91% (2.46%) and -1.74% (-2.80%) compared with DXA, respectively. Absolute limits of agreement were wider for total FM in obese men and women and for total LM in overweight men than their counterparts. Gradience in the distribution of total and regional FM content was observed across different BMI categories and its combinations with waist circumference and metabolic status.
Conclusions:
In-Body BIA and DXA provided overall good agreement at group level in Tibetan adults, but the agreement was inferior in participants being overweight or obese.
Insufficient sleep’s impact on cognitive and emotional function is well-documented, but its effects on social functioning remain understudied. This research investigates the influence of depressive symptoms on the relationship between sleep deprivation (SD) and social decision-making. Forty-two young adults were randomly assigned to either the SD or sleep control (SC) group. The SD group stayed awake in the laboratory, while the SC group had a normal night’s sleep at home. During the subsequent morning, participants completed a Trust Game (TG) in which a higher monetary offer distributed by them indicated more trust toward their partners. They also completed an Ultimatum Game (UG) in which a higher acceptance rate indicated more rational decision-making. The results revealed that depressive symptoms significantly moderated the effect of SD on trust in the TG. However, there was no interaction between group and depressive symptoms found in predicting acceptance rates in the UG. This study demonstrates that individuals with higher levels of depressive symptoms display less trust after SD, highlighting the role of depressive symptoms in modulating the impact of SD on social decision-making. Future research should explore sleep-related interventions targeting the psychosocial dysfunctions of individuals with depression.
Conditional risk measures and their associated risk contribution measures are commonly employed in finance and actuarial science for evaluating systemic risk and quantifying the effects of risk interactions. This paper introduces various types of contribution ratio measures based on the multivariate conditional value-at-risk (MCoVaR), multivariate conditional expected shortfall (MCoES), and multivariate marginal mean excess (MMME) studied in [34] (Ortega-Jiménez, P., Sordo, M., & Suárez-Llorens, A. (2021). Stochastic orders and multivariate measures of risk contagion. Insurance: Mathematics and Economics, vol. 96, 199–207) and [11] (Das, B., & Fasen-Hartmann, V. (2018). Risk contagion under regular variation and asymptotic tail independence. Journal of Multivariate Analysis165(1), 194–215) to assess the relative effects of a single risk when other risks in a group are in distress. The properties of these contribution risk measures are examined, and sufficient conditions for comparing these measures between two sets of random vectors are established using univariate and multivariate stochastic orders and statistically dependent notions. Numerical examples are presented to validate these conditions. Finally, a real dataset from the cryptocurrency market is used to analyze the spillover effects through our proposed contribution measures.
Dusty plasmas typically contain various species of dust particles, though most studies have focused on homogeneous systems. This paper investigates the propagation of dust acoustic waves in an inhomogeneous dusty plasma with an interface, analysing how plasma inhomogeneity influences wave behaviour. Using scattering and reductive perturbation methods, we show that both transmitted and reflected waves depend strongly on the mass ratio between regions. Dust acoustic waves cannot propagate through a dust lattice when the wavelength is smaller than the lattice constant. At a discontinuous interface, at least one transmitted solitary wave is generated, with its amplitude determined by the mass ratio, while at most one reflected solitary wave can exist. These results underscore the critical role of the mass ratio in wave propagation and suggest a method for estimating dust particle masses and properties by analysing the incident, transmitted and reflected waves.
Obesity, a global health issue, is associated with numerous diseases and has been shown to affect male reproductive health by inducing endocrine hormonal changes, chronic inflammation, oxidative stress and epigenetic alterations in reproductive cells. This study investigates the impact of obesity on testicular gene expression across mice, monkeys and humans, identifying 730 conserved testis-specific genes. High-fat diet-induced obesity upregulates GNG5, INHA, MSH5, SLC30A8 and SLC7A4 in testes, suggesting their potential as regulatory targets in testicular damage associated with obesity. Single-cell analysis reveals species-conserved expression patterns of SLC7A4 in Sertoli cells and SLC30A8 in SPG cells. It also confirmed that SLC30A8 and SLC7A4 were significantly upregulated in the testes of spontaneously obese mice. The findings highlight the potential of these genes as regulatory targets in obesity-related testicular dysfunction, providing insights into male reproductive health impairments caused by obesity.
The cumulative effects of long-term exposure to pandemic-related stressors and the severity of social restrictions may have been important determinants of mental distress in the time of COVID-19.
Aim
This study aimed to investigate mental health among a cohort of Chinese university students over a 28-month period, focusing on the effects of lockdown type.
Methods
Depression, anxiety, stress and fear of COVID-19 infection were measured ten times among 188 Chinese students (females 77.7%, meanage = 19.8, s.d.age = 0.97), every 3 months: from prior to the emergence of COVID-19 in November 2019 (T1) to March 2022 (T10).
Results
Initially depression, anxiety and stress dipped from T1 to T2, followed by a sudden increase at T3 and a slow upward rise over the remainder of the study period (T3 to T10). When locked down at university, participants showed greater mental distress compared with both home lockdown (d = 0.35–0.48) and a no-lockdown comparison period (d = 0.28–0.40). Conversely, home lockdown was associated with less anxiety and stress (d = 0.19 and 0.21, respectively), but not with depression (d = 0.13) compared with a no-lockdown period.
Conclusions
This study highlights the cumulative effects of exposure to COVID-19 stressors over time. It also suggests that the way in which a lockdown is carried out can impact the well-being of those involved. Some forms of lockdown appear to pose a greater threat to mental health than others.
Postpartum maternal diet quality has been linked with optimal infant feeding practices. However, whether maternal diet quality during pregnancy influences infant feeding practices remains unclear. The present study explored the relationship between maternal diet quality in pregnancy and infant feeding practices in Australian women. A brief 15-item FFQ was used to collect maternal dietary data (n 469). Diet quality was calculated using a modified 2013 Dietary Guideline Index (DGI). Multivariable linear and logistic regressions with adjustment for covariates were used to examine associations between maternal diet quality in pregnancy and infant feeding practices: infant feeding mode, breast-feeding duration and timing of solids introduction. Higher DGI score during pregnancy was associated with higher odds of breast-feeding than formula/mixed feeding (adjusted OR (AOR) 1·03, 95 % CI 1·00, 1·07), longer breast-feeding duration (adjusted β 0·09, 95 % CI 0·03, 0·15) and higher odds of breast-feeding for ≥ 6 months (AOR 1·04, 95 % CI 1·02, 1·07) than for < 6 months. Associations between maternal DGI score and breast-feeding variables were moderated by maternal country of birth, with significant associations observed in Australian-born mothers only. No association was found between maternal DGI score and timing of solids introduction. Higher maternal diet quality was associated with better infant feeding practices, and the association was moderated by country of birth. Our findings provide evidence to support the initiation of dietary interventions to promote diet quality during pregnancy, particularly among Australian-born women. Further research could explore underlying mechanisms linking maternal diet quality and infant feeding practices.
In the contemporary maritime industry, characterised by intense competition, reduced visibility due to heavy fog is a primary cause of accidents, significantly impairing maritime operational efficiency. Consequently, investigating foggy weather navigation safety holds crucial practical significance. This paper, through an analysis and synthesis of various aspects of foggy navigation technology, including foggy navigation regulations at different ports, fog warnings, foggy vessel environmental perception and foggy auxiliary navigation systems, explores the key issues concerning vessel navigation during foggy conditions from a scientific perspective. This discussion encompasses the aspects of regulatory frameworks, standardisation, and the development of intelligent and responsive onboard equipment. Finally, the paper offers a glimpse into potential strategies for fog navigation.
Substantial changes resulting from the interaction of environmental and dietary factors contribute to an increased risk of obesity, while their specific associations with obesity remain unclear. We identified inflammation-related dietary patterns (DP) and explored their associations with obesity among urbanised Tibetan adults under significant environmental and dietary changes. Totally, 1826 subjects from the suburbs of Golmud City were enrolled in an open cohort study, of which 514 were followed up. Height, weight and waist circumference were used to define overweight and obesity. DP were derived using reduced rank regression with forty-one food groups as predictors and high-sensitivity C-reactive protein and prognostic nutritional index as inflammatory response variables. Altitude was classified as high or ultra-high. Two DP were extracted. DP-1 was characterised by having high consumptions of sugar-sweetened beverages, savoury snacks, and poultry and a low intake of tsamba. DP-2 had high intakes of poultry, pork, animal offal, and fruits and a low intake of butter tea. Participants in the highest tertiles (T3) of DP had increased risks of overweight and obesity (DP-1: OR = 1·37, 95 % CI 1·07, 1·77; DP-2: OR = 1·48, 95 % CI 1·18, 1·85) than those in the lowest tertiles (T1). Participants in T3 of DP-2 had an increased risk of central obesity (OR = 2·25, 95 % CI 1·49, 3·39) than those in T1. The positive association of DP-1 with overweight and obesity was only significant at high altitudes, while no similar effect was observed for DP-2. Inflammation-related DP were associated with increased risks of overweight and/or obesity.
Demoralization isa common psychological problem in cancer patients. The purpose of this study is to systematically evaluate the correlated factors of demoralization among cancer patients. We also summarized the available evidence, effect estimates, and the strength of statistical associations between demoralization and its associated factors.
Methods
We systematically searched PubMed, Web of Science, CINAHL, Embase, the Cochrane Library, PsycINFO, and 2 electronic databases to identify studies published up to October 2023 with data on the correlates of demoralization. Two researchers independently reviewed references, extracted data, and assessed data quality. Meta-analysis was performed using R4.1.1 software.
Results
Thirty-eight studies were included in this meta-analysis. For the most studied sociodemographic correlates, demoralization was negatively correlated with income (z = −0.29, 95% CI: −0.51, −0.02), education (z = − 0.11, 95% CI: − 0.16, −0.05), and age (z = −0.45, 95%CI: −0.75, −0.01). For the most studied clinical correlates, demoralization was positively correlated with symptom burden (z = 0.37, 95% CI: 0.22, 0.50) and negatively correlated with quality of life (z = −0.40, 95% CI: −0.54, −0.24). For the most studied psychosocial correlates, demoralization was negatively correlated with social support (z = −0.39, 95% CI: −0.51, −0.26) and positively correlated with anxiety (z = 0.65, 95% CI: 0.56, 0.73), depression (z = 0.61, 95% CI: 0.54, 0.67), and suicidal ideation (z = 0.48, 95% CI: 0.34, 0.60).
Significance of results
Demoralization showed either positive or negative associations with sociodemographic, clinical, and psychological variables. More research is needed to explore the underlying mechanisms to develop effective interventions. This review provides information on the factors associated with demoralization in cancer patients, which can be used to inform strategies for clinical care providers.
We make theoretical comparisons among five coefficients—Cronbach’s α, Revelle’s β, McDonald’s ωh, and two alternative conceptualizations of reliability. Though many end users and psychometricians alike may not distinguish among these five coefficients, we demonstrate formally their nonequivalence. Specifically, whereas there are conditions under which α, β, and ωh are equivalent to each other and to one of the two conceptualizations of reliability considered here, we show that equality with this conceptualization of reliability and between α and ωh holds only under a highly restrictive set of conditions and that the conditions under which β equals ωh are only somewhat more general. The nonequivalence of α, β, and ωh suggests that important information about the psychometric properties of a scale may be missing when scale developers and users only report α as is almost always the case.
As avionics systems become increasingly complex, traditional fault prediction methods are no longer sufficient to meet modern demands. This paper introduces four advanced fault prediction methods for avionics components, utilising a multi-step prediction strategy combined with a stacking regressor. By selecting various standard regression models as base regressors, these base regressors are first trained on the original data, and their predictions are subsequently used as input features for training a meta-regressor. Additionally, the Tree-structured Parzen Estimator (TPE) algorithm is employed for hyperparameter optimisation. The experimental results demonstrate that the proposed stacking regression methods exhibit superior accuracy in fault prediction compared to traditional single-model approaches.
Despite growing awareness of the mental health damage caused by air pollution, the epidemiologic evidence on impact of air pollutants on major mental disorders (MDs) remains limited. We aim to explore the impact of various air pollutants on the risk of major MD.
Methods
This prospective study analyzed data from 170 369 participants without depression, anxiety, bipolar disorder, and schizophrenia at baseline. The concentrations of particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), particulate matter with aerodynamic diameter > 2.5 μm, and ≤ 10 μm (PM2.5–10), nitrogen dioxide (NO2), and nitric oxide (NO) were estimated using land-use regression models. The association between air pollutants and incident MD was investigated by Cox proportional hazard model.
Results
During a median follow-up of 10.6 years, 9 004 participants developed MD. Exposure to air pollution in the highest quartile significantly increased the risk of MD compared with the lowest quartile: PM2.5 (hazard ratio [HR]: 1.16, 95% CI: 1.09–1.23), NO2 (HR: 1.12, 95% CI: 1.05–1.19), and NO (HR: 1.10, 95% CI: 1.03–1.17). Subgroup analysis showed that participants with lower income were more likely to experience MD when exposed to air pollution. We also observed joint effects of socioeconomic status or genetic risk with air pollution on the MD risk. For instance, the HR of individuals with the highest genetic risk and highest quartiles of PM2.5 was 1.63 (95% CI: 1.46–1.81) compared to those with the lowest genetic risk and lowest quartiles of PM2.5.
Conclusions
Our findings highlight the importance of air pollution control in alleviating the burden of MD.
A high-energy pulsed vacuum ultraviolet (VUV) solid-state laser at 177 nm with high peak power by the sixth harmonic of a neodymium-doped yttrium aluminum garnet (Nd:YAG) amplifier in a KBe2BO3F2 prism-coupled device was demonstrated. The ultraviolet (UV) pump laser is a 352 ps pulsed, spatial top-hat super-Gaussian beam at 355 nm. A high energy of a 7.12 mJ VUV laser at 177 nm is obtained with a pulse width of 255 ps, indicating a peak power of 28 MW, and the conversion efficiency is 9.42% from 355 to 177 nm. The measured results fitted well with the theoretical prediction. It is the highest pulse energy and highest peak power ever reported in the VUV range for any solid-state lasers. The high-energy, high-peak-power, and high-spatial-uniformity VUV laser is of great interest for ultra-fine machining and particle-size measurements using UV in-line Fraunhofer holography diagnostics.
Natural infection by Trichinella sp. has been reported in humans and more than 150 species of animals, especially carnivorous and omnivorous mammals. Although the presence of Trichinella sp. infection in wild boars (Sus scrofa) has been documented worldwide, limited information is known about Trichinella circulation in farmed wild boars in China. This study intends to investigate the prevalence of Trichinella sp. in farmed wild boars in China. Seven hundred and sixty-one (761) muscle samples from farmed wild boars were collected in Jilin Province of China from 2017 to 2020. The diaphragm muscles were examined by artificial digestion method. The overall prevalence of Trichinella in farmed wild boars was 0.53% [95% confidence interval (CI): 0.51–0.55]. The average parasite loading was 0.076 ± 0.025 larvae per gram (lpg), and the highest burden was 0.21 lpg in a wild boar from Fusong city. Trichinella spiralis was the only species identified by multiplex polymerase chain reaction. The 5S rDNA inter-genic spacer region of Trichinella was amplified and sequenced. The results showed that the obtained sequence (GenBank accession number: OQ725583) shared 100% identity with the T. spiralis HLJ isolate (GenBank accession number: MH289505). Since the consumption of farmed wild boars is expected to increase in the future, these findings highlight the significance of developing exclusive guidelines for the processing of slaughtered farmed wild boar meat in China.
In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
In this work, the Riemann–Hilbert (RH) problem is employed to study the multiple high-order pole solutions of the cubic Camassa–Holm (cCH) equation with the term characterizing the effect of linear dispersion under zero boundary conditions and nonzero boundary conditions. Under the reflectionless situation, we generalize the residue theorem and obtain the multiple high-order pole solutions of cCH equation by solving an algebraic system. During the process of establishing the solution of RH problem, to simplify the calculations involving the implicitly expressed of variables (x, t) in the solution, we introduce a new scale (y, t) to ensure the solution of RH problem is explicitly expressed with respect to it. Finally, the exact solutions are obtained for cases involving one high-order pole and N high-order poles.