This paper introduces a new framework for high-dimensional covariance matrix estimation, the Blockwise Exponential Covariance Model (BECM), which extends the traditional block-partitioned representation to the log-covariance domain. By exploiting the block-preserving properties of the matrix logarithm and exponential transformations, the proposed model guarantees strict positive definiteness while substantially reducing the number of parameters to be estimated through a blockwise log-covariance parameterization, without imposing any rank constraint. Within each block, intra- and inter-group dependencies are parameterized through interpretable coefficients and kernel-based similarity measures of factor loadings, enabling a data-driven representation of nonlinear groupwise associations. Using monthly stock return data from the U.S. stock market, we conduct extensive rolling-window tests to evaluate the empirical performance of the BECM in minimum-variance portfolio construction. The results reveal three main findings. First, the BECM consistently outperforms the Canonical Block Representation Model (CBRM) and the native 1/N benchmark in terms of out-of-sample Sharpe ratios and risk-adjusted returns. Second, adaptive determination of the number of clusters through cross-validation effectively balances structural flexibility and estimation stability. Third, the model maintains numerical robustness under fine-grained partitions, avoiding the loss of positive definiteness common in high-dimensional covariance estimators. Overall, the BECM offers a theoretically grounded and empirically effective approach to modeling complex covariance structures in high-dimensional financial applications.

Association between obstructive sleep apnea and metabolic profiles across sleep stages in pediatrics.

Covariance matrices estimated from short, noisy, and non-Gaussian financial time series are notoriously unstable. Empirical evidence suggests that such covariance structures often exhibit power-law scaling, reflecting complex, hierarchical interactions among assets. Motivated by this observation, we introduce a power-law covariance model to characterize collective market dynamics and propose a hybrid estimator that integrates Random Matrix Theory (RMT) with deep Residual Neural Networks (ResNets). The RMT component regularizes the eigenvalue spectrum in high-dimensional noisy settings, while the ResNet learns data-driven corrections that recover latent structural dependencies encoded in the eigenvectors. Monte Carlo simulations show that the proposed ResNetbased estimators consistently minimize both Frobenius and minimum-variance losses across a range of population covariance models. Empirical experiments on 89 cryptocurrencies over the period 2020–2025, using a training window ending at the local Bitcoin peak in November 2021 and testing through the subsequent bear market, demonstrate that a two-step estimator combining hierarchical filtering with ResNet corrections produces the most profitable and well-balanced portfolios, remaining robust across market regime shifts. Beyond finance, the proposed hybrid framework applies broadly to highdimensional systems described by low-rank deformations of Wishart ensembles, where incorporating eigenvector information enables the detection of multiscale and hierarchical structure that is inaccessible to purely eigenvalue-based methods.

This study aimed to determine whether bipedal static balance performance, assessed under eyes-open and eyes-closed conditions, contributes to countermovement jump (CMJ) performance when sex-related differences and postural stability parameters are statistically controlled. Sixty-four physically active adults (32 females and 32 males; aged 18–45 years) who regularly engaged in resistance-based exercise participated in the study. Static balance was evaluated in a standardized bipedal stance using the TecnoBody D-Wall system by quantifying center-of-pressure (CoP) ellipse area under eyes-open and eyes-closed conditions. CMJ performance was assessed using the same system, with jump height, flight time, total mechanical work, maximum force, and maximum absolute power recorded. Statistical analyses were performed using IBM SPSS Statistics. Data normality was assessed with the Shapiro–Wilk test. Sex-based differences in anthropometric variables were analyzed using independent samples t-tests or Mann–Whitney U tests, as appropriate. To examine the effect of sex on CMJ performance while controlling for static balance parameters, analysis of covariance (ANCOVA) models were applied, with eyes-open and eyes-closed CoP ellipse areas entered as covariates. ANCOVA results revealed significant main effects of sex on several CMJ outcomes, including flight time, total work, maximum force, and maximum absolute power (p 0.05), with large effect sizes. Eyes-open static balance did not significantly influence any CMJ parameter. In contrast, the eyes-closed CoP ellipse area demonstrated a borderline significant effect on total mechanical work (p = 0.050), suggesting a limited contribution of proprioceptive-dominant postural control to mechanical work production independent of sex. These findings indicate that bipedal static balance, as quantified by CoP ellipse area, does not substantially explain variability in vertical jump performance beyond sex-related effects. This conclusion is specific to static balance conditions and should not be generalized to dynamic balance or functional stability tasks. Overall, static postural control and explosive jump performance appear to represent largely independent motor capacities, underscoring the importance of task-specific assessment and training strategies in athletic populations.Keywords: Countermovement Jump, Digital Posturography Technologies, Static Balance.

The Global Diet Quality Score (GDQS) is a recently developed food-based index that evaluates both healthy and unhealthy dietary components and has been linked to non-communicable disease risk. However, limited evidence exists regarding its relationship with metabolic and inflammatory markers among obese individuals. This study aimed to examine the association between GDQS and cardio-metabolic risk factors, lipid accumulation product (LAP), and systemic inflammation in obese adults. In this cross-sectional study, 302 obese participants (body mass index [BMI] ≥ 30kg/m²) aged 18-50 years were recruited. Dietary intake was assessed using a validated food frequency questionnaire, and GDQS was calculated from 25 food groups. Anthropometric indices, blood pressure, fasting blood glucose, lipid profile, hemoglobin (Hb) A1c, insulin, homeostasis model assessment of insulin resistance (HOMA-IR), high sensitive C-reactive protein (hs-CRP), and LAP were measured. Participants were classified into tertiles of GDQS, and differences in metabolic parameters across tertiles were analyzed using analysis of covariance and multinomial regression models, adjusting for potential confounders. Higher GDQS tertiles were associated with significantly lower systolic blood pressure (P = 0.048), total cholesterol, triglycerides (both P < 0.05), hs-CRP (P < 0.001), and LAP (P = 0.026). No significant associations were observed between GDQS and other parameters. Greater adherence to a high-quality diet, as reflected by GDQS, is linked to favorable lipid profiles, reduced inflammation, and lower LAP in obese adults. These findings support the GDQS as a valuable tool for assessing diet quality and highlight the importance of dietary improvement in managing obesity-related metabolic risk.

An exploration of generational status and enculturation as putative protective factors for disordered eating behaviors and cognitions among college students.

Purpose: The purpose of this study is to explore whether higher educational institutes' e-learning programs on Facebook groups enhance Students' intention to use (IU) E-learning Programs or not by identifying influential determinants. By drawing on the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), Theory of Reasoned Action (TRA), and Student Engagement (SE) theory, this study assessed the role of SE in e-learners’ IU on Facebook perspectives. Methodology: This research applies quantitative research methodology using non-probability purposive sampling of a total of 211 higher secondary to post-graduate students in higher educational institutes, private and public universities in Bangladesh who are familiar and associated with e-learning programs of Facebook groups. Structural equation modeling (SEM) and mediation analysis as the data analysis method have been implemented by applying Co-Variance Structural Equation Modeling (CB-SEM). Findings: The result reveals that perceived ease of use (PEOU) and perceived usefulness (PU) from TAM, and social influence (SI) from the UTAUT model significantly affecting students' intention to use (IU) Facebook groups, with the strong effect of mediation of students' engagement (SE), except for the insignificant impact of hedonic motivation (HE). Practical Implications: Following the studies' implications and future recommendations, educators and e-learning providers should make Facebook groups more effective and enjoyable by integrating engagement with educational usage. Originality/Value: The originality of this study is in extending the four separate theories and models in enhancing students' future use of Facebook groups for e-learning programs, with the engagement level as a mediator in 'Meta.' Limitations: The present study employs a non-probability sampling method without the consideration of cross-cultural concerns and socio-demographic factors, focusing on other social media. Drawing on these issues, future academics should approach PLS-SEM, LISREL, and workable moderating variables.

Habituation to Dietary Proteins with Higher Tryptophan Levels Increases Fasted and Postprandial Concentrations of Tryptophan and Its Metabolites in Brain Regions of the Growing Pig.

Long-term effect of pain history and experimental pain responses on adolescents' quality-of-life: A cohort study.

Association Between Omega-3 Supplement Use and Cognitive Function in Korean Older Adults: An 8-Year Longitudinal Cohort Study

ABSTRACT The Hubble parameter, $H(z)$, plays a crucial role in understanding the expansion history of the Universe and constraining the Hubble constant, $\mathrm{H}_0$. The Cosmic Chronometers (CC) method provides an independent approach to measuring $H(z)$, but existing studies either neglect off-diagonal elements in the covariance matrix or use an incomplete covariance matrix, limiting the accuracy of $\mathrm{H}_0$ constraints. To address this, we use a Positive-Definite Covariance Network (PD-CovNet) to simulate the full $33 \times 33$ covariance matrix based on a previously published $15 \times 15$ covariance matrix. Hyperparameters are chosen via leave-one-z-out validation, and performance is benchmarked against a Gaussian-process (GP) baseline. Under identical five-fold cross-validation over redshift groups, we prove that PD-CovNet is a reliable generator of the full covariance compared to the GP baseline. Using this full PD-CovNet-simulated covariance alongside three comparators with different covariance specifications, we constrain $\mathrm{H}_0$ with two independent methods (EMCEE and GP). Across all covariance specifications and both constraint methods, standardized differences and two-sided p-values show no statistically meaningful shift in the central value of the constrained $\mathrm{H}_0$. However, the precision of the constrained $\mathrm{H}_0$ depends on both covariance and method: EMCEE is uniformly more precise than GP once covariance is modelled; within a fixed method, incorporating more covariance reduces precision; and PD-CovNet hyperparameters have a modest effect on uncertainty. These results indicate the importance of accurate covariance modelling in CC-based $\mathrm{H}_0$ constraints.

IntroductionAdolescent idiopathic scoliosis (AIS) involves three-dimensional structural spinal changes, frequently accompanied by scapular dyskinesis (SD) and proprioceptive dysfunction. Although physiotherapeutic scoliosis-specific exercises effectively correct spinal alignment, their efficacy in addressing SD and associated sensorimotor deficits remains underexplored. This randomised controlled trial (RCT) will evaluate whether integrating upper limb proprioceptive neuromuscular facilitation (PNF) with conventional physical therapy yields synergistic improvements in scapular kinematics and proprioceptive function in AIS.Methods and analysisThis single-centre RCT will be conducted at the Department of Rehabilitation Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 48 adolescents with AIS will be randomly assigned to either a control group (n=24) receiving conventional physical therapy or an experimental group (n=24) receiving combined conventional therapy and upper limb PNF interventions. Both groups will follow a structured 60 min rehabilitation programme, administered five sessions per week for 8 weeks (including two outpatient sessions and three home training sessions per week). Follow-up assessments will be conducted at 12 weeks postintervention to evaluate the maintenance of therapeutic effects. Primary outcomes will include the scapular balance angle and the active relocation test for shoulder proprioception. Secondary outcomes will comprise the scapular index, the lateral scapular slide test, normalised surface electromyography (root mean square, %muscle activation degree) of the upper trapezius, lower trapezius, serratus anterior, posterior deltoid and infraspinatus during standardised tasks, posture analysis, Cobb angle, angle of trunk rotation and the Simplified Chinese version of the Scoliosis Research Society-22 questionnaire for health-related quality of life. Data will be analysed using Analysis of Covariance and linear mixed-effects models, adjusted for baseline values, following the intention-to-treat principle.Ethics and disseminationThe study protocol has been approved by the Ethics Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology (Approval No. TJ-IEB2025-018) and has been registered on ClinicalTrials.gov. The findings will be disseminated through peer-reviewed journal publications, conference presentations and media releases.Trial registration numberChiCTR2500099252.

This review analyzes how Federal Reserve easingfederal funds rate reductions and quantitative easing (QE)feeds into the inputs of meanvariance optimization (expected returns, variances, and covariances) and how those shifts propagate to institutional rebalancing under stress. Drawing on evidence from the Dot-Com bust (20002002), the Global Financial Crisis (20082009), and the COVID-19 period (20202022), it integrates theory on discount-rate channels and QE transmission (portfolio-rebalancing, signaling, and liquidity) with estimates mapped to MVO parameters. Across episodes, easing compresses sovereign and credit yields, reshapes cross-asset correlation structures, and can induce benchmark-constrained institutions to rebalance procyclically, amplifying short-horizon volatility. The main gap is the limited treatment of policy-driven regime shifts and liquidity frictions in dynamic MVO; addressing it has practical relevance for regime-aware covariance modeling, liquidity-adjusted risk budgets, and policy-contingent rebalancing rules.

Globally, human population structure is quickly trending older, increasing the prevalence and systemic burden of age-related skeletal disorders such as osteoporosis. Osteoporosis is characterized by the loss of bone mass, including trabecular bone tissue, leading to skeletal fracture. Although clinically important, fundamental questions remain about normal trabecular bone variation and age-related bone loss. In this study, we use free-ranging rhesus macaques (Macaca mulatta) from the Cayo Santiago Field Station to explore variation in trabecular bone structure. We measured several aspects of trabecular bone structure (maximum and mean bone volume fraction, degree of anisotropy, and trabecular thickness) across the elbow (humerus, ulna, radius), hip (proximal femur), and knee (distal femur, tibia). Analyses of covariance models assessed factors influencing bone structure, including body mass, demography (age, sex, matriline), as well as indices of sociality and early life adversity. Point cloud models of prime and postprime age groups visualized age-related differences in bone structure. We observed significant variation in trabecular bone morphology (max and mean bone volume fraction, degree of anisotropy, and trabecular thickness) across both bones and joints. Sex influenced trabecular thickness, with thicker trabeculae in males. Max and mean bone volume fraction as well as trabecular thickness were positively associated with body mass. Age was associated with significantly lower values of mean bone volume fraction, specifically in the hind limb. We observed significant bone loss specifically in the femoral head and neck. There were no associations of trabecular bone structure with either sociality or early life adversity in this sample. This study provides a comprehensive view of trabecular bone variation by region, sex, mass, and age contextualized by social factors.

Introduction: The Mediterranean diet (MD) has been linked to better cognition, but evidence in older adults at high dementia risk is limited. Moreover, the traditional Mediterranean Diet Adherence Screener (MEDAS) counts daily wine consumption as a beneficial component, which may distort genuine diet–cognition relationships. Objective: Evaluate whether MD adherence, as measured with the original MEDAS (MEDAS-O) versus a version that reverses the wine item (MEDAS-R), is associated with cognitive function in Portuguese adults aged 55–85 years at increased dementia risk. Methodology: The sample comprised 75 participants from the NUTRIMIND randomised controlled trial (mean age 70.5 ± 7.0 years). MD adherence was evaluated using the original version of MEDAS (MEDAS-O) and an adapted version with a reverse score in the wine question (MEDAS-R). Cognitive function was assessed via the Montreal Cognitive Assessment (MoCA), Addenbrooke’s Cognitive Examination Revised (ACE-R) and Mini-Mental State Examination (MMSE). Statistical analysis was performed using Analysis of Covariance (ANCOVA) models adjusted for age, sex, BMI, education, and physical activity. Results: MEDAS-R was positively associated with better MMSE performance (p = 0.043) and showed a borderline association with the MoCA (p = 0.051), but not with the ACE-R score (p = 0.356). No association was found between MEDAS-O and cognitive function. Better cognitive scores were more frequently observed among participants with higher education (p < 0.001). Conclusions: Reversing the wine item changes how MEDAS relates to cognitive function. These findings support re-evaluating how wine is scored in MD adherence measures.

To compare long-term regressive effects on pigment epithelial detachment (PED) between aflibercept and faricimab in type 1 macular neovascularization (MNV). We analyzed 94 eyes from 92 patients diagnosed with type 1 MNV using multimodal imaging. Seventy-one eyes received intravitreal aflibercept injections (IVA group), and 23 received intravitreal faricimab injections (IVFa group). After three consecutive monthly injections, intervals were adjusted in 2-4 week increments within drug-specific windows (IVA, 4-12 weeks; IVFa, 8-16 weeks) through 1 year. The maximum height (MH) and horizontal maximum diameter (H-MD) of PED were measured using optical coherence tomography before treatment and at 3 months and 1year post-treatment. We also assessed associations between PED change and 1-year dry macula, and explored visual outcomes with using analysis of covariance and logistic models. MH decreased in both IVA (184 ± 176→126 ± 153μm at 3 months, P = 0.0003; 124 ± 135μm at 1 year, P = 0.0005) and IVFa (162 ± 124→83 ± 65μm, P = 0.0056; 86 ± 71μm, P = 0.0053). The mean change in MH was not significantly different between groups (P = 0.244). H-MD did not show significant regression in either group. IVFa required fewer injections (6.17 ± 0.39 vs. 7.90 ± 1.99/year; P < 0.0001) and achieved a longer final intended injection interval (14.17 ± 2.53 vs. 8.64 ± 2.90 weeks; P < 0.0001). In multivariable linear regression for percent MH change at 1 year, annual injection number was positively associated with percent change (β = 7.62% points/injection, P = 0.012), whereas drug type was not (P = 0.633), adjusting for baseline MH (β = -0.078/µm, P = 0.016; all VIFs < 2). At 1 year, MH was lower in dry vs. wet macula (90 ± 82 vs. 186 ± 185μm; P = 0.0004). For vision, ≥ 0.2logMAR gain was predicted by CMT decrease (OR ≈ 1.56 per 100μm decrease; P = 0.045), while percent PED change was not significant (P = 0.283). In a treat-and-extend regimen with different label constraints, 1-year PED regression was similar for IVA and IVFa and was achieved with less treatment burden in IVFa. PED regression aligned with dry macula rather than with large visual gains, which instead tracked with retinal thickness recovery.

Background: The molecular mechanisms underlying colchicine’s benefits after myocardial infarction (MI) remain unclear. This study aimed to investigate the impact of colchicine on the plasma proteome. Methods: Plasma samples were collected from a subset of 203 COLCOT trial participants at baseline and at six months. Proteomic profiling was performed using a targeted multiple-reaction monitoring mass spectrometry assay, while inflammatory biomarkers were quantified using electrochemiluminescence-based multiplex and enzyme-linked immunosorbent assays. The changes from baseline to six months were analyzed using analysis of covariance models adjusted for baseline values either using the original data or log-transformed data, depending on the distribution. The mean percentage reductions by colchicine are presented for in vitro assays and the logarithm of the ratio of LPS+colchicine/LPS were tested against zero. Results: Reductions in the plasma concentrations of interleukin-12p70 (IL-12p70), IL-12/IL-23p40 (p40) subunit, IFN-γ, and IL-17A were observed in the colchicine group compared with the placebo group (adjusted geometric mean % changes of -42.8% vs. 0.4%, p = 0.007 for IL-12p70 and -23.7% vs. -4.1%, p = 0.053 for IFN-γ; adjusted mean changes of -12.8 pg/ml vs. 7.5 pg/ml, p = 0.003 for IL-12/IL-23p40 and -2.1 pg/ml vs. 0.2 pg/ml, p = 0.038 for IL-17A). Decreases over time in plasma IL-6 and IL-1α concentrations also occurred in the colchicine group compared with placebo (adjusted geometric mean % changes of -51.1% vs. -40.8%, p = 0.055 and -18.9% vs. 7.6%, p = 0.052, respectively). These effects were supported by in vitro assays that demonstrated colchicine-induced reductions of secretion of IL-12 (-41.8%, p=0.023), IL-23 (-21.0%, p=0.014) and IL-6 (-46.7%, p&lt;0.001) by lipopolysaccharide-stimulated THP-1 macrophages. The proteomic panel showed that colchicine, compared with placebo, reduced additional inflammation-related biomarkers including alpha-1-acid glycoprotein, complement factor D and lysozyme C (adjusted geometric mean % changes of -35.6% vs. -28.1%, p = 0.026; -13.2% vs. -0.2%, p = 0.020; and -10.8% vs. -3.3%, p = 0.041, respectively). Conclusions: Low-dose colchicine treatment after MI substantially reduced IL-12 and IL-23 signaling, suggesting important effects on Th1 and Th17 inflammatory pathways. The effects of colchicine on IL-6 and IL-1α also demonstrate its effects on NLRP3 inflammasome activity.

The role of sedimentary heterogeneity in reactive transport processes is becoming increasingly important as closed open-pit lignite mines are converted into post-mining lakes or pumped hydropower storage reservoirs. Flooding of the open pits introduces constant oxygen-rich inflows that reactivate pyrite oxidation within internal mine dumps. A reactive transport model coupling groundwater flow, advection–diffusion–dispersion, and geochemical reactions was applied to a 2D cross-section of a water-saturated mine dump to determine the processes governing pyrite oxidation. Spatially correlated fields representing permeability and pyrite distributions were generated via exponential covariance models reflecting the end-dumping depositional architecture, supported by a suite of scenarios with systematically varied correlation lengths and variances. Simulation results covering a time span of 100 years quantify the impact of heterogeneous permeability fields that result in preferential flow paths, which advance tracer breakthrough by ~15 % and increase the cumulative solute outflux up to 139 % relative to the homogeneous baseline. Low initial pyrite concentrations (0.05 wt %) allow for deeper oxygen penetration, extending oxidation fronts over the complete length of the modeling domain. Here, high initial pyrite concentrations (0.5 wt %) confine reactions close to the inlet. Kinetic oxidation allows for more precise simulation of redox dynamics, while equilibrium assumptions substantially reduce the computational time (&gt;10×), but may oversimplify the redox system. We conclude that reliable risk assessments for post-mining redevelopment should not simplify numerical models by assuming average homogeneous porosity and mineral distributions, but have to incorporate site-specific spatial heterogeneity, as it critically controls acid generation, sulfate mobilization, and the timing of contaminant release.

The objective of this study was to investigate the population pharmacokinetics of sarafloxacin following a single oral administration at a dose of 20 mg/kg body weight (BW) in Yellow River carp (Cyprinus carpio haematopterus) reared at 24°C, and to provide a scientific basis for its rational use in aquaculture. Blood samples were collected from the tail vein of six fish at each predetermined time point: 0.25, 0.5, 1, 2, 4, 6, 8, 12, 16, 24, 36, 46, 48, 92, 96, 120, and 144 h post-administration, using a sparse sampling design. Blood was collected only four times per fish, and six fish were sampled at each time point. Plasma concentrations of sarafloxacin were measured using high-performance liquid chromatography (HPLC), and the drug remained quantifiable in plasma up to 120 h post-administration. Population pharmacokinetic modeling was conducted using nonlinear mixed-effects modeling to characterize both the typical population parameters (fixed effects) and inter-individual variability (random effects). Covariate and covariance models were incorporated to account for variability and improve model predictability under sparse sampling conditions. The final population model estimated typical values (tv) and inter-individual coefficients of variation (CV%) for the absorption rate constant (tvKa), apparent volume of distribution (tvV), and clearance (tvCL) as 14.889 h-1 (CV: 3.04%), 31.573 L/kg (CV: 0.39%), and 2.885 L/h/kg (CV: 0.38%), respectively. Based on the calculated AUC/MIC or Cmax/MIC ratios, the current oral dosing regimen of 20 mg/kg BW appears to be effective against pathogens with MIC values below 0.05 μg/mL.

Recent cosmological observations have achieved high-precision measurements of the Universe's expansion history, prompting the use of nonparametric methods such as Gaussian processes (GP) regression. We apply GP regression for reconstructing the Hubble parameter using CC data, with improved covariance modeling and latest study in CC data. In addition, we perform a joint analysis combining BAO, SN Ia, and a CMB prior, which constitutes the standard and most constraining framework in cosmology. By comparing reconstructions in redshift space z and transformed space log(z+1), we evaluate six kernel functions using nested sampling (NS) and approximate Bayesian computation rejection (ABC rejection) methods and analyze the construction of Hubble constant H 0 in different models. Our analysis demonstrates that reconstructions in log(z+1) space remain physically reasonable, offering a viable alternative to conventional z space approaches, while the introduction of non-diagonal covariance matrices in CC data leads to degraded reconstruction quality, suggesting that simplified diagonal forms may be preferable for reconstruction. And we find robust evidence for an observable deviation from the ΛCDM model under the joint constraints of BAO and SNe Ia data with a CMB prior. These findings underscore the importance of task-specific kernel selection in GP-based cosmological inference. In particular, our findings suggest that careful preliminary screening of kernel functions, based on the physical quantities of interest, is essential for reliable inference in cosmological research using GP.