Search Results (1,505)

Background: During the COVID-19 pandemic, uncertainty regarding the safety of kidneys from COVID-19-positive donors led to a reduction in kidney transplants and increased organ non-use in the United States. This study aims to evaluate whether donor COVID-19 positivity is associated with one-year post-transplant estimated glomerular filtration rate (eGFR) among kidney transplant recipients. Methods: This retrospective cohort study used data from the United States Organ Procurement and Transplantation Network (OPTN) 2020–2024. Donor COVID-19 status was determined by the SARS-CoV-2 nucleic acid amplification technique (NAT) and antibody test results. The main outcome was recipients’ one-year eGFR, estimated by the CKD-EPI 2021 formula. Linear regression models were used to compare the mean one-year eGFR among donor COVID-19 groups, adjusted by inverse probability of treatment weights. Interaction terms of donor acute kidney injury status and race were assessed to evaluate effect modification. Results: Among 38,199 included kidney transplant recipients, 1090 (2.9%) received kidneys from donors with active COVID-19 infection, 423 (1.1%) from donors with resolved infection, and 36,686 (96.0%) from COVID-19-negative donors. After weighting and adjustment, there was no significant difference in one-year eGFR for recipients of kidneys from donors with active COVID-19 (mean difference, 0.05 [95% CI, −1.08 to 1.18]) or resolved infection (mean difference, −0.27 [95% CI, −2.19 to 1.64]) compared with COVID-19-negative donors. Neither donor AKI nor donor race modified the association between donor COVID-19 status and one-year eGFR. Conclusions: This study suggests that kidneys from COVID-19-positive donors may be a viable option without compromising short-term allograft function as measured by 1-year eGFR. Full article

Waveform agility improves anti-reconnaissance and anti-jamming capability in diverse inverse synthetic aperture radar (ISAR) scenarios, but it also breaks the phase variation assumptions used for conventional coherent processing. For cooperative bistatic ISAR radars, the problem is further complicated by the bistatic geometry and phase evolution induced by synchronization. This paper develops a joint coherent integration method for a cooperative bistatic radar with simultaneous pulse width (PW) and pulse repetition interval (PRI) agility. Firstly, we establish and analyze a bistatic geometric model to reveal key integration problems under agile waveforms, and then derive the coherent processing interval (CPI) local polynomial description for bistatic delay, Doppler and acceleration. On this basis, the matched filter response of each agile pulse is analyzed under the fixed-bandwidth assumption with linear frequency modulation (LFM), showing that PW agility produces a compressed peak displacement and an additional deterministic phase term, whereas PRI agility converts slow-time coherent integration into a nonuniformly sampled spectral estimation problem. To solve this problem, a joint fast and slow-time compensation route is derived, together with a bistatic-specific parameter design method that connects coherent integration tolerances with the bistatic angle and the observable projection vector. Finally, we test the performance of the proposed joint integration method in multiple scenarios and verify its effectiveness and robustness, which enhances detection performance and resolution for target localization. Full article

While minimalist kinetic models effectively capture the acute inverse coupling between Hepatitis B (HBV) and Hepatitis Delta (HDV), they often fail to account for the asymptotic stability and long-term viral plateaus observed during clinical therapy. In this work, we present an expanded compartmental framework integrating the non-linear dynamics of susceptible (S) and infected (I) hepatocyte populations, explicitly incorporating the satellite nature of HDV. Using the next-generation matrix method and Lyapunov stability theory, we analytically derive R₀ and prove the global attractivity of the endemic equilibrium. We demonstrate that “Target Cell Limitation” serves as the fundamental homeostatic governor. A transcritical bifurcation at threshold drug efficacy ε ≈ 0.9 marks the mathematical boundary between chronic persistence and viral extinction. Full article

Background: Physical activity is a key modifiable factor influencing healthy aging, yet data on activity patterns and their physiological correlates in older adults from Central Asia remain limited. Understanding these relationships is essential for informing region-specific health promotion strategies. Objectives: This study assessed physical activity levels among urban-dwelling older adults in Astana, Kazakhstan, and examined associations between activity level, body composition, visceral fat accumulation, metabolic indicators, and muscle strength. Methods: A cross-sectional study was conducted among 608 adults aged ≥60 years (median age: 68 years; 82.1% women). Physical activity was measured using the validated Physical Activity Scale for the Elderly (PASE). Anthropometric and body composition indicators, including BMI, total and visceral fat, skeletal muscle mass, and handgrip strength, were evaluated. Spearman correlation and linear regression analyses were applied. The analyses were exploratory and did not include adjustment for potential confounders such as sex, chronic disease burden, or socioeconomic status; therefore, the observed associations should be interpreted with caution. Results: The median PASE score was 55.55, with 61.8% of participants demonstrating moderate activity levels, primarily through walking and household tasks. In analyses without adjustment for potential confounding factors, PASE scores showed weak inverse associations with visceral fat (ρ = −0.214; p < 0.001) and waist-to-hip ratio (ρ = −0.154; p < 0.001), as well as weak positive associations with handgrip strength. Across the reported significant associations, correlation coefficients ranged from |ρ| = 0.103 to 0.235, and the explanatory capacity of the regression models was low, with R² values ranging from 0.6% to 8.2%. Conclusions: Higher habitual physical activity may be linked to selected bioelectrical impedance parameters, WHR, and handgrip strength among urban older adults. Given the cross-sectional design, causal interpretation should be approached with caution. These findings provide meaningful regional baseline evidence for future longitudinal and intervention studies on physical activity and healthy aging in Central Asia. Full article

Background: Vitamin D deficiency is highly prevalent in older adults and has been increasingly recognised as a potential contributor to cognitive decline, depressive symptomatology, and functional impairment. However, the clinical significance of specific 25-hydroxyvitamin D thresholds in relation to this multidomain geriatric phenotype remains incompletely characterised. Methods: We conducted a cross-sectional study of 1438 consecutive patients aged 65 years or older admitted for comprehensive geriatric assessment at a tertiary centre in Cluj-Napoca, Romania, between January 2023 and November 2025. Serum 25-hydroxyvitamin D [25(OH)D] was categorised as deficient (<20 ng/mL), insufficient (20–30 ng/mL), or sufficient (≥30 ng/mL). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE), depressive symptoms using the Geriatric Depression Scale (GDS-30 and GDS-SF), and functional status using Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL). Multivariable linear regression analyses were adjusted for age, body mass index, serum albumin, and estimated glomerular filtration rate (eGFR). Results: Suboptimal vitamin D status was highly prevalent in this geriatric cohort, with 43.3% of participants meeting criteria for frank deficiency (<20 ng/mL). Lower 25(OH)D concentrations were significantly associated with worse cognitive performance, greater depressive symptom burden, and higher functional dependency. Serum 25(OH)D correlated positively with MoCA and MMSE scores and inversely with ADL, IADL, and GDS scores. In adjusted models, vitamin D remained independently associated with MoCA, IADL, and GDS. Stratified analyses suggested that the main clinical deterioration occurred below 20 ng/mL, while the 20–30 ng/mL range behaved as an intermediate phenotype closer to sufficiency than to frank deficiency. Conclusions: In this large cohort of hospitalised older adults, serum 25(OH)D deficiency below 20 ng/mL was independently associated with poorer cognition, more depressive symptoms, and greater functional impairment. These findings support routine vitamin D assessment in geriatric practice and suggest that the <20 ng/mL threshold identifies a clinically relevant high-risk phenotype. Full article

Hyperspectral imaging (HSI) provides rich spatial and spectral information for remote sensing, mineral exploration, and biomedical analysis, but its limited spatial resolution and sensor imperfections lead to blurred, noisy, and mixed-pixel observations. Addressing these degradations jointly—rather than sequentially—has been shown to improve physical interpretability, yet existing joint deblurring–unmixing methods rely primarily on hand-crafted regularizers that do not fully exploit spatial–spectral structure. Meanwhile, recent plug-and-play (PnP) approaches applied to HSI leverage deep priors but focus solely on either deconvolution or unmixing in isolation. To bridge this gap, we formulate the joint inverse problem of hyperspectral deblurring and spectral unmixing and propose, to our knowledge, the first plug-and-play framework tailored for this coupled task using the Alternating Direction Method of Multipliers (ADMM) and a pretrained deep denoiser (DnCNN) as an implicit PnP prior. Our method uses the natural splitting properties of ADMM to separate a physics-driven subproblem that enforces fidelity to the hyperspectral forward model, which includes linear mixing and blur under a linear, space-invariant convolution approximation, from the data-driven prior step. This synergy of model-based fidelity and learned spatial prior enables more accurate abundance estimates than those obtained with approaches relying solely on analytical regularizers. Experimental results on real hyperspectral datasets demonstrate that the proposed Plug-and-Play Joint Deconvolution and Unmixing (PnP-JDU) method outperforms conventional unmixing baselines, stand-alone PnP unmixing methods, and the Deblurring and Sparse Unmixing via the Alternating Direction Method with Total Variation (DSUnADM-TV) baseline in reconstruction and abundance accuracy metrics. Across the tested datasets and imaging conditions, PnP-JDU achieves lower RMSE, higher PSNR, lower reconstruction and abundance errors, and lower SAD values, while preserving fine spatial details and producing physically meaningful abundance maps. Full article

Background: The transition to university life is characterized by substantial changes in eating behaviors, sleep–wake organization, and lifestyle patterns. Chrononutrition-related behaviors, including meal timing and caloric distribution across the day, may influence metabolic health independently of dietary quantity, yet prospective evidence in university students remains limited. This study aimed to evaluate BMI trajectories during the first academic year and to identify chrononutrition-related behaviors associated with BMI change and clinically significant weight gain in young adults. Methods: This prospective observational study included 921 university students aged 18–24 years. BMI was assessed at university entry and after one academic year, and BMI change (Diff_BMI) was calculated. Chrononutrition-related variables included meal frequency, identity of the main meal, breakfast habits, and late eating. Multivariable linear and logistic regression models were used to evaluate independent associations between chrononutrition-related behaviors, BMI change, and clinically significant weight gain (Diff_BMI > +1 kg/m²). Results: Mean Diff_BMI was −0.45 ± 1.07 kg/m² (95% CI −0.52 to −0.38; p < 0.001). Overall, 48.2% of participants showed BMI reduction, 38.7% remained weight-stable, and 13.1% experienced BMI increases; clinically significant weight gain occurred in 7.2% of the cohort. In multivariable analysis, having dinner as the main meal (vs. lunch) was independently associated with greater BMI gain (β = +0.22 kg/m²; p = 0.004). Male sex was associated with lower BMI gain and lower odds of clinically significant weight increase. Breakfast skipping showed an inverse association with BMI change, whereas meal frequency and late eating were not independently associated with BMI trajectory after adjustment. Conclusions: The temporal distribution of caloric intake, particularly late eating patterns and shifting the principal meal toward later hours of the day, appears more strongly associated with BMI trajectory during the transition to university life than meal frequency alone. These findings support the relevance of chrononutrition-oriented strategies targeting meal timing and circadian eating behaviors in university students. Full article

High-resolution soil moisture monitoring in a lysimeter requires precise Ground-Penetrating Radar (GPR) systems that can provide clean time-domain data for a Full-Waveform Inversion (FWI) algorithm. Using high-speed Radio Frequency System-on-Module (RFSoM) devices provides flexibility in signal generation. To optimize such a system, an appropriate transmit waveform and processing pipeline need to be selected. This paper presents a performance evaluation of three GPR waveforms—impulse, Stepped-Frequency Continuous Wave (SFCW) and non-linear Frequency-Modulated Continuous Wave (FMCW/chirp)—on the same hardware setup. To ensure a fair comparison, all waveforms were tested under an identical total measurement time. Numerical simulations were performed using an electromagnetic model of the system. Physical validation was conducted in an anechoic chamber using a 4 GS/s RFSoM setup and planar elliptical dipole antennas. Simulations showed that both sinewave-based methods provide better signal-to-noise ratios (SNRs) than the impulse GPR, with the non-linear chirp achieving the best results (20.7 dB improvement compared to impulse). Experimental measurements supported these results, showing better SNR across the frequency band for the SFCW and chirp waveforms. Because of its high SNR and simple hardware implementation, the non-linear chirp was identified as the most suitable waveform for this RFSoM-based GPR system. Full article

This paper introduces and investigates a novel two-parameter sequence, termed the biparametric Appell extension (B-App-Ex) and denoted by ${\mathcal{B}}_n(x;\lambda ,\alpha )$. Standard classical Appell sequences often lack sufficient structural parameters, which can limit their operational flexibility in certain advanced spectral schemes. To address this limitation, we construct an enhanced operational framework by integrating a binomial structural kernel ${(1+w)}^{\lambda }$ with a linear exponential scaling $e^{\alpha xw}$ entirely within the Appell class. We provide a rigorous logical deduction of the fundamental properties of this sequence, including its explicit power series representation, a characteristic three-term recurrence relation, and a governing second-order differential equation (DEq.). A significant contribution of this work is the establishment of analytically exact connection and inverse connection formulas between the B-App-Ex basis and various classical orthogonal polynomial (COP) families. Numerical verification via a collocation-based projection framework demonstrates that these algebraic kernels achieve near-machine epsilon precision (≈${10}^{-15}$), remaining stable even for high-order approximations. Furthermore, by isolating the dilation factor $\alpha$, we establish an $O\left(N\right)$ computational complexity that offers a reduction in latency by approximately two orders of magnitude compared to classical matrix-based transformations. The results demonstrate that the proposed biparametric (Bip.) extension offers a versatile and highly optimized analytical template for modeling complex dynamic systems where structural shifting and spatial scaling must be tuned simultaneously. Full article

Background: Adolescent mental health is a global concern, with lifestyle factors such as diet and physical activity (PA) playing a crucial role. While the Mediterranean Diet adherence (MDA) is known for its neuroprotective benefits on mental health, the mechanisms by which they are related remain unclear. Therefore, the aim of this study was twofold: (1) to examine the associations between MDA, PA, and screen time (ST) with anxiety symptoms, depression, stress, and total psychological distress in Chilean adolescents; and (2) to determine whether PA mediates the relationship between MDA and anxiety symptoms. Methods: A cross-sectional study was conducted with 322 Chilean school-aged adolescents 158 males and 164 females (14.98 ± 1.96 years). Mental health outcomes (depression, anxiety, and stress) and lifestyle behaviors, including MDA, PA, and ST, were comprehensively assessed using validated self-reported questionnaires. Results: After adjusting for age and sex, multiple linear regression models showed that higher MDA was significantly and inversely associated with anxiety (b = −0.23, p = 0.044), stress (b = −0.25, p = 0.022), and total psychological distress (b = −0.72, p = 0.022). Conversely, ST was identified as a consistent risk factor, positively predicting higher levels of anxiety (b = 0.45, p = 0.008), stress (b = 0.42, p = 0.008), and total distress (b = 1.11, p = 0.014). Furthermore, PA was inversely linked to anxiety (b = −0.35, p = 0.013) and successfully mediated the relationship between MDA and anxiety symptoms (Indirect Effect = −0.047, 95% CI: −0.10 to −0.01). No significant mediation effects were observed for depression or stress. Conclusions: The present study identifies robust inverse associations between MDA and symptoms of anxiety, depression, and stress in Chilean adolescents. A key finding is the specific pattern of relationships observed: while higher MDA is directly linked to lower levels of depression and stress, its association with anxiety is shared with levels of PA. Despite these findings, the cross-sectional nature of the study limits the establishment of causal relationships, and further longitudinal research is needed to confirm these directional pathways. Full article

High-precision topography of tidal flats is essential for coastal monitoring, geomorphic change analysis, and ecological assessment. Although satellite remote sensing supports repeated and large-area observation, topographic inversion over small-scale tidal flats—here defined as localized intertidal patches with limited areal extent, represented in this study by a 1.11 km² tidal flat near Dafeng Port—remains challenging, because ICESat-2 laser altimetry tracks across such areas are typically sparse and spatially clustered within narrow sub-regions, leaving extensive observation-blind zones without direct elevation labels. This label-clustering problem constrains the applicability of traditional empirical models and tends to cause deep learning models to generalize poorly beyond the spatial distribution of training samples. To address this issue, this study proposes a Residual Attention Physical-constraint Semi-supervised U-Net (RAPS-UNet) that fuses ICESat-2 ATL03/ATL08 elevation labels with Sentinel-1 SAR and Sentinel-2 optical features. The preprocessing pipeline comprises refined ICESat-2 photon filtering, adaptive inundation-frequency extraction, multi-source feature selection, and baseline DEM construction. RAPS-UNet integrates residual learning, attention-based multi-source fusion, physics-constrained loss, and confidence-weighted pseudo-label augmentation to improve extrapolation under clustered-label conditions. A four-level validation protocol—in-distribution validation, spatial holdout testing, and field-based assessment over both interpolation and extrapolation zones—was designed to evaluate spatial generalization. Against a field-surveyed DEM, RAPS-UNet achieved an overall RMSE of 0.20 m, an MAE of 0.16 m, and an R² of 0.91; the field-based interpolation and extrapolation zones yielded RMSEs of 0.17 m and 0.22 m, respectively, while the spatial holdout test reached an RMSE of 0.23 m and an R² of 0.81. Relative to the traditional inundation frequency–elevation linear model (RMSE = 0.35 m), RAPS-UNet reduced the field-validation RMSE by approximately 43%. The proposed framework therefore offers a practical approach for fine-scale coastal-zone topographic mapping under sparse and spatially clustered altimetry conditions. Full article

This paper presents a probabilistic sensitivity analysis of a nonlinear electrochemical model for lithium-ion batteries. The model is treated as a reduced virtual replica for uncertainty-aware analysis rather than as a full digital twin. A reduced electrochemical formulation is combined with constrained inverse parameter identification using experimental current–voltage data to relate observable battery behavior to effective model parameters. Predictive variability is assessed through Monte Carlo uncertainty propagation and global sensitivity analysis under both charging and discharging conditions. The results indicate that the particle radius of the positive active material and the effective electrodes area are the dominant contributors to terminal-voltage uncertainty, whereas the electrode thickness parameter and negative electrode active material particle radius have a moderate influence within the studied ranges. Rank-based and variance-based sensitivity measures are more informative than linear indices for this reduced nonlinear system. From a mathematical perspective, the work integrates reduced-order modeling, inverse problem formulation, numerical simulation, and uncertainty quantification in one computational framework for battery analysis. The results support uncertainty-aware parameter prioritization, calibration of reduced electrochemical models, and provide a basis for future work on battery design, control, and digital-twin-oriented extensions under uncertainty. Full article

Adolescence is a critical window for health behavior consolidation, yet the combined influence of physical activity level (PAL) and the body mass index (BMI) on aerobic capacity remains understudied, especially in transitioning periurban environments. This study examined the association between PAL, BMI, and aerobic capacity in adolescents from Montería, Colombia. A cross-sectional study was conducted among 112 adolescents (aged 12–17 years). Aerobic capacity was assessed using the 20 m shuttle run test (Course Navette), and PAL was measured via the validated Assessment of Physical Activity Levels Questionnaire (APALQ), following standard fitness assessment protocols. Multivariable linear regression models were utilized to estimate independent associations, adjusting for age and sex. The multivariable model was significant (F = 8.45; p < 0.001), explaining 21% of the variance in aerobic capacity (adjusted R² = 0.21). PAL was positively and independently associated with aerobic capacity (B = 0.22; 95% CI: 0.05–0.38; p = 0.010), regardless of BMI. While age showed a positive association (B = 0.09; p = 0.032) and sex was inversely associated (B = −0.39; p < 0.001), BMI did not emerge as an independent predictor in the adjusted model (B = −0.04; p = 0.080). Aerobic capacity in adolescents is more consistently explained by behavioral factors (what they “do”) than by anthropometric status (what they “weigh”). These findings support a paradigm shift in pediatric public health, prioritizing high-intensity movement overweight control to improve cardiorespiratory fitness in transitioning urban territories. Full article

Background: The standing long jump (SLJ) is a field-based test of lower-limb muscular fitness in youth and a proposed indicator of health-related physical fitness. However, evidence on its relationship with psychological, sleep, dietary, and lifestyle factors in adolescents remains limited, particularly in Latin America. Objective: To examine the association between SLJ performance and health-related indicators and lifestyle factors in Chilean adolescents. Methods: A cross-sectional study was conducted with 145 adolescents (16.02 ± 1.09 years; 99 males, 46 females) from a subsidized secondary school in Chile. SLJ performance, handgrip strength, body mass index (BMI), physical activity (PAQ-A), sleep quality (PSQI), dietary indices (HCI and UHCI), and psychological symptoms (DASS-21) were assessed. Associations were examined using Pearson’s correlation and multiple linear regression, with false discovery rate (FDR) correction for multiple comparisons. Results: SLJ performance was positively associated with handgrip strength (r = 0.59, p < 0.001) and physical activity (r = 0.42, p < 0.001), and negatively associated with BMI (r = −0.30, p = 0.001) and anxiety (r = −0.24, p = 0.011). Sleep quality showed a weak inverse association that was not significant after FDR correction. Dietary indices were not associated with SLJ performance. In the adjusted model, sex (β = 0.224, p = 0.013), BMI (β = −0.275, p < 0.001), handgrip strength (β = 0.435, p < 0.001), and physical activity (β = 0.229, p = 0.002) were independently associated with SLJ performance, explaining 57% of the variance (R² = 0.57, adjusted R² = 0.523). Conclusions: SLJ performance is mainly associated with muscular strength, physical activity, and BMI in Chilean adolescents, while psychological, dietary, and sleep variables are not independently associated after adjustment. These findings support SLJ as a practical indicator of muscular fitness, but not of overall health. Due to the cross-sectional design, causal inference is not possible. Full article

Urban canopy height is an essential indicator for characterizing vegetation structure and carbon sequestration, yet satellite LiDAR often lacks sufficient spatial resolution, airborne LiDAR is costly, and SAR has limited sensitivity to vegetation structure. This study proposes a canopy height inversion framework using high-resolution stereo pairs from the Gaofen-7 (GF-7) satellite. A 0.65 m Digital Surface Model (DSM) was generated from GF-7 data, and a relative surface height was derived by differencing the GF-7 DSM from a coarse 30 m DSM reference. Key features were selected via Boruta and Random Forest Recursive Feature Elimination (RF-RFE), and six models—linear, polynomial, support vector machine, backpropagation neural network, XGBoost, and RF—were compared. The results showed that the Boruta feature set improved average R² by 8.2%. Among all models, RF performed best (test set R² = 0.71, RMSE = 1.70 m) and exhibited the strongest resistance to overfitting. Canopy heights within Beijing’s Fifth Ring Road showed an “outer-high, inner-low” pattern: large parks exceeded 30 m, while the Central Business District remained below 3 m. GF-7 stereo pairs enable efficient and cost-effective retrieval of canopy height in fragmented urban green spaces, supporting ecological parameter quantification and urban green-space management. Full article