Search Results (4,437)

Objectives: This study aims to describe real-world clinical profiles, treatment patterns and one-year outcomes of older adults hospitalized for acute heart failure (HF) across different admission services, and to examine whether sex influences these characteristics and outcomes. Methods: We performed a retrospective study including 1226 patients aged ≥80 years hospitalized for acute HF between 2018 and 2021. Patients were categorized by admitting service (cardiology [CAR] or internal medicine [IM]) and sex. The primary endpoint was all-cause mortality at 12 months, with secondary endpoints including HF readmission and a composite of death or HF readmission. Results: The mean age was 87.4 ± 4.4 years, 65.8% were women, and 80% presented HF with preserved ejection fraction (HFpEF). Admission services reflected differing patient profiles: individuals admitted under IM were older, predominantly female, and more frequently presented with HFpEF and worse functional class, while CAR admissions included a higher proportion of patients with ischemic disease. Use of guideline-directed medical therapy varied according to clinical characteristics and admitting service. At 12 months, mortality and the composite endpoint differed across admission services, whereas HF readmission rates were similar. Sex-stratified analyses showed no difference in all-cause mortality or in the composite endpoint, but women experienced more frequent HF readmissions. Conclusions: Among very old adults hospitalized for acute HF, clinical profiles, therapeutic patterns, and outcomes differ according to patient characteristics and hospital admission pathways. Sex also shapes clinical presentation and readmission patterns. These findings highlight the importance of harmonized, multidisciplinary, and sex-sensitive HF care pathways to address the diverse needs of an aging HF population. Full article

Condensation heat transfer and frictional pressure drop of R410A, R455A, R454C, and a newly proposed ternary low-GWP (Low-Global Warming Potential) refrigerant (R1234yf/R13I1/R32) were experimentally investigated in a horizontal smooth tube. The heat transfer results established R410A and R1234yf/R13I1/R32 as the upper and lower performance bounds, respectively, while the two low-GWP blends occupied an intermediate range. The hydraulic behavior showed a different ranking from the heat transfer performance, indicating that thermal advantage and pressure-drop reduction are controlled by different refrigerant properties. Among the three established correlations, Shah (2022) provided the best overall agreement and was selected as the basis for further development. The Bell–Ghaly mixture correction was modified by replacing the vapor quality weighting term with a Zivi-based void fraction and the uniform phase equilibrium slope with a local pointwise slope. The proposed correlation reduced the overall Mean Absolute Deviation (MAD) from 16.9% to 9.3% and Mean Relative Deviation (MRD) from +16.7% to +4.3% across all 150 data points compared to Shah (2022). Full article

High-accuracy potential energy surface (PES) and rovibrational energy levels are essential for computational IR line lists used in (exo)planetary atmospheric spectroscopic analysis and modeling. We present a new ¹⁴N₂¹⁶O PES refinement achieving 0.001–0.002 cm⁻¹ statistical accuracy for E_vib ≤ 7000 cm⁻¹ and J_max = 88–100, relative to complete experiment-based rovibrational energy levels in RITZ, MARVEL, HITRAN2020, and NOSL-296 datasets. Building upon the high-quality ab initio Comp-I PES, the resulting D2n (and D2nB) PES outperform the Ames B1b PES, the UCL TYM PES, and the UCL 2025 PES series in both energy-resolved and J-resolved comparisons, exhibiting the smallest mean residuals and scatter below E_vib = 8000 cm⁻¹, as well as the highest fractions of |δ| < 0.0010 cm⁻¹ and |δ| < 0.0005 cm⁻¹. Robust analysis identified only seven outliers among the UCL-2025 reference level set; all remaining levels are retained to ensure resilient statistics. The D2n PES also shows stable IR intensities with the G10K dipole moment surface and reasonably consistent isotopologue accuracy. Analysis of J-resolved σ_rms highlights the critical role of reference-dataset accuracy and internal consistency. We discuss factors enabling (sub-)0.002 cm⁻¹ accuracy and prospects for extending similar accuracy to higher energies, additional isotopologues, and other molecules. Full article

A new generalization of the Logarithmic mean function and Euler’s Beta k-Logarithm function is proposed using the Mittag–Leffler k-function. We study their analytical properties, including functional relations, symmetry relation, inequalities, summation representations, and integral representations. Mellin transformations are established, and a generalized k-Beta Logarithmic distribution is presented along with its probabilistic applications. Furthermore, we introduce a novel k-Beta Logarithmic fractional derivative operator of Caputo type and develop a Legendre spectral collocation method with Chebyshev–Gauss–Lobatto nodes for the numerical solution of associated fractional differential equations. Rigorous error analysis in the weighted $L^2$-norm is provided, establishing algebraic convergence for finite-regularity solutions and exponential convergence for analytic solutions. Numerical experiments confirm the theoretical convergence rates and demonstrate the efficiency and spectral accuracy of the proposed scheme. Full article

Microplastics (MPs) are emerging contaminants that have been detected in human blood and tissues, raising concerns regarding systemic exposure and potential health effects. Internal MP burden mitigation techniques, nevertheless, are yet largely unexplored. We evaluated whether oral administration of chitosan derived from Procambarus clarkii (PCC) could reduce circulating MPs in humans via gastrointestinal sequestration in this pilot-controlled study. 11 healthy adults received PCC supplementation (0.8 g/day) for 15 days, while 10 matched controls received a placebo. Using stereomicroscopy, scanning electron microscopy (SEM), and micro-Fourier transform infrared spectroscopy (µFTIR), blood MP concentrations were quantified and characterised according to size, shape, and polymer type. At baseline, MPs were found in every subject. Following PCC supplementation, mean MP concentrations decreased from 1.84 ± 0.28 µg/mL to 1.34 ± 0.20 µg/mL (−26.3%, p < 0.01, paired analysis). The control group observed no significant differences. While polymer-resolved analysis consistently indicated reductions across major polymer classes, size-resolved analysis indicated preferential reductions in intermediate particle fractions (11–50 µm). The circulating MPs’ estimated mean residence time (MRT) was 58 ± 28 days. These findings provide preliminary evidence that chitosan-based gastrointestinal sequestration could potentially reduce the systemic MP burden in humans. Full article

This study refines the application of unmanned aerial vehicle light detection and ranging (UAV-LiDAR) for forest parameter extraction, focusing on calibration aspects of random forest models within subtropical mixed forests. A notable inverse correlation was identified between high-density LiDAR-derived intensity percentiles and stand volume of 20 m × 20 m plots. Using a random forest model with a 20% validation proportion (30 plots), we achieved a validation coefficient of determination (R²) of 0.61 and root mean square error (RMSE) of 27.2%. Key variables included radar echo intensity and forest gap fraction, emphasizing their importance in volume estimation. Additionally, analyses highlighted forest gap fraction as an important variable in model construction, suggesting careful consideration of its distribution in sample plot selection. Full article

This paper is concerned with the problems of mean-square global dissipativity and global asymptotic stability for a class of stochastic fractional-order memristive BAM neural networks with leakage terms and mixed time-varying delays, including discrete delays and distributed delays. By using differential inclusion theory, stochastic analysis, matrix measure approach, and Lyapunov stability theory combined with linear matrix inequalities (LMIs), several new sufficient conditions are derived to ensure the mean-square global dissipativity and global asymptotic stability of the considered system. Compared with the existing results, the obtained stability and dissipativity criteria are less conservative due to the adoption of matrix measure and fractional-order differential inequalities. The proposed model simultaneously incorporates stochastic perturbations, memristive discontinuity, leakage effects, and mixed delays, which makes it more consistent with actual engineering scenarios such as pattern recognition and intelligent control. Finally, a numerical example is provided to demonstrate the effectiveness and correctness of the theoretical results. Full article

This paper investigates the estimation of the stress–strength reliability parameter $R=P(Y<X)$ when both stress and strength follow independent Garhy distributions under progressive Type-II censoring schemes. A closed-form expression for $\mathbf{R}$ is explicitly derived, enabling effective and precise calculation without numerical integration. The Garhy distribution, a flexible one-parameter lifetime model with an increasing hazard function, is confirmed by full-scale goodness-of-fit diagnostics. A Bayesian estimation model is trained on non-informative priors (normal and extended Jeffreys priors) under squared error loss. The posterior expectations are analytically intractable; we adopt two complementary methods of computation: (i) Markov Chain Monte Carlo (MCMC) using the Metropolis–Hastings algorithm and (ii) the Tierney–Kadane (TK) approximation, which provides extremely precise analytical estimates with significantly reduced computational burden. Monte Carlo simulations are large-scale and compare the proposed estimators under different censoring schemes, sample sizes, and parameter configurations in terms of bias and mean squared error (MSE). The methodology is further applied to a real medical dataset comprising kidney dialysis patient survival times, demonstrating its practical relevance in clinical reliability assessment. Results consistently indicate that Bayesian methods, particularly with the extended Jeffreys prior, outperform classical MLEs in terms of stability and accuracy, especially under heavy censoring. Moreover, the TK approximation yields estimates virtually identical to MCMC while requiring only a fraction of the computational effort. We further extend the TK framework to approximate the posterior variance of R and the expected log-likelihood, providing a fully analytical alternative to MCMC for comprehensive Bayesian inference. Full article

Background: Trigeminal neuralgia (TN) is clinically defined, but patients presenting to tertiary practice with trigeminal-region pain are often diagnostically heterogeneous and may follow prolonged medication, dental, imaging, and procedural pathways before a stable phenotype is established. We aimed to characterize diagnostic phenotypes, secondary causes, and treatment-escalation patterns in a large retrospective tertiary-center trigeminal pain cohort derived from routine free-text clinical documentation. Methods: We conducted a retrospective single-center cohort study based on a clinical dataset containing 18,007 note fragments linked to 672 unique patient records between 12 October 2010 and 21 April 2026. A rule-based natural-language-processing-assisted chart review framework was used to identify patients with trigeminal pain and to extract documentation-derived demographic features, pain distribution, secondary causes, dental pathway variables, imaging signals, medication exposure, procedures, and outcome language. Patients were grouped into primary/classical TN, secondary TN/trigeminal pain, and dental-first or mimic pathways using predefined operational criteria. Results: A total of 455 patients met criteria for the analytic trigeminal pain cohort; 311 (68.4%) carried explicit TN terminology. Mean age was 58.7 years, median age 60 years, and 267 of 428 patients with recoverable sex data (62.4%) were women. Trigeminal branch involvement could be extracted in 351 patients (77.1%), with V2 involvement documented in 256 (56.3%), V3 involvement in 218 (47.9%), and V1 involvement in 138 (30.3%). The final NLP-derived phenotypic distribution comprised 201 primary/classical TN cases (44.2%), 146 secondary TN/trigeminal pain cases (32.1%), and 108 dental-first or mimic presentations (23.7%). MRI was documented in 384 patients (84.4%), neurovascular conflict or vascular loop in 253 (55.6%), multiple-sclerosis-related disease in 69 (15.2%), and tumor-related trigeminal involvement in 84 (18.5%). Prior dental evaluation was identified in 169 patients (37.1%), and prior dental procedures in 114 (25.1%). Carbamazepine exposure was documented in 367 patients (80.7%), pregabalin in 221 (48.6%), gabapentin in 150 (33.0%), oxcarbazepine in 116 (25.5%), and phenytoin in 73 (16.0%). At least one invasive or image-guided procedure was documented in 390 patients (85.7%), including nerve blocks/injections in 355 (78.0%), radiofrequency procedures in 126 (27.7%), balloon compression in 90 (19.8%), microvascular decompression in 113 (24.8%), and stereotactic radiosurgery in 55 (12.1%). Dental-first patients were significantly more likely to have undergone prior dental procedures (65.7% vs. 3.5% in primary/classical TN and 24.7% in secondary TN; p < 0.001), whereas secondary TN/trigeminal pain was associated with higher use of radiofrequency procedures (36.3%; p = 0.017), higher use of stereotactic radiosurgery (19.9%; p = 0.002), higher recurrence documentation (70.5%; p = 0.001), and a higher rate of complete pain relief documented at last follow-up (46.6%; p = 0.004). Conclusions: In tertiary practice, trigeminal pain is substantially broader than a formal TN label. Secondary disease and dental-first pathways account for a large fraction of referrals, and management is characterized by heavy medication burden, frequent escalation, and recurrent retreatment. A structured phenotyping approach may help convert routine clinical documentation into a clinically meaningful framework for diagnostic triage and treatment selection, although imaging and outcome variables require cautious interpretation when derived from retrospective free text. Full article

Fine particulate matter (PM_2.5) composition, rather than mass alone, plays a critical role in determining toxicity and health impact. This study examined short-term associations between daily PM_2.5 constituents—black carbon (BC), nitrate (NO₃⁻), ammonium (NH₄⁺), and trace elements—and cardiopulmonary hospital admissions in Makkah, Saudi Arabia. Twelve months of constituent data from the Alharam monitoring site were linked to Herra hospital admissions for cardiovascular (CVD) and pulmonary diseases, stratified by visit type, age, and sex. Negative-binomial generalized linear models estimated adjusted relative risks (aRRs) per interquartile range increase in each constituent, controlling for meteorology, seasonality, and temporal trends. Mean PM_2.5 was 113.6 µg/m³; BC, sulfur, NO₃⁻, and NH₄⁺ dominated the fine fraction. Crustal elements were strongly intercorrelated (r > 0.9), while BC, lead (Pb), and nickel (Ni) showed moderate correlations (r ≈ 0.4–0.6), suggesting shared anthropogenic origins. BC increased CVD emergency/outpatient visits by 18% (aRR = 1.18; 95% CI: 1.08–1.29) and inpatient admissions by 25% (aRR = 1.25; 95% CI: 1.07–1.46). Ni and sulfur were also significant predictors; crustal elements were not. Multi-pollutant models confirmed BC and Pb as independent predictors (aRR = 1.19; 95% CI: 1.02–1.38). Effects were strongest among older adults aged 45–65 at lag 0–2 days. These findings highlight the need for emission controls targeting traffic and industrial combustion sources. Full article

X-band marine radar shadow features are widely applied to wave height estimation. Since the shadow fraction rises with the distance from the radar antenna, wave slope estimation is sensitive to the selected analysis region. To resolve this issue, a wave height estimation method is proposed by adopting the optimal shadowed fraction which is unrelated to the boundary selection of the analysis area. Within this paper, the shadow fraction is computed on the basis of the mechanism of radar image shadow imaging. Instead of adopting the widely used Smith fitting function, the wave slope with the non-shadow areas is achieved by using the obtained shadow fraction and the grazing angle. The collected marine radar images, totaling 450 h, are employed to demonstrate the performance of the proposed wave height retrieval method. Compared with fundamental shadow statistical approach, the root mean square error of the proposed method decreases by 0.19 m, and the correlation coefficient increases by 0.10. Meanwhile, the execution time of the presented algorithm has significantly decreased. Full article

Vision-based monitoring of personal protective equipment (PPE) is central to construction safety, yet robust detectors remain limited by scarce, privacy-constrained site imagery. Digital twin simulation can generate labeled synthetic data at scale, but Sim-to-Real gaps make the effective use of synthetic data under a fixed training budget unclear. We benchmark YOLOv11s, Faster R-CNN, and RT-DETR-L using a controlled real–synthetic mixing protocol comprising a fixed real-only test set (400 images), separate sampling pools (5760 real and 4000 synthetic images), and eleven training configurations of approximately constant size (∼1450 images before the validation split) with real fractions ranging from 0% to 100%. Using average recall (AR@100) as the primary safety-oriented metric, the original single-run benchmark shows non-linear architecture-dependent responses to data mixing: YOLOv11s and RT-DETR-L achieve their single-run peaks at G9 (90% real/10% synthetic), whereas Faster R-CNN performs best at G10 (100% real). To assess robustness for the most central YOLOv11s comparison, we further conduct a targeted supplementary repeated-seed analysis for G9 and G10 and re-evaluate all resulting checkpoints on the same fixed real-only test set. This supplementary analysis shows that G10 achieves higher mean performance and lower variance than G9 for YOLOv11s, indicating that the apparent single-run advantage of limited synthetic supplementation is not stable across reruns. However, this robustness check is limited to the central YOLOv11s G9-versus-G10 case and should not be interpreted as a comprehensive robustness validation across all configurations and detector families. Persistent errors on safety vests further indicate a materiality gap for deformable PPE. Overall, these findings suggest that synthetic supplementation can be useful in some settings, but its value is architecture-dependent, evaluation setting-sensitive, and should be interpreted cautiously under robustness-oriented evaluation. Full article

Background/Objectives: Atrial fibrillation (AF) is common in heart failure with preserved ejection fraction (HFpEF) and is associated with worse symptoms and prognosis. Emerging evidence suggests that sex modifies the AF–HFpEF relationship through differences in atrial remodeling, comorbidity burden, and hemodynamic vulnerability. This study aimed to evaluate how sex and AF jointly relate to differences in cardiac structure, clinical characteristics, and outcomes in HFpEF. Methods: We retrospectively analyzed 622 patients with HFpEF admitted between January 2019 and May 2023. Patients were categorized into four predefined clinical subgroups: women without AF, women with AF, men without AF, and men with AF. The primary endpoint was first rehospitalization for HF decompensation. Results: Over a mean follow-up of 48.6 ± 16.4 months, 181 patients (29.1%) were rehospitalized for worsening HF, with the highest event burden observed in men with AF. Sex and AF were each associated with distinct clinical and remodeling profiles, without significant sex-by-AF interaction effects. AF was independently associated with a higher risk of HF rehospitalization (HR 1.45, 95% CI 1.06–1.99, p = 0.021), whereas female sex was protective (HR 0.71, 95% CI 0.53–0.97, p = 0.032). Men with AF exhibited the most adverse remodeling profile, characterized by the largest unindexed left atrial and left ventricular dimensions, the highest prevalence of significant tricuspid regurgitation, and the lowest event-free survival (HR 1.92, 95% CI 1.23–2.99, p = 0.004). In contrast, women with AF more frequently displayed concentric remodeling and significant mitral regurgitation. Independent predictors of rehospitalization included higher NYHA functional class and lower left ventricular EF within the preserved EF range. Conclusions: Sex and AF were independently associated with substantial differences in cardiac structure, clinical characteristics and prognosis in HFpEF. Men with AF represent the highest-risk subgroup, driven by more advanced structural remodeling and valvular dysfunction. These findings suggest that simple sex- and rhythm-based classification may provide complementary information for risk stratification and management in HFpEF. Further validation in independent cohorts is warranted. Full article

Methane generation from anaerobic biodegradation of fugitive diluent hydrocarbons is an important source of greenhouse gas emissions from oil-sands tailings, yet predictive tools that preserve hydrocarbon-level information remain limited. This study develops a hydrocarbon-resolved methane-prediction model and tests it on a case study involving a twelve-component diluent mixture containing BTEX, normal alkanes, and iso-alkanes. The model integrates stoichiometric methane yields, compound-specific lag times, Monod-type hydrocarbon consumption, logistic activation, and a single methane-conversion factor to simulate cumulative methane production and group-level methane contributions through time. Model performance is evaluated against measured methane and residual hydrocarbon data using normalized mean square error. The model reproduces cumulative methane with improved normalized mean square error relative to the existing stoichiometric benchmarks, while group-resolved outputs and robustness analyses show that predictive performance is governed primarily by conversion efficiency and lag structure. On the other hand, inclusion of an unresolved biodegradable-substrate fraction did not strengthen model agreement. These results indicate that the modeled hydrocarbon set captures the principal methane-generating substrate pool and that the proposed framework provides an accurate and mechanistically interpretable basis for methane prediction in oil-sands tailings. Full article

Connected and autonomous vehicles (CAVs) increasingly rely on vehicle-to-everything (V2X) communication and distributed sensing infrastructures to support cooperative driving and intelligent transportation services. While these capabilities improve traffic efficiency and safety, they also expand the attack surface of vehicular networks and expose in-vehicle communication systems such as the Controller Area Network (CAN) bus to a wide range of cyber threats. Machine learning-based anomaly detection has emerged as a promising approach for identifying malicious CAN traffic patterns; however, conventional centralized learning requires large-scale data aggregation from vehicles, which raises privacy and scalability concerns. Federated learning (FL) enables collaborative model training across distributed vehicles without requiring the exchange of raw in-vehicle data, making it attractive for privacy-preserving vehicular security applications. Nevertheless, FL systems remain vulnerable to adversarial participants that manipulate local training data or model updates to poison the global model during aggregation. In this work, we present a systematic robustness evaluation of federated anomaly detection in connected vehicular networks under adversarial conditions. The study compares six aggregation strategies, including Federated Averaging (FedAvg), coordinate-wise Median, Trimmed Mean, Krum, Multi-Krum, and Geometric Median (GeoMed), within a non-IID federated CAN bus anomaly detection setting. The evaluation covers label-flipping attacks, gradient-scaling attacks, and a feature-triggered backdoor attack. In addition, the analysis examines malicious client participation, attack-strength variation, learning-rate sensitivity, Trimmed Mean beta sensitivity, multi-seed reliability, and server-side aggregation time. The results show that FedAvg is vulnerable under strong adversarial manipulation, while Trimmed Mean is sensitive to the selected trimming fraction. Median and GeoMed provide strong robustness against gradient-scaling attacks, whereas Multi-Krum achieves the strongest resistance to label-flipping and backdoor attacks. These findings demonstrate that no single aggregation strategy is optimal across all threat models. Instead, robust aggregation for federated CAV anomaly detection should be selected according to the expected attack type, reliability requirement, and computational overhead. Full article