Search Results (4,608)

Background: Acute focal neurological deficits require rapid differentiation between ischemic stroke and stroke mimics to avoid treatment delays and inappropriate therapy. Seizures, including ictal deficits, status epilepticus, and post-ictal/Todd’s phenomena, are among the most challenging mimics. This review summarizes the role of multimodal neuroimaging in distinguishing acute ischemic stroke from seizure-related deficits. Methods: We performed a focused narrative review of neuroimaging findings in acute stroke mimics, emphasizing non-contrast computed tomography (CT), CT angiography, CT perfusion, magnetic resonance imaging (MRI), including diffusion weighted imaging (DWI), apparent diffusion coefficient (ADC), fluid attenuated inversion recovery (FLAIR), and arterial spin labeling (ASL) sequences. Imaging patterns, diagnostic pitfalls, and practical clues for hyperacute stroke pathways were synthesized. Results: Acute ischemic stroke is typically suggested by vascular-territorial abnormalities, including arterial occlusion or stenosis, territorial hypoperfusion, and congruent DWI/ADC restriction. Seizure-related deficits more often show non-territorial cortical perfusion changes, ictal or status-related hyperperfusion, reversible MRI abnormalities, and absence of arterial occlusion. However, post-ictal hypoperfusion, peri-ictal diffusion restriction, and reperfusion-related hyperperfusion may overlap with ischemic patterns. Conclusions: A multimodal approach integrating vascular imaging, perfusion distribution, DWI/ADC, ASL, clinical timing, and EEG findings can improve diagnostic accuracy in the stroke–seizure differential without delaying treatment in true acute ischemic stroke. Full article

Background: Crohn’s disease-associated intestinal strictures represent a major source of morbidity and frequently require endoscopic or surgical intervention. However, patients with stricturing Crohn’s disease demonstrate substantial clinical heterogeneity regarding disease localization, penetrating complications, systemic manifestations, metabolic alterations, and treatment exposure. This study aimed to explore phenotypic heterogeneity within patients with Crohn’s disease-associated intestinal strictures. Methods: In this retrospective exploratory cohort study, 96 patients with Crohn’s disease-associated intestinal strictures treated at a tertiary referral center between 2014 and 2024 were included. Clinical, structural, metabolic, and treatment-related variables were analyzed. Univariate analyses were performed using chi-square, Fisher’s exact test, Student’s t-test, or Mann–Whitney U test as appropriate. Exploratory multivariable logistic regression models were constructed to explore relationships between different clinical phenotypes and disease-related characteristics, including extraintestinal manifestations (EIMs), smoking status, penetrating disease manifestations, hepatic steatosis, stenosis localization, and abscess formation. Given the limited sample size and event numbers in several subgroup analyses, all multivariable analyses were considered exploratory and hypothesis-generating. Results: The cohort demonstrated a heterogeneous clinical presentation with a high prevalence of perianal disease, penetrating complications, prior intestinal surgery, and biologic therapy exposure. Female sex (OR 4.63, p = 0.044), autoimmune disease (OR 23.5, p = 0.049), rectal stenosis (inverse association; OR 0.08, p = 0.041), and exposure to multiple biologic therapies (OR 20.11, p = 0.036) remained associated with EIMs after multivariable adjustment. Smoking status was associated with anastomotic stenosis (OR 3.16, p = 0.023) and inversely associated with female sex (OR 0.35, p = 0.036). Phenotype-oriented analyses further suggested clustering of penetrating disease manifestations, including associations between intestinal fistulas, perianal fistulas, and abscess formation. Hepatic steatosis demonstrated exploratory associations with intestinal fistulas, intestinal resection, and appendectomy. Several analyses demonstrated wide confidence intervals and should therefore be interpreted cautiously. Conclusions: This exploratory retrospective cohort study highlights the substantial clinical heterogeneity observed among patients with Crohn’s disease-associated intestinal strictures. Different structural, systemic, penetrating, behavioral, and metabolic disease manifestations may indicate potentially overlapping phenotypic patterns within stricturing Crohn’s disease. Given the retrospective design, limited sample size, and exploratory statistical approach, these findings should be interpreted cautiously and require validation in larger prospective studies. Full article

Magnetostrictive sensors based on the inverse magnetostrictive effect offer the advantages of wireless passive operation and structural simplicity; however, achieving both high sensitivity and superior linearity remains a persistent challenge. This study presents a magnetostrictive pressure sensor incorporating a tunable Poisson’s ratio (TPR) chiral auxetic honeycomb substructure, designed to linearize the stress response of the sensing material. A theoretical model linking substructure design parameters to sensor output linearity was derived and validated through finite element simulations. The fabricated substructure exhibited a stable negative Poisson’s ratio (−1.278 to −1.213) within its elastic regime and a highly linear axial-to-transverse strain relationship (x = 1.214y + 0.113). The sensor achieved a calibration linearity of R² = 0.99745, a continuous linear force response up to 118.7 N while the corresponding voltage variation reached 10.75 mV, and a maximum hysteresis error of 5.495% over eight loading cycles. Bearing press-fit force monitoring experiments confirmed practical viability under industrial conditions, with R² exceeding at least 0.995 for dry assembly between multiple bearing types and maintaining R² > 0.994 under lubricated conditions. The proposed TPR substructure approach establishes a reference framework for linearity enhancement in inverse magnetostrictive force sensors. Full article

High-resolution, long-term gridded meteorological datasets from in situ observations are crucial for ecosystem monitoring, soil diagnostics, hydrological modelling, and Earth system model evaluation. This study presents two enhanced real-time adaptations of Thornton’s Daymet V4 interpolation method. Daymet4-r1 uses a traditional calibration strategy with exhaustive parameter search, while Daymet4-r2 applies a global optimization algorithm (find_min_global from the dlib library) to adjust parameters automatically at each time step. Both methods were tested over Tuscany using high-resolution terrain and a dense observation network. Validation with leave-one-out method was carried out for the period 1995–2011 for both versions, while Daymet4-r2 underwent extended evaluation from 1991 to 2024 to assess seasonal dynamics and long-term variability. Results show that Daymet4-r2 outperforms Daymet4-r1 and the original Daymet V4 for all variables (mean absolute error of 1.24 mm, 1.06 °C, 1.29 °C, 6.26%, 0.78 m/s, and 2.04 hPa for precipitation, maximum and minimum temperature, relative humidity, wind speed, and sea level pressure, respectively). The largest improvement was observed in minimum temperature due to an enhanced approach for detecting and modelling thermal inversions. The high performance, flexibility, and ability of Daymet4-r2 to operate without prior calibration highlight its potential for model verification, real-time environmental monitoring, and integration into climate services. Full article

The inclusion of the cement industry into China’s national carbon emissions trading system in 2025 has fundamentally altered the compliance environment for high-emission enterprises, transforming carbon allowances from passive regulatory instruments into dynamic assets whose management directly affects financial performance. We develop a multi-scenario carbon asset management decision model tailored to the intensity-based benchmarking mechanism adopted by the national market. The model centres on the quota surplus-deficit variable EA4, which is computed from enterprise-level emission intensity relative to the industry benchmark, and decomposes the management problem into sequential selling and buying subproblems linked by coupled decision boundaries. A systematic parameter framework is constructed, and the model is applied to two cement enterprises—Enterprise A, a leading producer with a clear allowance surplus, and Enterprise B, a mid-tier producer operating near the benchmark boundary—through historical backtesting over the 2024–2025 period. Three principal findings emerge. First, the intensity benchmarking mechanism creates a dual-leverage effect whereby a 1.4% improvement in emission intensity (from 0.8112 to 0.8000 t/t) increases the quota surplus by 27%, a nonlinearity not captured by conventional compliance-cost models. Second, the model-driven strategy outperforms traditional experience-based approaches by 36.8% (baseline scenario, +95.20 vs. +69.58 MRMB) and 37.3% (risk scenario, −44.55 vs. −71.08 MRMB), with the improvement rate remaining consistent across both enterprises, suggesting that trading timing outweighs instrument selection in determining compliance cost outcomes. Third, dynamic CEA–CCER allocation captures an incremental 2.33 MRMB through the exploitation of a transient price inversion, a gain invisible to single-instrument strategies. Sensitivity analysis confirms that the relative advantage is robust to carbon price variations (±30%) and CCER offset caps (2–10%), while emission intensity and carry-over allowances represent the most consequential parameters for strategy direction, with EA4 crossing zero near the industry benchmark (I ≈ 0.85). The framework provides actionable decision support for cement and other high-emission enterprises navigating the unified carbon market, and contributes a quantitative methodology to the emerging field of environmental management accounting. This study contributes to Sustainable Development Goal 13 (Climate Action), Goal 7 (Affordable and Clean Energy), and Goal 9 (Industry, Innovation, and Infrastructure) by providing operational tools for decarbonisation in carbon-intensive industries. Full article

Heated crude oil pipelines transporting high-pour-point, high-viscosity, and high-wax-content crude oil are increasingly operated under small-batch and multi-condition scenarios. Under such conditions, fixed-parameter models and experience-based operating strategies may fail to accurately describe the evolving thermo-hydraulic state, resulting in inaccurate temperature-safety assessment and conservative energy use. To address this problem, this study develops a hybrid modelling and simulation framework for the energy-efficient operation of heated crude oil pipelines. The framework integrates operating-state perception, online parameter inversion, transient thermo-hydraulic simulation, data assimilation, and rolling optimization. First, an online parameter inversion method based on inverse problem solving is established to dynamically identify the overall heat-transfer coefficient and friction correction factor from Supervisory Control and Data Acquisition (SCADA) measurements. Second, a transient thermo-hydraulic simulation and data-assimilation model is constructed to predict pressure, temperature, and safety margins under changing boundary conditions. Third, a constraint-aware rolling optimization strategy is introduced to coordinate heating and pumping operations while satisfying temperature and pressure constraints. The proposed framework is validated using a practical crude oil pipeline. Under a representative low-flow-rate condition, online parameter inversion corrects the overestimation of the thermo-hydraulic state by the fixed-parameter model: the total temperature drop along the pipeline is revised from 33.12 °C to 35.65 °C, and the minimum station-inlet oil temperature is revised from 24.77 °C to 21.61 °C. After optimization is introduced, the total operating energy consumption decreases from 11,715.65 kW to 11,287.43 kW, corresponding to a reduction of 3.66%, while all temperature and pressure constraints remain satisfied. Under time-varying boundary conditions, the rolling optimization strategy further adjusts heating-furnace operation according to variations in inlet flow rate, inlet oil temperature, and ambient temperature, thereby reducing cumulative heating energy consumption while maintaining safe operation. The results demonstrate that the proposed framework provides an implementable modelling and simulation approach for online state assessment, transient prediction, and energy-efficient operation of heated crude oil pipelines under variable operating conditions. Full article

Bandstructure methods occupy a central place in the physics of nanostructures, and the multiband $\mathit{k}·\mathit{p}$ theory of Luttinger, Kohn, and Kane has served as one of the most widely used computational frameworks for modelling electronic states and energies in low-dimensional semiconductor systems for several decades. Despite its broad success, the theory harbours a fundamental mathematical difficulty that has been largely overlooked: the multiband Luttinger–Kohn Hamiltonians are non-elliptic partial differential operators for the overwhelming majority of common III–V and III-nitride crystalline materials, a fact that violates the axiomatic requirements of quantum mechanics and is the root cause of the long-standing problem of spurious solutions. In this paper, we derive ellipticity conditions rigorously for the $6\times 6$, $8\times 8$, and $14\times 14$ zinc-blende Hamiltonians, demonstrating that non-ellipticity affects a substantially larger class of materials than previously reported. We develop and justify a systematic parameter rescaling procedure for the $8\times 8$ Kane Hamiltonian and obtain admissible parameter sets for GaAs, AlAs, InAs, GaP, AlP, InP, GaSb, AlSb, InSb, GaN, AlN, and InN. The inversion-asymmetry parameter B is shown to play an essential and previously unrecognized role in maintaining ellipticity, and it is used to optimize the bandstructure fit of the rescaled parameter sets. Analysis of several known $14\times 14$ models reveals structural sources of non-ellipticity, pointing to the need for a revision of perturbative assumptions regarding out-of-basis band contributions. The consistent parametrization framework developed here provides the rigorous mathematical foundation required by inverse design methodologies, AI-enhanced electronic structure calculations, and data-driven multifidelity approaches in nanoscience and nanotechnology. Full article

This study addresses the early-age brittleness and performance limitations of sustainable cement soil. While prior works optimized the baseline compressive strength using recycled sand and nanoclay, the multi-scale synergistic effects of fibers and nanomaterials on the post-peak deformation remain underexplored. To address this gap, a composite modification system incorporating recycled sand, nanoclay, polypropylene fibers, and graphene derivatives was developed. The experimental program comprised standard specimen fabrication, early-age curing, and unconfined compressive strength (UCS) testing, supplemented by RBF neural network curve fitting and quantitative ArcGIS digital image processing of scanning electron microscopy (SEM) micrographs. The results demonstrate that optimizing the fiber parameters (0.6% content with 6 mm length) successfully increases the early UCS to 2263.2 kPa, which is further elevated to a peak of 2755.0 kPa upon co-incorporation with 0.05% small-sized graphene oxide. Correspondingly, a newly introduced ductility index quantitatively confirms that the single-fiber reinforcement yields an index of 1.93, which is further enhanced to 2.02 by the graphene composite system. Microstructure tracking and digital image extraction revealed that the SEM-derived surface porosity decreased significantly, exhibiting a clear inverse relationship with the macroscopic mechanical strength. These quantitative microstructural shifts confirm that graphene effectively filled micropores and reinforced the fiber–matrix interface, establishing a dense matrix network with enhanced interfacial bonding. This multi-scale approach offers a sustainable strategy for green geotechnical applications. Full article

To address the limitations of the traditional cross-scanning method in absolute calibration of weather radars using metal spheres, including insufficient spatial coverage, limited target acquisition efficiency, and echo underestimation in inter-range bins, this study proposes a sector scanning field calibration method. In this approach, standard metal spheres are suspended from UAVs, and a three-dimensional scanning volume around their theoretical positions is constructed to enable high-density echo sampling. By applying drive backlash correction, quadratic Gaussian surface fitting, and three-dimensional ellipsoid model inversion, key radar parameters can be retrieved. Experimental results show that the improved sector scanning method enhances automation, accuracy, and robustness in field environments and minor target drifts. The experiments were conducted under low-wind and low-clutter conditions. The average calibration error of antenna pointing is 0.08°, the average error of echo intensity calibration is 0.3 dB, the average beamwidth error is 0.07°, the range resolution is 6.6 m, and the average radial ranging error is 14 m. These results indicate that the proposed method can meet the main calibration requirements of weather radars in the present experiments. Full article

This article presents several new analytical results for a modified class of Bernoulli polynomials, namely, the Bernoulli polynomials of the second kind (BPs2). The paper mainly develops new connection and inverse connection formulas between the first and second kinds of Bernoulli polynomials using two different approaches. One of these approaches uses the generating functions for both polynomial families, whereas the other employs the power series representation, along with its inverse formula and certain closed forms of sums. Another principal contribution of the paper is the derivation of new explicit formulas for moments, derivatives, and higher-order derivatives of the BPs2, together with inverse derivative formulas and mixed linearization formulas involving several polynomial families, including Chebyshev-type and generalized Fibonacci polynomials. Furthermore, a collection of new definite integral formulas associated with the BPs2 is established. The obtained formulas provide new operational representations for the BPs2 and may be useful in spectral methods, basis transformations, and the treatment of differential equations involving polynomial approximations. Full article

Integration of high-rate Global Navigation Satellite Systems (GNSS) with strong motion (SM) sensors enables accurate broadband coseismic displacements, which are critical for earthquake early warning and rapid source inversion. However, GNSS colored noise and SM baseline shift can degrade the accuracy and stability of the integrated displacements. In this study, we propose a novel loose integration approach where a two-step Kalman filter (KF) is used. In the first step, the high-rate GNSS displacements without colored noise are estimated using an adaptive KF that parameterizes the colored noise. Then, the denoised high-rate GNSS displacements are integrated with SM in the second KF where the baseline shift in SM is parameterized as a random walk process. The effectiveness of the proposed method was validated with co-located high-rate GNSS and strong motion data collected from a shake table experiment, the 2010 Mw 7.2 El Mayor-Cucapah earthquake, the 2016 Mw 7.8 Kaikōura earthquake, and the 2019 Mw 7.1 Ridgecrest earthquake. The results show that the proposed method achieves an RMSE of 1.1 mm, a 21% improvement over the KFb solution when shake table recordings are used as the reference. Application to three real earthquake cases demonstrates that the method effectively mitigates low-frequency GNSS noise and SM baseline shift, resulting in more accurate and stable coseismic displacement estimates. Full article

Understanding the spatiotemporal variability of nanoplastics (NPs) in porous media is vital for environmental risk assessment, yet quantitative in-media analysis of NP distributions during transport remains limited. To address this, we innovatively applied low-field nuclear magnetic resonance (LF-NMR) as a non-invasive approach to dynamically monitor magnetic polystyrene nanoplastic (MPSNP) transport in saturated quartz sand. By establishing the relationship between LF-NMR transverse relaxation rate [1/T_2,I − 1/T_2,0] and MPSNP concentrations, we reconstructed spatiotemporal concentration profiles via T₂ inversion. This methodology enabled systematic evaluation of the effects of ionic strength (IS), flow velocity, initial concentration, and flow direction. Three mathematical models were further applied to analyze MPSNP transport behavior. Results revealed IS as the dominant factor; increasing IS (0.001 to 1 mM) dropped mass recovery from 85.7% to 0%, the migration front no longer advanced at IS > 5 mM. Lower flow rates, higher initial concentrations, and horizontal flow also enhanced retention. The two types of two-site kinetic models provide a better fit for the features of the breakthrough curves. This novel use of LF-NMR demonstrates its robust capability to resolve spatial transport heterogeneity, underscoring that flow velocity, flow direction, and ionic strength are critical regulatory parameters that should be carefully accounted for when evaluating nanoplastic transport in porous media. Full article

Inertial Measurement Units (IMUs) enable portable, multibody motion capture in diverse environments beyond the laboratory, making them a desirable choice for diagnosing mobility disorders and supporting rehabilitation in clinical or home settings. However, challenges associated with IMU measurements, including magnetic distortions and errors due to integration drift, complicate their broader use for motion capture. In this work, we propose a tightly coupled motion-capture approach that directly integrates IMU measurements with multibody dynamic models via an iterated extended Kalman filter to simultaneously estimate the system’s kinematics and kinetics. By enforcing the complete multibody system dynamics and utilizing only accelerometer and gyroscope data, our method accurately estimates joint kinematics and kinetics. Our algorithm is designed to fuse different sensor data, such as optical motion-capture measurements and joint torque readings, to further enhance estimation accuracy. We validated our approach using highly accurate ground-truth data from a 3-degree-of-freedom pendulum and a 6-degree-of-freedom collaborative robot. We demonstrate a maximum root-mean-square difference of 3.75° in the pendulum’s computed joint angles with respect to the marker motion-capture inverse kinematics. For the robot, we observed a maximum joint angle root-mean-square difference of 3.24° with respect to the joint encoders, while the maximum joint angle root-mean-square difference of the optical motion-capture inverse kinematics with respect to the encoders was 1.16°. With regard to kinetic estimates, we report a maximum joint torque root-mean-square difference of 3.02 Nm in the pendulum with respect to the marker motion-capture inverse dynamics and 4.27 Nm in the robot relative to its joint torque sensors. Full article

Background/Objectives: Chronological age does not fully capture the heterogeneity of physiological aging among healthy individuals. Immune aging and redox imbalance are key hallmarks of biological aging, yet their interaction and relationship with circulating extracellular vesicles (EVs) remain incompletely understood. This study aimed to investigate whether endothelial- and platelet-derived EVs are associated with immune and oxidative aging processes in clinically healthy subjects. Methods: Circulating EVs were isolated and characterized by flow cytometry in a cohort of healthy volunteers spanning a wide age range. Endothelial-derived EVs (EeEVs) and platelet-derived EVs (PEVs) were quantified and analyzed in relation to chronological age, immune function parameters, redox biomarkers, ImmunolAge (an immune aging index), and OxyScore (a composite redox index). A normalized EV-Score was developed using an age- and sex-adjusted Z-score approach. Associations were assessed using correlation analyses, non-linear regression models, generalized additive models, and receiver operating characteristic (ROC) curves. Results: Both EeEVs and PEVs increased non-linearly with age, with a pronounced rise during midlife. EV concentrations were positively associated with molecular aging markers and inversely related to multiple immune function parameters. EVs were also linked to redox biomarkers, although oxidative status alone did not explain EV variability. EV-Score was strongly associated with immune aging and showed context-dependent relationships with oxidative status. Notably, high EV-Score values were observed primarily in individuals with accelerated immune aging, whereas subjects with high oxidative status but preserved immune aging exhibited low EV-Score values. ROC analyses demonstrated that the discriminative capacity of EV-Score for immune or oxidative aging depended on the combined immune–redox context. Conclusions: Circulating EVs may reflect the integrated state of immune and redox aging rather than chronological age alone. These findings suggest the potential utility of EVs as dynamic biomarkers of biological aging in healthy individuals and highlight the importance of considering immune and oxidative processes jointly to interpret EV-associated aging signatures. Full article

Auxetic metamaterials exhibit unique mechanical behavior due to their negative Poisson’s ratio, but reliable determination of their effective elastic properties remains challenging. In this study, an experimental–numerical approach is proposed to characterize additively manufactured polylactic acid (PLA)-based auxetic sandwich structures. Material properties were first assessed using tensile testing, melt flow rate/volume rate (MFR/MVR) measurements, Fourier-transform infrared (FTIR) spectroscopy, differential scanning calorimetry (DSC), dilatometry, and nanoindentation, revealing stable mechanical behavior, good processability, and slight increases in crystallinity induced by the printing process. Impulse excitation technique (IET) measurements provided highly reproducible resonant frequencies, demonstrating a strong dependence on core geometry and orientation. However, classical ASTM-based evaluation yielded non-physical elastic properties, highlighting its limitations for architected metamaterials. Finite element modal analyses, combined with inverse parameter identification, enabled the determination of effective elastic properties using a transversely isotropic homogenized model. This approach significantly improved the agreement between experimental and numerical results. The findings revealed pronounced anisotropy and orientation-dependent auxetic behavior, including a negative Poisson’s ratio for specific configurations. The proposed methodology provides a suitable framework for the reliable characterization and design of complex metamaterials. Full article