Search Results (659)

Biofilm-associated infections represent a critical challenge in modern medicine, accounting for approximately 80% of all microbial infections and demonstrating up to 1000-fold higher antimicrobial resistance compared to planktonic bacteria. The extraordinary recalcitrance of biofilms stems from a complex interplay of physical barriers (extracellular polymeric substance matrix), chemical gradients (pH and oxygen heterogeneity), and biological defenses (persister cells and horizontal gene transfer), rendering conventional antibiotics largely ineffective. This comprehensive review highlights the transformative potential of antimicrobial nanoformulations in overcoming these formidable barriers through strategic design principles and diverse mechanisms of action. Evidence demonstrates that rationally engineered nanocarriers achieve improvements in bacterial killing, biofilm biomass reduction, and colony-forming unit reductions compared to free antibiotics. Advanced stimuli-responsive systems exploiting biofilm-specific triggers (acidic pH, bacterial enzymes, elevated ATP) and externally applied stimuli (near-infrared photothermal therapy, ultrasound sonodynamic therapy) enable on-demand therapeutic activation with unprecedented precision, achieving >99.999% bacterial elimination and near-complete biofilm eradication. Despite these remarkable advances, clinical translation remains hindered by challenges in scalability, comprehensive safety evaluation, and regulatory pathway navigation. This review establishes a consolidated evidence base for the design of next-generation antimicrobial nanoformulations, highlights their potential to address biofilm-associated infections, and identifies key knowledge gaps and translation barriers that must be addressed to realize their therapeutic promise. Full article

Severe soil salinization and low fertility significantly constrain sustainable agricultural development in the Yellow River Delta, one of the three major estuarine deltas in China. Despite their ecological importance, the regional-scale spatial interactions between soil salinity and nutrients, particularly regarding their vertical variability, remain poorly understood. This study analyzed 228 soil samples from 76 sites distributed across a distinct salinity gradient, which was determined by constructing a spatial salinity distribution map after sampling. Samples were collected at three depths (0–15, 15–30, and 30–45 cm) to investigate the spatial distribution of soil organic carbon (SOC), total nitrogen (TN), and the C/N ratio, along with their underlying driving factors. SOC and TN exhibited similar spatial patterns, with higher values distributed along both banks of the Yellow River. Horizontally, SOC and TN in the 0–15 cm layer decreased gradually from west to east, whereas the 15–30 cm and 30–45 cm layers showed an opposite trend, increasing eastward. Vertically, SOC and TN contents declined significantly with soil depth (p < 0.05), although the magnitude of this decline varied regionally: the 0–15 cm layer in the western area contained markedly higher nutrient levels than deeper layers, while vertical variation was less pronounced in the eastern and estuarine regions. Both variables were positively associated with total phosphorus (TP), available potassium (AK), soil moisture content (MC), clay content, and pH, but negatively correlated with electrical conductivity (EC), particularly in the 0–15 cm layer. Our results highlight that soil texture, moisture, and salinity affect the spatial heterogeneity and vertical decline of SOC and TN in the Yellow River Delta. Future research should focus on the long-term temporal distribution of the coupling of multiple elements under changing hydrological and salinity regimes. Full article

The stable boundary layer (SBL) over land exhibits pronounced vertical decoupling and structural heterogeneity that remain challenging to diagnose using routine operational monitoring. Here, we utilize a three-year continuous multi-level tower dataset ($N=\mathrm{40,630}$ quality-controlled 15-min records at 2, 10, 20, and 50 m) over the Horqin Grassland to characterize stability-dependent modifications of surface-layer wind structure and near-surface kinetic energy. Using the bulk Richardson number ($R{i}_b$) and raw thermal gradients ($\Delta T_v/\Delta z$), we identify a stability-driven reduction in vertical wind coupling, with a statistical change-point cluster centered near $R{i}_b\approx 0.30$ (95% CI: 0.09–0.52). Cross-level correlation analysis empirically localizes a structural transition zone to the 10–20 m interval, separating a faster, shear-driven upper layer from a dynamically suppressed near-surface flow under strong stability. Concurrently, near-surface horizontal kinetic energy ($HK{E}_{02}$) undergoes a 47% (nighttime) to 55% (full-record) median reduction, while horizontal wind-direction variability (${\sigma }_{\theta \_02}$) broadens due to low-wind meandering, and sub-hourly vertical velocity variance (${\sigma }_{w,\mathrm{LF}}^2$) is suppressed by 57–72% across all heights. Multidimensional scaling (MDS) reveals a statistically significant phase-space compaction under high stability (${\tilde{d}}_{\mathrm{high}}=2.13$ vs. ${\tilde{d}}_{\mathrm{low}}=2.67$, $p<0.001$), with adjusted odds ratios highlighting thermal gradient ($\mathrm{OR}=5.80$), wind shear ($\mathrm{OR}=1.52$), and directional variability ($\mathrm{OR}=1.34$) as dominant positive predictors. These empirical patterns remain robust under temporal-holdout validation (Year-1 calibration vs. Years 2–3 validation; consensus breakpoint $R{i}_b=0.161$ vs. $0.156$) and seasonal/wind-speed stratifications. The results demonstrate that routine 15-min multi-level tower networks provide valuable observational constraints on surface-layer structural transitions, informing boundary-layer parameterizations in numerical weather prediction models and near-surface dispersion assessments. Full article

γ-photon tomography provides a non-contact approach for reconstructing and visualizing flow-field parameters. However, the resulting grayscale images often exhibit blurred boundaries and weak texture features, causing conventional colorization methods such as DeOldify to produce cross-region color diffusion and boundary color overflow. To address this, this paper proposes a γ-photon flow-field image colorization algorithm based on the Hybrid Swin Colorization Network (HSCN). A hybrid dual-stream encoder composed of a Swin Transformer semantic stream and a central difference convolution (CDC) gradient branch is combined with cross-stage gradient injection and a spatially gated adaptive fusion mechanism to enhance the perception of high-frequency structures at flow-field boundaries and suppress color overflow. The effectiveness of the algorithm is evaluated in terms of colorization quality and flow-field temperature-parameter inversion using γ-photon flow-field images of two CFD-simulated flow patterns, a large-scale vortical wake and a horizontal wake. The proposed method achieves PSNR, SSIM, FID, and MAE values of 38.7422, 0.9372, 10.7344, and 0.0085, respectively. Compared with DeOldify, PSNR and SSIM are improved by 24.30% and 11.89%, while FID and MAE are reduced by 42.98% and 60.47%, respectively. In addition, HSCN achieved a MAPE of 12.65% across 15 boundary and temperature-transition locations in three representative samples, compared with 31.24% for DeOldify and 28.70% for DDColor. Full article

This study develops an analytical model for a mid-deep U-shaped borehole heat exchanger (UBHE) based on the segmented finite line source method, integrating geothermal gradient, five-layer geological stratification, and groundwater seepage within a unified framework. The injection, horizontal, and extraction sections are represented by independent local coordinates and coupled through the position- and time-dependent unit-length heat-transfer rate $q_l\left(s_n,t\right)$. Validation against the benchmark results of Bao et al. yields a mean absolute error of 0.87 °C and a mean relative error of 1.6%. Numerical-independence tests identify a 1 h time step and 100/50 m vertical/horizontal segment lengths as the adopted settings, and the iterative residual reaches 10⁻⁴ °C within eight iterations for the representative case. In a homogeneous, no-seepage limiting case, the model agrees with the classical finite line-source solution with an MAE of 0.012 °C and a maximum relative-error magnitude of 0.41%. The extraction-well fluid-temperature peak occurs at 600–800 m depth, whereas the local heat-transfer direction changes near 1600 m. For the investigated 2500–650–2500 m geometry, the highest cycle-averaged outlet temperature is obtained at an insulation length of 1600 m. Sensitivity analyses further quantify the effects of seepage velocity, equivalent thermal conductivity, geothermal gradient, and the validation insulation-length assumption. Full article

Background/Objectives: Structural inequalities in access to healthcare persist even within systems that have achieved near-universal coverage, reflecting the enduring influence of social determinants of health on service utilization. This study examines horizontal inequity in rehabilitation and specialist care in Türkiye and investigates whether access inequality mediates the well-documented income–depression gradient. Methods: Analyzing the nationally representative 2022 Türkiye Health Survey (adults aged ≥15; N = 22,742), we employed Latent Profile Analysis (LPA) to construct people-centered, multidimensional bodily burden profiles, and assessed need-adjusted access using survey-weighted logistic regression, Erreygers-corrected concentration-index decomposition, Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA), and restricted cubic splines, with measurement-invariance and classification-uncertainty sensitivity analyses. Statistical mediation was examined with natural-effect models and E-value sensitivity analysis. Results: Although the system demonstrated responsiveness to need—78.8% of the highest-burden profile accessed specialist services—only 13.7% of this same group reached dedicated physiotherapy or rehabilitation, revealing a profound structural bottleneck in care coordination for marginalized populations with the greatest functional impairment. A persistent pro-rich gradient was confirmed by an Erreygers-corrected concentration index of 0.058 (95% CI 0.043–0.072), driven additively by income and education. Access did not mediate the income–depression pathway (natural indirect effect OR 1.001, 95% CI 1.0003–1.002). Conclusions: The mental health burden of low income operates through pathways that equitable healthcare access alone cannot address. These findings call for macroeconomic and people-centered health system reforms—including direct physiotherapy access, transportation subsidies, and social protection interventions—to advance health equity in rehabilitation utilization. Full article

Frozen soil on alpine slopes is influenced by inclination and aspect-induced differential solar radiation effects, resulting in non-uniform temperature fields and inclined layered ice lenses that enhance anisotropy and degrade mechanical properties. This study investigates the deformation and strength responses of frozen soil under different temperature-gradient magnitudes and orientations and ice-lens conditions. A stress–strain constitutive model incorporating the magnitude and orientation of the temperature gradient is established. In addition, an equal-scale discrete element model based on the parallel-bond contact model is developed and calibrated against the laboratory results. The numerical specimen is divided into 13 layers, and temperature-dependent interparticle bond properties are assigned layer by layer to reproduce the prescribed magnitude and orientation of the temperature gradient. Results show that the orientation of the temperature gradient significantly alters the mechanical response and failure mode. As the inclination angle increases, the failure mode transitions from compressive dilatancy to combined dilatancy–shear failure and ultimately to shear-dominated failure. At −10 °C, increasing the inclination angle from 0° to 30° reduces the compressive strength by 44.48%. The elastic modulus also decreases with increasing inclination, with a maximum inclination-induced difference of 111.98 kPa. Moreover, the presence of an ice lens further reduces specimen stiffness, and the elastic-modulus difference between ice-lens-bearing and ice-lens-free specimens increases from 5.57 kPa at −1 °C to 75.72 kPa at −10 °C. The DEM results show that particles at the top and bottom of the specimen primarily undergo vertical displacement, whereas particles in the middle region exhibit dominant horizontal displacement, forming an X-shaped shear band. The inclined temperature gradient produces a heterogeneous distribution of interparticle bond strength within each horizontal layer. As inclination increases, the shear band evolves from symmetric to asymmetric; particle displacements on the side toward which the temperature gradient points are larger than those on the opposite side, revealing the microscopic origins of macroscopic mechanical behavior. Full article

Henan Province, a major coal producing region in China, faces severe surface subsidence induced by extensive underground mining, which compromises regional ecological security and infrastructure stability. In this study, small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) was applied to Sentinel-1A imagery acquired from March 2017 to February 2025 to characterize surface deformation in concentrated coal mining areas. A local validation was conducted within a representative mining area in Study Area 3 using measurements from 14 leveling benchmarks acquired between 5 May and 20 July 2023. The comparison yielded an $R^2$ of 0.816 and an RMSE of 9.22 mm, indicating good agreement between the SBAS-InSAR and leveling measurements during the validation interval. The subsidence in the study area exhibits significant spatial heterogeneity and continuous accumulation characteristics. The most negative approximate vertically projected deformation rate reached −371 mm/yr, and the maximum cumulative displacement reached −2101 mm. Scenario-based sensitivity analysis indicated potential projection errors of 6.76–8.34% for a horizontal-to-vertical displacement ratio of 0.10 and 20.28–25.01% for a ratio of 0.30, with larger uncertainty expected near subsidence trough margins. Given the difficulty of quantifying large-scale underground mining parameters, this study employs multisource environmental and topographic variables as auxiliary indicators and develops an XGBoost-SHAP model to evaluate their relative explanatory contributions to the spatial heterogeneity of mining-induced subsidence. Among the selected measurable environmental and topographic variables, groundwater table depth represents the most important measurable explanatory factor for the spatial heterogeneity of subsidence, with distinct response patterns between plain areas with thick unconsolidated layers and piedmont bedrock regions. Furthermore, wavelet coherence analysis identifies scale-dependent spatial associations between topography and subsidence. At the regional scale, elevation exhibits spatial correspondence with the geomorphological framework of contiguous subsidence basins. At the local scale, slope and aspect show localized associations with differential deformation gradients near the margins of subsidence troughs. Full article

Interferometric synthetic aperture radar (InSAR) is a key tool for monitoring landslide deformation in reservoir regions. However, when only ascending and descending line-of-sight (LOS) observations are available, 3D deformation inversion over complex hillslopes remains challenging because of slope-geometry priors and the anisotropic observation sensitivity. This study focuses on hillslopes in the Baihetan Reservoir area after impoundment. We use 340 ascending and descending Sentinel-1A images acquired from April 2021 to October 2024, generating LOS displacement time series using the extended small baseline subset (E-SBAS) technique. We propose a two-track InSAR 3D inversion framework centered on sensitivity-constrained anisotropic regularization (SC-Aniso). In this framework, a local-gradient surface-parallel flow model (LGSPFM) serves as a supporting pixel-scale topographic prior for representing local slope geometry. SC-Aniso constitutes the primary methodological innovation by mapping the inverse joint LOS sensitivities of the E, N, and U components to component-wise regularization weights. This design suppresses noise amplification in weakly constrained directions. Results show that the Baihetan Reservoir area is generally stable, with localized anomalies mainly in typical reservoir-bank landslide zones. The inverted 3D fields reveal coupled subsidence, horizontal displacement and downslope creep in the L01–L03 landslides. GNSS validation shows vertical RMSEs below 5.29 mm, mean 3D rate differences below 4 mm/yr, and an average component-wise rate difference of 2.56 mm/yr. At the optimal regularization parameter, SC-Aniso reduces north–south dispersion in stable areas by 41.9% compared with isotropic regularization. Wavelet analysis indicates a 288–384 day seasonal period for nonlinear displacement of the Xiaomidi landslide, with lags of 24 and 90 days relative to precipitation and reservoir water level, respectively. This study provides support for accurately recovering 3D deformation and interpreting movement mechanisms of landslides under limited two-track LOS observations. Full article

This study evaluates the techno-economic viability of bifacial photovoltaic (PV) systems in Uribia, La Guajira—the department that holds Colombia’s strongest solar resource, with a mean global horizontal irradiance near 5.6 kWh/m²/day and seasonal peaks above 6.0. Despite this endowment, the country’s installed solar capacity remains far below its potential, largely because developers lack the site-specific financial risk analyses that investment decisions require. To address this, we pair stochastic Monte Carlo simulation with a set of machine learning surrogate models and quantify how Colombia’s Law 1715 fiscal incentives—VAT exclusion and accelerated depreciation—reshape the Levelized Cost of Electricity (LCOE) of bifacial PV systems under realistic climatic variability. Drawing on six years of daily meteorological data, we model bifacial PERC performance under two ground-albedo conditions: the natural site value ($\alpha =0.125$) and an optimized surface ($\alpha =0.30$). The results are consistent and encouraging. Under the Law 1715 tax shields, the mean LCOE settles at 0.0588 USD/kWh, and even the 95% Value-at-Risk (VaR) of 0.0638 USD/kWh stays below the prevailing Colombian industrial tariff across every climatic realization evaluated—evidence that the fiscal framework does as much to compress downside risk as it does to lower the average cost. Ground-albedo optimization proved to be the decisive lever: raising $\alpha$ from 0.125 to 0.30 through low-cost surface preparation shortens the payback period to roughly four years and lets the bifacial configuration overtake the cumulative net present value of the monofacial baseline before year seven. The surrogate models tell a complementary story about the structure of the problem. The non-linear algorithms—Support Vector Regression, Gradient Boosting, a Multi-Layer Perceptron and Gaussian Process Regression—reproduce the Monte Carlo response surface almost exactly ($R^2\ge 0.99$, 0.994–0.997), whereas linear models trail at $R^2\approx 0.90$–$0.94$, a gap that quantifies just how strongly the techno-economic drivers of LCOE interact. Full article

Accurate delineation of landslides in RGB optical remote sensing imagery supports rapid disaster mapping and post-event assessment. This remains difficult because landslides are often small and irregular, resemble bare soil or disturbed vegetation, and acquire blurred boundaries when images are resized. We developed AS-UNet, a lightweight U-Net variant with three targeted modifications. The Asymmetric Strip Attention Module uses horizontal and vertical depthwise strip convolutions with parallel channel-spatial reweighting to capture anisotropic landslide morphology. The Channel-Spatial Joint Gate uses decoder semantics to filter selected skip connections while retaining channel-specific spatial responses. The Poly-Harmonized Gradient Dice Loss (PGD Loss) combines pixel-wise, region-overlap, gradient-density, and probability-regularization terms for imbalanced segmentation. At 128 × 128 input resolution, AS-UNet achieved a best-validation IoU of 80.46 ± 0.03% and an independent-test IoU of 77.82 ± 0.32% across three random seeds. AS-UNet contains 8.634 M parameters and processed 380.79 frames per second on the reported hardware. These results indicate a favorable balance between segmentation accuracy and computational efficiency for RGB optical landslide mapping. Full article

To accurately reveal the mechanism of interlayer separation, crack propagation, and progressive instability of vault strata in underground cavities in gentle-dipping bedded rock masses, this paper systematically elucidates the entire mechanical behavior of separation evolution, crack penetration, structural transformation, and step-by-step caving of vault bedded rock masses under excavation disturbance through a comprehensive integration of excavation unloading mechanical analysis, the Griffith strength criterion, and the dynamic transformation theory of beam structures. The results show that excavation induces radial unloading and circumferential stress concentration in the surrounding rock, and the vault rock mass preferentially undergoes interlayer separation along near-horizontal gentle-dipping bedding planes, forming a spatial zoning feature of gradient attenuation from bottom to top: a strong separation zone at the lower part, a transition zone in the middle, and a closed zone at the upper part. The vault strata undergo a cyclic dynamic structural transformation of cantilever beam–fixed-end beam–simply supported beam, exhibiting stepped fracturing and layer-by-layer caving failure characteristics. The fracture and caving range follow a three-stage evolution law of initial increase–peak–subsequent convergence and stabilization. Based on the elastic mechanics stress transformation relationship, a Griffith initiation criterion for surrounding rock of circular cavities under non-axisymmetric loads is derived and established, and mechanical calculation models of single beam and composite beam suitable for stratified rock masses are constructed, which quantitatively reveal the controlling effects of tensile strength of strata, lateral pressure coefficient, tunnel diameter, stratification thickness, and burial depth on crack initiation and failure degree. Verified by a city-gate-shaped tunnel numerical test and an practical engineering case of a large-scale underground tunnel in western China, the theoretical calculation results are in good agreement with the on-site failure morphology and numerical analysis results. The established separation criterion and mechanical model can effectively predict the initiation risk and stability critical conditions of vault strata. The research results can provide a theoretical basis and technical support for the stability evaluation, early warning, and optimal design of support structures of surrounding rock in underground engineering in gentle-dipping bedded rock masses. Full article

The Philippine Sea Basin is one of the world’s largest marginal sea basins, and the spatiotemporal variation characteristics of its sound speed field hold significant importance for deep-sea navigation and positioning as well as underwater acoustic detection. This study investigates the sound speed field in the central Philippine Basin (130.0–134.0° E, 17.5–20.5° N) using the Global Ocean Physics Analysis and Forecast product from the European Union’s Copernicus Marine Environment Monitoring Service (CMEMS), cross-validated with the U.S. HYCOM (Hybrid Coordinate Ocean Model), and independent verified against 69 Argo profiles. We systematically investigate the spatiotemporal variation characteristics of the sound speed field in this region. Temperature and salinity consistency between the two products is established (deviations of <0.5 °C and <0.05 ppt below 400 m), with CMEMS selected as the primary data source for its higher accuracy and greater temporal stability. Three sound speed formulae—Del Grosso, Chen–Millero, and TEOS-10—are intercompared, with TEOS-10 yielding the highest accuracy in cross-validation; it is therefore recommended for its rigorous thermodynamic consistency. Vertical sound speed profiles are evaluated using bi-exponential, Munk canonical, and fourth-order polynomial models. Among them, the bi-exponential model achieves the optimal balance between physical interpretability and fitting accuracy (RMSE = 2.77 m/s, inter-monthly correlation coefficient = 0.857). Its two exponential decay scales characterize the upper-ocean thermocline and the deep stratification, respectively, avoiding the physically unrealistic deep-water fluctuations exhibited by the polynomial model (RMSE = 2.68 m/s) and the poorer generalization of the Munk model (RMSE = 2.97 m/s). Horizontal gradient analysis reveals a cross-directional correlation of approximately 0.5 between sound speed gradients and ocean currents, reflecting the combined modulation of sound speed gradients by Kuroshio advection and thermodynamic stratification. The general gradient control scale is estimated at approximately 100 km × 100 km, confirmed by cross-method consistency between K-means and Gaussian mixture model clustering. Temporal analysis demonstrates that sound speed peak-to-peak variation attenuates rapidly with depth (from ~8.9 m/s at 50 m to <0.1 m/s at 4000 m), and EOF (empirical orthogonal function) analysis reveals that the first four modes explain over 99% of the total variance, with harmonic fitting identifying annual and semi-annual cycles as the dominant periodic components. Sound channel axis depth varies seasonally between 900 and 1125 m (deeper in winter, shallower in spring), with axis sound speed stable at 1480–1484 m/s (slightly higher in winter, slightly lower in spring) and axis thickness ranging from 225 to 450 m (wider in winter, narrower in spring). These results provide prior critical constraints for underwater acoustic positioning, AUV navigation, and long-range sound channel communication and navigation in the central Philippine Sea region. Full article

Alzheimer’s disease (AD) is a neurodegenerative disorder that causes progressive damage to brain neurons, leading to declines in cognitive and behavioral abilities. This deterioration often results in changes in personality and increasing difficulty in thinking and memory over time. Although there is no cure, early detection is crucial as it allows for more effective management and care. Advances in deep learning have significantly improved the accuracy of brain scan analysis for diagnostic purposes. In this study, we utilized the publicly available Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset consisting of subjects diagnosed with AD, Mild Cognitive Impairment (MCI), and Normal Control (NC). Each participant has either Magnetic Resonance Imaging (MRI) or Positron Emission Tomography (PET) neuroimaging data, ensuring representation across heterogeneous modalities. The research focuses on comparing gradient-based, edge-based, and segmentation-based data augmentation techniques for early AD detection using neuroimaging and deep learning approaches, particularly 3D Convolutional Neural Networks (3D CNNs). Various augmentation methods were applied, including directional gradient, azimuth gradient direction, numerical gradient, Sobel horizontal edge filter, superpixel oversegmentation, and Canny edge detection. These techniques are evaluated in both binary and multiclass classification tasks involving MRI and PET scans. The results indicate that optimal performance varied depending on the task and modality. For PET-based classification, directional gradient performed the best for AD vs. NC binary classification, achieving an accuracy of 87.24%, while Canny edge detection was most effective for AD vs. MCI binary classification and AD-MCI-NC multiclass classification tasks, achieving accuracies of 72.77% and 59.04%, respectively. For MCI vs. NC, the best result (accuracy = 64.32%) is achieved by combining azimuth gradient direction with Sobel filtering. In contrast, for the MRI-based AD vs. NC classification task, the highest performance is achieved without applying augmentation (balanced accuracy = 60.90%). This research confirms the efficacy of data augmentation methods in the early diagnosis of AD in clinical settings. Full article

X-ray computed laminography (CL) is a promising nondestructive testing technique for plate-type objects and is of great importance in 3D imaging. Nevertheless, its scanning geometry results in a lack of projection data along in-plane directions, causing severe inter-slice aliasing and cone-beam artifacts, especially under sparse-view sampling. To address this challenge, a prior image-guided adaptive-weighted relative total variation (PiAwRTV) algorithm is proposed for sparse-view CL. Based on relative total variation (RTV), PiAwRTV leverages structural information from a high-quality prior image to guide image reconstruction and introduces weights that vary with local image gradients. The reconstruction model incorporates 2D PiAwRTV in the horizontal direction to perform edge-preserving smoothing and 1D PiAwRTV in the vertical direction to suppress inter-slice blurring. An alternating minimization strategy is employed to decompose this optimization problem into three subproblems for iterative solution. Experimental results demonstrate that the proposed algorithm reconstructs key structural features while reducing cone-beam artifacts, significantly improving the imaging quality of sparse-view CL. Full article