Search Results (619)

Hotelling’s T-squared statistic provides an interpretable framework for multivariate fault detection; however, its rolling implementation is highly sensitive to transient casewise outliers in the reference window. Such abnormal observations may inflate the sample covariance matrix, enlarge the monitoring boundary, and consequently mask subsequent moderate fault signals. This study proposes a robust rolling Hotelling fault detection method, denoted as RRH-FD, to reduce this masking effect. The proposed method estimates the rolling reference center and scatter matrix using reweighted minimum covariance determinant (RMCD) estimators, while each newly arriving observation is evaluated directly as a potential fault signal. The monitoring threshold is obtained using a robust Hotelling approximation rather than the classical Hotelling distribution. A simulation study was conducted under both clean and contaminated rolling reference scenarios. Under clean reference windows, the proposed robust procedures remained competitive with the classical rolling Hotelling detector, showing only a modest efficiency loss. Under contaminated reference windows, RRH-FD substantially improved detection performance. The adaptive RRH-FD method reduced the average detection delay by approximately 37.6% relative to the classical rolling detector, while the fixed MCD fraction 0.85 version achieved an approximate reduction of 42.4%. The proposed methods also improved early detection rates within the first 25 and 50 post-fault monitoring points. Boundary inflation was quantified using the log-determinant ratio between the classical sample covariance matrix and the RMCD scatter estimate. This analysis further confirmed that the advantage of RRH-FD becomes more pronounced as the classical covariance boundary is more strongly inflated by transient outliers. An R package, RRHFD, was developed to facilitate implementation and reproducibility. Full article

Batch effects arising from variations in hardware, acquisition protocols, and reconstruction parameters present a critical challenge in radiomics, limiting the generalizability of models across multicentre studies. Existing harmonization methods, such as ComBat, CovBat, z-score normalization, and Generative Adversarial Networks, exhibit significant limitations when applied to high-dimensional radiomic data. ComBat assumes a linear feature space and tends to leave residual center-specific information recoverable by downstream classifiers. This paper introduces RiTex (Riemannian Texture Harmonization), a framework that solves a generalized eigenvalue problem between class-aware biological scatter and Ledoit–Wolf-regularized per-batch covariances, with the SPD-manifold Fréchet mean used as a principled averaging step. We evaluate RiTex on the 50-dataset radMLBench benchmark and on a new four-center head-and-neck benchmark with known center labels ($n$ = 380 patients, k = 4 centers from TCIA: HGJ, MDACC, Maastro, QIN). On radMLBench, RiTex reduces the batch auto-detection AUC in 48/50 (96%) datasets, 42/50 (84%) reductions remain significant after Benjamini–Hochberg correction; the mean Batch AUC reduction is ΔBatch = −0.365 (95% bootstrap CI [−0.418, −0.312]), with no significant degradation in biological AUC (mean ΔBio = +0.018, 95% CI [−0.011, +0.047]). On the H&N benchmark with real center labels, RiTex reduces the Batch AUC from 0.74 to 0.59, while ComBat and CovBat leave it at ≈0.98. A component-wise ablation shows that the dominant source of empirical performance is the GEVD step, together with Ledoit–Wolf shrinkage. The SPD Fréchet mean acts as a theoretical scaffold with a negligible empirical contribution (ΔBatch AUC = −0.014 vs. arithmetic mean). Full article

We present the results of applications of ATLAS2.0 to experimental data in this final part of our series of publications. ATLAS2.0 retrieves particle microphysical parameters from multiwavelength Raman and high-spectral-resolution lidar measurements of backscatter (β) coefficients at three wavelengths, i.e., λ = 355, 532, and 1064 nm, extinction (α) coefficients at two wavelengths, i.e., 355 and 532 nm, and particle linear depolarization ratios (PLDR, δ) at three wavelengths, i.e., 355, 532, and 1064 nm, so-called 3β + 2α + 3δ datasets. The explicit use of PLDRs is a novel feature compared to all previously developed lidar data retrieval algorithms. For the tests of ATLAS2.0, we use data that were taken with NASA Langley Research Center’s airborne high-spectral-resolution lidar 2 (HSRL-2). We show the results of two case studies. We compare the particle microphysical parameters and single-scattering albedo (SSA) retrieved with ATLAS2.0 to results obtained with the first version of ATLAS, our Tikhonov regularization algorithm (TiARA), and in situ observations carried out aboard an aircraft that followed the airborne HSRL-2 instrument. The solutions converge within the retrieval uncertainties of these techniques. The discrepancy between the measured and backcalculated, i.e., retrieved 3β + 2α + 3δ data on average stays below 10%. The difference between the retrieved and measured PLDRs is, on average, even less. This comparably good convergence of the optical datasets (experimental versus backcalculated) of both measurement cases can only be achieved if the investigated aerosol particles are analyzed on the basis of a sphere-spheroid mixture. Full article

Aircraft targets in SAR imagery often exhibit discrete scattering characteristics, significant variations in pose and scale, strong speckle noise in background clutter, and complex background interference, which jointly hinder stable structural feature extraction and accurate target localization. Existing detectors for SAR aircraft recognition primarily rely on bounding-box regression and classification; they do not completely exploit target structural cues, spatial attention, and frequency-domain information. To address these limitations, we propose a collaborative detection framework that integrates an uncertainty-aware keypoint-driven module (UAKM) with a fractional Fourier convolution backbone (S-FRConv). UAKM introduces a center-keypoint regression branch that jointly predicts keypoint coordinates and Laplacian scale parameters and employs a 2D Laplace negative log-likelihood loss to estimate uncertainty. The derived dense uncertainty heatmap is then used as spatial attention weights to guide distribution-based regression and multi-scale feature re-weighting, without requiring any additional annotations. S-FRConv embeds the Fractional Fourier Transform into shallow backbone layers and C2f modules, enabling joint spatial–spectral feature modeling that suppresses speckle noise and enhances edge and orientation representations. Experiments on the public SAR-AIRcraft-1.0 dataset demonstrate that the proposed method systematically improves the detection performance. For the Nano model, the overall mAP50 increases from 0.810 to 0.867, and the mAP 50:95 improves from 0.637 to 0.655 compared with the baseline, corresponding to gains of 5.7 and 1.8 percentage points, respectively. These results validate the effectiveness and generalization potential of combining uncertainty-driven spatial attention with fractional spectral feature enhancement for SAR aircraft target detection. Full article

Amid an ongoing environmental crisis marked by high deforestation rates in the Brazilian Amazon, two new species of chactid scorpions are herein described. Cayooca puchus sp. n. is described from an inselberg in the municipality of Mucajaí, state of Roraima, northern Brazilian Amazon. The new species resembles Cayooca venezuelensis but differs by denser body granulation and strongly costate, scattered granular ventromedian and ventral prosubmedian carinae. Brotheas cernii sp. n., described from the same locality, resembles Brotheas granulatus and B. subgranulatus but differs by smaller body size, granular ventral carinae on metasomal segment I, strongly granular pedipalp chelae, and spinoid granules on ventral metasomal carinae of segments III–V. These findings reinforce the Amazon as a major center of biodiversity and highlight the likelihood that numerous species remain undescribed. Full article

Chronic obstructive pulmonary disease (COPD) is a progressive respiratory disorder characterized by persistent airflow limitation and chronic airway inflammation. Current therapeutic strategies primarily offer symptomatic relief and are often limited by systemic side effects, inadequate lung deposition, and poor patient compliance. Naringin (NAR), a natural flavonoid with strong antioxidant, anti-inflammatory, and anti-fibrotic activities, has demonstrated potential in mitigating COPD-associated pathophysiology. However, its therapeutic application is restricted by poor water solubility, low bioavailability, and rapid metabolism. Nanotechnology-based drug delivery systems, particularly poly(lactic-co-glycolic acid) (PLGA) nanoparticles, provide an effective approach for lung-targeted therapy. Their nanoscale size promotes deep lung deposition, enhanced cellular uptake, reduced lung clearance, improved therapeutic efficacy, and reduced systemic side effects. The present study aimed to develop NAR-loaded PLGA nanoparticles (NAR PLGA NP) for enhanced cell-targeting in inflammatory lung conditions. NAR PLGA NP were prepared using the emulsion solvent evaporation method, with PLGA in the organic phase and soya lecithin (SL) with poly(vinyl alcohol) (PVA) as surfactants in the aqueous phase. A face-centered central composite design was employed to optimize the formulation. The optimized nanoparticles were characterized for size distribution by dynamic light scattering, entrapment efficiency, Transmission Electron Microscopy (TEM), Fourier Transform Infrared (FTIR), Differential Scanning Calorimetry (DSC), X-Ray Diffraction (XRD), and in vitro drug release. The safety of PLGA and lecithin-coated PLGA nanoparticles (LC PLGA NP) was assessed using an MTT assay on lung epithelial cells, followed by cellular uptake studies, angiogenesis by chick Yolk Sac Membrane (YSM) assay, and in vitro evaluation of reactive oxidative stress (ROS) and anti-inflammatory activity. The optimized PLGA formulation showed a hydrodynamic diameter of 201 ± 1 nm with PDI 0.20 ± 0.03 and EE of 76.11 ± 2.1%, and 81.7 ± 4.9% drug release at 72 h, whereas LC PLGA NP showed a hydrodynamic diameter of 308 ± 3 nm, PDI of 0.21 ± 0.05, entrapment efficiency of 82.45 ± 4.8%, and 71.4 ± 3.2% drug release at 72 h. Both PLGA NP and LC PLGA NP demonstrated good cytocompatibility with lung epithelial cells, efficient cellular uptake, and a significant reduction in intracellular reactive oxygen species (ROS) levels (**** p value < 0.0001). Moreover, the formulations markedly suppressed pro-inflammatory cytokines, including TNF-α, IL-6, and IL-1β, indicating anti-inflammatory activity. The angiogenesis assay further suggested their ability for lung tissue repair and remodeling. These findings support the potential of LC PLGA NP as a promising cell-specific targeting system for naringin in inflammatory lung conditions. Full article

Background/Objectives: Recessive titinopathies caused by biallelic TTN truncating variants (TTNtvs) present a clinically heterogeneous spectrum from fetal demise to late-onset slowly progressive distal muscular dystrophy. Prognostic counseling is challenging due to the vast size of the TTN gene, complex splicing patterns, and differential expression throughout developmental stages and tissues. This paper aims to delineate the regional genotype patterns and clinical characteristics of recessive titinopathies described from the prenatal period onwards to inform genotype–phenotype associations and genetic counseling. Methods: We analyzed clinical and genetic data from a prenatal-onset cohort with biallelic TTNtvs from both previously reported cases and novel cases from our center. To characterize the regional distribution of biallelic variants within this specific cohort, a two-dimensional scatter plot was utilized to map variants onto 10 biological regions (R1–R10) and 55 analytical units (U1–U55). We also performed Fisher’s exact tests on the subset of 50 cases with confirmed survival records to evaluate statistically significant associations between biallelic regional or percent spliced-in (PSI) thresholds combinations and severe clinical endpoints (intrauterine demise or death before 5 years). Results: A total of 96 prenatal cases from 76 unrelated families were analyzed. Decreased fetal movement was the most commonly reported symptom, observed in 81.3% (78/96) of cases, which was followed by arthrogryposis in 45.8% (44/96) and amniotic fluid volume abnormalities in 35.4% (34/96). Additionally, of the 95 cases with known pregnancy outcomes, 25.3% (24/95) resulted in termination and 11.6% (11/95) resulted in intrauterine demise (IUD), while 63.2% (60/95) reached birth with over 16.7% (10/60) being preterm. Among 60 live-born infants, severe postnatal morbidity was high: 45.0% (27/60) experienced respiratory failure, and 33.3% (20/60) died before the age of five. In this cohort, 84.4% (81/96) of cases possessed at least one TTNtv in either the metatranscript-only or A-band regions. The most common biallelic changes involved TTNtvs in both the A-band and metatranscript-only regions, accounting for 35.4% (34/96) of cases, followed by metatranscript-only combined with I-band variants at 16.7% (16/96), regardless of the PSI score of exons. Overall, 83.3% (80/96) had ≥1 variant on low-PSI (<50%) exons, and 19.8% (19/96) had both alleles on these low-PSI exons. In the 50 patients with confirmed survival records, biallelic changes (excluding splice-site variants) affecting both high-PSI (>90%) exons were significantly associated with severe outcomes (intrauterine demise or death before 5 years; exact p = 0.015), whereas the metatranscript-only plus I-band combination conferred a significantly lower risk of lethality before 5 years of age (exact p = 0.001). Conclusions: Our findings add to the accumulating evidence that TTNtvs on low PSl exons or metatranscript-only regions are frequently observed among reported prenatal-onset recessive titinopathy. Health surveillance for heterozygous carriers among family members is warranted due to the substantial risk for adult-onset dilated cardiomyopathy and peripartum cardiomyopathy. Full article

As a non-rivalrous, replicable, and non-consumable production factor, data offers conditions for resource-efficient value creation, and the conversion from scattered data resources into measurable data assets sits at the center of firm competitiveness and sustainable allocation of digital factors. How artificial intelligence supports this conversion, and how executive cognition shapes its strength, are taken up within a framework drawing on the resource-based view, dynamic capability, and upper-echelons theory. Using 24,251 firm-year observations from Chinese A-share listed firms over 2012–2022, panel fixed-effects estimation yields a positive association between AI and data asset formation, stable across instrumental-variable estimation, propensity score matching, Heckman correction, and alternative measures of both variables. AI deepens data mining capability through stronger research and development investment and widens data-carrying capacity through expanded digital infrastructure, with the two channels opening up the relationship. Cognitive flexibility improves the fit between AI and shifting business scenarios, while cognitive complexity supports balanced allocation of technological resources across competing constraints; both characteristics strengthen the main association. The pattern is more pronounced among state-owned enterprises and firms in eastern and central regions, with industry differences less clear-cut. The findings inform differentiated policy design for sustainable digital development in emerging-market settings. Full article

Railway construction and industrialization played an important role in reshaping the urban morphology of inland resource-based cities in Republican-period China. Taking Taiyuan during 1912–1937 as a case study, this paper examines the spatial association between railway corridors and industrial locations and discusses how this relationship contributed to the reorganization of urban space. Historical maps, railway maps, local gazetteers, archival materials, and existing literature were integrated into a historical GIS database. Kernel density estimation, railway buffer analysis, mean-center analysis, and standard deviational ellipse analysis were used to reconstruct the staged evolution of industrial nodes and railway corridors. The results show that Taiyuan’s industrial space evolved from a scattered point-based pattern to a railway-oriented axial-belt layout and then to a polycentric industrial corridor. Industrial nodes gradually moved closer to railway lines, while the mean center of industrial distribution shifted from the traditional city toward railway-related industrial districts. The findings suggest that Taiyuan followed one possible railway–resource–industry pathway shaped by railway construction, resource endowments, provincial industrial policies, land conditions, and the inherited urban fabric. This study provides historical spatial evidence for identifying railway–industrial heritage corridors and understanding inland industrial urban form. Full article

The Multi-Destination Vehicle Routing Problem (MD-VRP) with a heterogeneous electric fleet is a critical challenge in optimizing commuter services for large-scale institutions and logistics operations. To address the complexities of electric fleet composition uncertainty and multi-center routing in “micro-city” campus environments, this paper establishes a robust multi-objective programming model. The model aims to simultaneously minimize three conflicting objectives, the total number of vehicles, total driving distance, and total electric energy consumption (kWh), under constraints of flow conservation and vehicle availability. Considering the nondeterministic polynomial-time hard (NP-hard) nature of the problem, a novel two-stage hybrid heuristic algorithm is proposed. In the first stage, a Modified Kruskal’s algorithm is employed to aggregate scattered stops into optimized clusters to reduce dimensionality. In the second stage, a State-Compressed Dynamic Programming (SC-DP) algorithm is applied to determine the optimal routing and electric vehicle type selection for each cluster. The methodology is validated using a case study of a large-scale campus network with 100 nodes. The optimization results identify an optimal fleet configuration of 41 campus electric commuter vehicles across three specific types (capacities of 45, 55, and 60), resulting in an annual total energy consumption of 5893.98 kWh. Compared with a global Ant Colony Optimization (ACO) baseline in this case study, the proposed framework reduces the required fleet size by 22.6% and annual energy consumption by 9.2%; however, this comparison should be interpreted as a preliminary case-study benchmark because the proposed method adopts a decomposition-based “Cluster-First, Route-Second” strategy. The results indicate that the approach achieves higher solution efficiency, offering an economically and environmentally friendly scheme for electric vehicle fleet operations. Full article

The uniformity of local photoelectric properties in infrared detectors is critical for detection sensitivity. However, micro-nano-scale surface abnormalities introduced during mercury cadmium telluride (HgCdTe) fabrication systematically degrade in-plane photoelectric response consistency. To overcome the optical diffraction limits of standard far-field metrology, we utilized a cryogenic scattering-type scanning near-field optical microscopy (Cryo-SNOM) system to achieve the first super-resolution, in situ imaging of local near-field photocurrent in HgCdTe photoconductive detectors at 10 K. Device-level measurements reveal that sub-wavelength surface protrusions (~tens of nanometers high) act as strong recombination centers, suppressing local photocurrent and causing a consistent 10~20% relative signal attenuation compared to planar regions. Power and bias-dependent testing indicate these defects function as unsaturated linear recombination states. Increasing bias voltage amplifies the coupling between the external field and the defect’s built-in field, broadening the local depletion region and driving a non-linear escalation in the attenuation ratio. This study establishes quantitative engineering tolerances for morphological deviations at the nanoscale, providing critical criteria for the chip integration, structural optimization, and precision manufacturing of high-performance infrared sensing arrays. Full article

Considerable progress has been made in predicting nominal NVH behavior in electric drivetrains, but the acoustic scatter observed across manufactured units remains insufficiently understood. In practice, nominally identical drive units may still exhibit noticeably different tonal behavior because small deviations in gears, shafts, bearings, fits, centering features, or assembly phase modify the excitation, transfer, and radiation mechanisms of the system. This review examines how manufacturing and assembly variability influences NVH performance in electric drive units and e-axles, with particular focus on the rotor–shaft–gear–bearing–housing system. Unlike broader EV NVH reviews, the present work focuses specifically on variability-induced acoustic scatter and its propagation along the drivetrain NVH generation and transmission path. To support transparency and consistency, the literature search and selection process followed a structured, PRISMA-inspired approach across Scopus, Web of Science, Google Scholar, and SAE Mobilus for the 2015–2026 period. From 387 identified records, 50 studies were retained after duplicate removal, screening, and full-text assessment. The selected literature was synthesized into eight thematic categories: imbalance; run-out and eccentricity; bearing clearance and preload; spline and pilot centering; thermal effects; phase indexing; transmission error and sidebands; and end-of-line NVH diagnostics. The reviewed literature shows that manufacturing- and assembly-induced deviations can significantly alter transmission error, sideband structure, shaft-order content, and final tonal response, even when individual components remain within nominal tolerance limits. Beyond synthesizing the evidence base, the review organizes existing modeling and diagnostic practices into a structured framework for variability-aware NVH assessment, based on explicit deviation parameterization, hierarchical model fidelity, intermediate excitation metrics, thermal-state awareness, and closer integration with production and measurement data. Overall, the findings support a shift from nominal NVH assessment toward robustness-oriented, production-representative interpretation and future prediction of acoustic scatter in electric drivetrains. Full article

Reliable determination of the in-plane biaxial mechanical behavior of particle-reinforced composite adhesives under multiaxial stress conditions requires cruciform specimen geometries that achieve high stress uniformity in the measurement zone. In this study, the elastic response obtained from uniaxial tensile tests was verified through representative volume element (RVE)-based micromechanical analyses by systematically examining mesh sensitivity and RVE edge size convergence across multiple random microparticle distributions under periodic boundary conditions. The probability density characterization of the effective elastic constants indicated that the remaining scatter is mainly governed by microstructural randomness and decreases as the RVE edge size increases, supporting a nearly direction-independent effective stiffness associated with the random microparticle distribution. The RVE-predicted mean tensile modulus remained in close agreement with experiments, with relative deviations of approximately −2% to +2% across the investigated reinforcement levels. The validated material parameters were based on a dynamic XGBoost (eXtreme Gradient Boosting) surrogate model driven by the geometric design variables, fillet radius and center thickness, combined with an adapted version of the LIPOTR (Lipschitz Optimization with Trust Region) algorithm. The initial and optimized geometries were then compared using both experimentally determined elastic properties and selected RVE-predicted engineering constants for the 2, 6, and 10 wt% materials. The significant reductions in the equivalent S_eqv, normal S₁₁ and S₂₂, and shear S₁₂ stress variations within the gauge zone of the optimized candidate geometry resulted in improved stress homogeneity. Full article

Aiming at the urgent heat dissipation demands of high-power, high-integration electronic devices, Cu/Al composite heat sinks combine the high thermal conductivity of copper and the lightweight advantage of aluminum, becoming a mainstream solution for advanced thermal management systems. The significant physicochemical differences between Cu and Al, however, make high-quality joining a technical bottleneck. In this study, flux-free ultrasonic brazing with a Zn-based filler metal was used to join 6061 aluminum alloy and industrial pure copper. Gradient heat treatment (55–300 °C) was subsequently applied to systematically investigate its effect on the microstructure, microhardness, and thermal properties of the joints. The results show that the as-brazed joint exhibited excellent bonding (97.3% bonding rate) and shear strength (95.24 MPa). The weld seam consisted of Zn solid solution, Cu solid solution, and Al-Cu-Zn ternary compounds. Heat treatment did not induce new phases but led to the coarsening of Zn-Al-Cu compounds and aggregation of the eutectic structure, reducing grain boundaries. Consequently, the microhardness at the weld center varied non-monotonically, and the thermal conductivity of the joint showed an overall increasing trend with rising heat treatment temperature. This enhancement is attributed to reduced phonon scattering at diminished grain boundaries. This study clarifies the heat treatment–microstructure–thermal properties relationship, providing important guidance for the thermal performance optimization of Cu/Al composite heat sinks. Full article