Search Results (10)

Pansharpening is a fundamental image fusion technique used to enhance the spatial resolution of remote sensing imagery; however, it inevitably introduces spectral distortions that compromise the reliability of downstream analyses. Existing no-reference (NR) quality assessment methods often fail to exclusively isolate these spectral errors from spatial artifacts or lack sensitivity to specific radiometric inconsistencies. To address this gap, this paper proposes a novel No-Reference Multivariate Gaussian-based Spectral Distortion Index (MVG-SDI) specifically designed for pansharpened images. The methodology extracts a hybrid feature set, combining First Digit Distribution (FDD) features derived from Benford’s Law in the hyperspherical color space (HCS) and Color Moment (CM) features. These features are then used to fit Multivariate Gaussian (MVG) models to both the original multispectral and fused images, with spectral distortion quantified via the Mahalanobis distance between their statistical parameters. Experiments on the NBU dataset showed that the MVG-SDI correlates more strongly with standard full-reference benchmarks (such as SAM and CC) than existing NR methods like QNR. Tests with simulated distortions confirmed that the proposed index remains stable and accurate even when facing specific spectral degradations like hue shifts or saturation changes. Full article

Islands provide valuable opportunities to study how isolation affects phenotypic variation. Even though orchid bees are highly mobile, their movement can still be restricted by marine barriers. In this study, we assessed whether insular isolation impacts wing shape in the orchid bee Euglossa mixta across the Coiba archipelago and a nearby mainland site in Western Panama. Our study analyzed 271 individuals using geometric morphometrics, focusing on forewing venation landmarks, and evaluated the variation using multivariate analyses of shape variation and quantifying the shape of Mahalanobis distances. Additionally, we conducted a Mantel test to explore the relationship between geographic distance and morphological divergence. Our findings reveal that wing shape variation in E. mixta is largely conserved but shows fine-scale structuring consistent with spatial patterns expected in insular systems. These results suggest that even highly mobile pollinators may experience enough isolation for subtle phenotypic shifts to occur, highlighting the sensitivity of geometric morphometrics for detecting early stages of morphological differentiation. Full article

Background: The management of acute ischemic stroke (AIS) in anticoagulated patients presents a clinical challenge, as concerns about safety and efficacy often limit access to recanalization therapies. Despite the widespread use of direct oral anticoagulants (DOACs) and vitamin K antagonists (VKAs), their impact on functional recovery and mortality following intravenous thrombolysis (IVT) and mechanical thrombectomy (MT) remains uncertain. Therefore, this study investigates the association between prior anticoagulation and 90-day outcomes in AIS patients undergoing reperfusion therapy. Methods: We conducted a retrospective cohort analysis using our institutional stroke registry, including AIS patients admitted to the Department of Neurology at our university between February 2023 and 2025. Anticoagulated patients were 1:1 propensity score-matched with non-anticoagulated controls (n = 126 per group) using Mahalanobis distance matching with a caliper, adjusting for age, sex, hypertension, diabetes, stroke severity (National Institutes of Health Stroke Scale [NIHSS] at admission and 72 h), and pre-stroke functional status (pre-morbid modified Rankin Scale [pre-mRS]). Primary endpoints at 90 days were functional independence (modified Rankin Scale [mRS] ≤ 2), mRS-shift, and mortality (mRS = 6). Predictors of outcome were assessed using multivariable logistic regression and generalized additive models (GAMs). Subgroup analyses evaluated the effects of anticoagulation type and treatment modality. Results: Among 866 AIS patients (DOAC n = 100, VKA n = 48, non-anticoagulated n = 718), 426 (49.2%) underwent reperfusion therapy (IVT n = 195, MT n = 163, IVT + MT n = 68). Before matching, anticoagulated patients were less likely to achieve functional independence (34.5% vs. 52.1%, odds ratio [OR] = 0.48, 95% confidence interval [CI] [0.33–0.70], p < 0.001), had a greater mRS-shift (2.53 vs. 1.79, p < 0.001), and higher mortality (30.4% vs. 14.5%, OR = 2.58, 95% CI [1.72–3.88], p < 0.001). However, after matching, these differences were no longer statistically significant. NIHSS, 72hNIHSS, and pre-mRS were the strongest independent predictors of outcome (p < 0.001), while anticoagulation status had no significant effect. Conclusions: Recanalization therapy was not associated with worse functional outcomes in selected anticoagulated AIS patients. These findings suggest that prior anticoagulation alone should not preclude reperfusion therapy in otherwise eligible patients, and underscore the importance of individualized, evidence-based decision-making in acute stroke care. Full article

This study analyzes retinal fundus images to distinguish healthy retinas from those affected by diabetic retinopathy (DR) and glaucoma using a dual-framework approach: vascular texture analysis and global color distribution analysis. The texture-based approach involved segmenting the retinal vasculature and extracting eight Haralick texture features from the Gray-Level Co-occurrence Matrix. Significant differences in features such as energy, contrast, correlation, and entropy were found between healthy and pathological retinas. Pathological retinas exhibited lower textural complexity and higher uniformity, which correlates with vascular thinning and structural changes observed in DR and glaucoma. In parallel, the global color distribution of the full fundus area was analyzed without segmentation. RGB intensity histograms were calculated for each channel and averaged across groups. Statistical tests revealed significant differences, particularly in the green and blue channels. The Mahalanobis distance quantified the separability of the groups per channel. These results indicate that pathological changes in retinal tissue can also lead to detectable chromatic shifts in the fundus. The findings underscore the potential of both vascular texture and color features as non-invasive biomarkers for early retinal disease detection and classification. Full article

Background/Objectives: Direct oral anticoagulants (DOACs) are now the guideline-recommended alternative to vitamin K antagonists (VKAs) for long-term anticoagulation in patients with non-valvular atrial fibrillation. However, accurately assessing their impact on ischemic stroke outcomes remains challenging, primarily due to uncertainty regarding anticoagulation status at the time of hospital admission. This preliminary study addresses this gap by using point-of-care testing (POCT) to confirm DOAC activity at bedside, allowing for a more accurate comparison of 90-day functional outcomes between anticoagulated and non-anticoagulated stroke patients. Methods: We conducted a retrospective cohort study of 786 ischemic stroke patients admitted to the University of Pécs between February 2023 and February 2025. Active DOAC therapy was confirmed using the ClotPro^® viscoelastic testing platform, with ecarin Clotting Time (ECT) employed for thrombin inhibitors and Russell’s Viper Venom (RVV) assays for factor Xa inhibitors. Patients were categorized as non-anticoagulated (n = 767) or DOAC-treated with confirmed activity (n = 19). Mahalanobis distance-based matching was applied to account for confounding variables including age, sex, pre-stroke modified Rankin Scale (mRS), and National Institutes of Health Stroke Scale (NIHSS) scores at admission and 72 h post-stroke. The primary outcome was the change in mRS from baseline to 90 days. Statistical analysis included ordinary least squares (OLS) regression and principal component analysis (PCA). Results: After matching, 90-day functional outcomes were comparable between groups (mean mRS-shift: 2.00 in DOAC-treated vs. 1.78 in non-anticoagulated; p = 0.745). OLS regression showed no significant association between DOAC status and recovery (p = 0.599). In contrast, NIHSS score at 72 h (p = 0.004) and age (p = 0.015) were significant predictors of outcome. PCA supported these findings, identifying stroke severity as the primary driver of outcome. Conclusions: This preliminary analysis suggests that ischemic stroke patients with confirmed active DOAC therapy at admission may achieve 90-day functional outcomes comparable to those of non-anticoagulated patients. The integration of bedside POCT enhances the reliability of anticoagulation assessment and underscores its clinical value for real-time management in acute stroke care. Larger prospective studies are needed to validate these findings and to further refine treatment strategies. Full article

Bearing fault diagnosis under varying operating conditions faces challenges of domain shift and labeled data scarcity. This paper proposes a dual-stream hybrid-domain adaptation network (DS-HDA Net) that fuses CNN-extracted time-domain features with MLP-processed frequency-domain features for comprehensive fault representation. The method employs hierarchical domain adaptation: marginal distribution adaptation (MDA) for global alignment and conditional domain adaptation (CDA) for class-conditional alignment. A novel soft pseudo-label generation mechanism combining Gaussian mixture models (GMMs) with the Mahalanobis distance provides reliable supervisory signals for unlabeled target domain data. Extensive experiments on the Paderborn University and Jiangnan University datasets demonstrate that DS-HDA Net achieves average accuracy values of 99.43% and 99.56%, respectively, significantly outperforming state-of-the-art methods. The approach effectively addresses bearing fault diagnosis under complex operating conditions with minimal labeled data requirements. Full article

This research focuses on enhancing the preventive maintenance strategies currently employed for induction motors within ship propulsion systems, advocating for a shift towards a predictive maintenance model. It introduces a real-time monitoring framework that continuously observes the induction motor, providing essential support to maintenance personnel. The motor operates under a range of environmental and operational conditions, including temperature fluctuations, rotational speeds, and mechanical loads. These variations can obscure the current time series data, potentially masking signs of actual damage and hindering effective damage detection. To tackle this issue, the proposed framework utilizes artificial intelligence (AI) technology, specifically the well-established autoencoder, in conjunction with the Mahalanobis statistical distance. This approach accounts for the diverse operating conditions during the training phase, allowing it to model complex, non-linear relationships and effectively differentiate between normal and anomalous states. The framework is integrated into a decision support platform designed for real-time operations in maritime settings, offering a sophisticated system architecture that aims to align advanced damage detection methodologies with the maritime industry’s need for real-time, user-friendly solutions. Full article

The Prediction Accuracy Index (PAI) monitors stability, defined as whether the predictive power of a model has deteriorated due to a change in the distribution of the explanatory variables since its development. This paper shows how the PAI is related to the Mahalanobis distance, an established statistic for examining high leverage observations in data. This relationship is used to explore properties of the PAI, including tools for how the PAI can be decomposed into effects due to (a) individual observations/cases, (b) individual variables, and (c) shifts in the mean of variables. Not only are these tools useful for practitioners to help determine why models fail stability, but they also have implications for auditors and regulators. In particular, reasons why models containing econometric variables may fail stability are explored and suggestions to improve model development are discussed. Full article

Peptide and protein drug molecules fold into higher order structures (HOS) in formulation and these folded structures are often critical for drug efficacy and safety. Generic or biosimilar drug products (DPs) need to show similar HOS to the reference product. The solution NMR spectroscopy is a non-invasive, chemically and structurally specific analytical method that is ideal for characterizing protein therapeutics in formulation. However, only limited NMR studies have been performed directly on marketed DPs and questions remain on how to quantitively define similarity. Here, NMR spectra were collected on marketed peptide and protein DPs, including calcitonin-salmon, liraglutide, teriparatide, exenatide, insulin glargine and rituximab. The 1D ¹H spectral pattern readily revealed protein HOS heterogeneity, exchange and oligomerization in the different formulations. Principal component analysis (PCA) applied to two rituximab DPs showed consistent results with the previously demonstrated similarity metrics of Mahalanobis distance (D_M) of 3.3. The 2D ¹H-¹³C HSQC spectral comparison of insulin glargine DPs provided similarity metrics for chemical shift difference (Δδ) and methyl peak profile, i.e., 4 ppb for ¹H, 15 ppb for ¹³C and 98% peaks with equivalent peak height. Finally, 2D ¹H-¹⁵N sofast HMQC was demonstrated as a sensitive method for comparison of small protein HOS. The application of NMR procedures and chemometric analysis on therapeutic proteins offer quantitative similarity assessments of DPs with practically achievable similarity metrics. Full article

Point cloud segmentation for planar surface detection is a valid problem of automatic laser scans analysis. It is widely exploited for many industrial remote sensing tasks, such as LIDAR city scanning, creating inventories of buildings, or object reconstruction. Many current methods rely on robustly calculated covariance and centroid for plane model estimation or global energy optimization. This is coupled with point cloud division strategies, based on uniform or regular space subdivision. These approaches result in many redundant divisions, plane maladjustments caused by outliers, and excessive number of processing iterations. In this paper, a new robust method of point clouds segmentation, based on histogram-driven hierarchical space division, inspired by kd-tree is presented. The proposed partition method produces results with a smaller oversegmentation rate. Moreover, state-of-the-art partitions often lead to nodes of low cardinality, which results in the rejection of many points. In the proposed method, the point rejection rate was reduced. Point cloud subdivision is followed by resilient plane estimation, using Mahalanobis distance with respect to seven cardinal points. These points were established based on eigenvectors of the covariance matrix of the considered point cluster. The proposed method shows high robustness and yields good quality metrics, much faster than a FAST-MCD approach. The overall results indicate improvements in terms of plane precision, plane recall, under-, and the over- segmentation rate with respect to the reference benchmark methods. Plane precision for the S3DIS dataset increased on average by 2.6pp and plane recall- by 3pp. Both over- and under- segmentation rates fell by 3.2pp and 4.3pp. Full article