Search Results (73)

The growing number of on-orbit spacecraft and the increasing volume of telemetry data have made intelligent anomaly detection in multi-channel telemetry essential for mission operations. Current spacecraft anomaly detection methods primarily rely on statistical models or time-series deep learning approaches, which often fail to explicitly model spatiotemporal dependencies across multiple telemetry channels. This shortcoming limits their ability to capture the dynamically evolving and intricately coupled relationships between variables. To overcome this limitation, a Progressive Spatiotemporal Graph (PSTG) model is proposed for anomaly detection in multi-channel spacecraft telemetry. PSTG employs a multi-scale patch embedding module to extract hierarchical semantic features from multi-channel time series, effectively reducing the dimensionality of the spatiotemporal graph. It constructs a sparse adjacency matrix using a multi-head attention mechanism that integrates intra-channel temporal dynamics, inter-channel spatial correlations, and cross-channel spatiotemporal interactions. An improved multi-head graph attention network then captures pairwise dependencies among nodes within the adjacency matrix. As a result, PSTG encodes rich spatiotemporal representations derived from intricate variable interactions, enabling accurate, real-time prediction of multi-channel telemetry. Furthermore, a dynamic thresholding mechanism is incorporated into PSTG to perform online anomaly detection based on prediction residuals. Extensive experiments on real-world spacecraft telemetry data collected over 84 months show that PSTG outperforms eleven state-of-the-art benchmark methods in almost all cases across multiple evaluation metrics. Finally, visualizations of the learned adjacency and attention matrices are presented to interpret the spatiotemporal modeling process, providing operators with actionable insights into the detected anomalies and facilitating root cause analysis. Full article

Based on density functional theory, the structural, mechanical, and photoelectric properties of the perovskite material Cs₂SeCl₆ were systematically studied under pressures ranging from 0 to 50 GPa. Analysis of structural parameters indicates that the lattice constant, unit cell volume, and bond length decrease progressively with increasing pressure. Notably, the material maintains structural stability across the entire pressure range. Electronic property calculations show that Cs₂SeCl₆ retains an indirect band gap under pressure, with the band gap value monotonically decreasing as pressure increases. The orbital contributions remain almost unchanged at different pressures. The conduction band is mainly composed of Cl-p and Se-p orbitals, while the valence band is dominated by Cl-p orbitals. The analysis of the effective mass indicates that the transport capability of charge carriers is enhanced under compression. Mechanical stability and ductility were evaluated by calculating the elastic constants and derived mechanical moduli, confirming that the material remains mechanically stable under high pressure. Optical properties were investigated by computing the dielectric function, reflectivity, refractive index, optical absorption coefficient, and extinction coefficient. Collectively, the findings of this work demonstrate that the pressurized Cs₂SeCl₆ exhibits excellent structural robustness, improved charge transport, and promising photoelectric performance, making it a strong candidate for applications in solar cells and other photoelectronic devices. Full article

High-accuracy spatiotemporal monitoring of surface nitrogen dioxide (NO₂) concentrations is essential for air quality management. This study evaluates machine learning-based estimates of near-surface NO₂ concentrations using data from the geostationary GEMS instrument and the polar-orbiting TROPOMI over China in 2022. Four tree-based models—Random Forest, XGBoost, CatBoost, and LightGBM—were trained by integrating satellite vertical-column densities with multi-source meteorological and ancillary data. Results show that CatBoost achieved the highest accuracy, with an R² of 0.842 for GEMS and 0.765 for TROPOMI, alongside the lowest RMSE and MAE. Models trained on GEMS data consistently outperformed TROPOMI-based models across all metrics. This advantage is primarily attributed to the substantially larger training sample size enabled by GEMS’s high temporal resolution, as confirmed through a controlled experiment with consistent sample sizes which isolated the effect of data volume. Spatially, GEMS estimates captured sharper concentration gradients and localized emission hotspots, while TROPOMI produced smoother fields. Temporally, only GEMS allowed the reconstruction of detailed diurnal patterns and near-real-time pollution episode tracking. This study confirms the significant added value of geostationary satellite data for high-frequency air quality monitoring and analysis when combined with machine learning. Full article

Aerospace power systems, including satellites in low earth orbit (LEO) and geostationary earth orbit (GEO), face stringent thermal constraints to minimize size, weight, and power (SWaP). Gallium nitride (GaN) devices offer superior radiation hardness—critical for the harsh space environment—and MHz-level switching capabilities. This high-frequency operation minimizes passive components, particularly magnetics, thereby reducing the overall volume. However, above 10 MHz, magnetic cores become impractical due to material limitations. To address these issues, this article proposes a design methodology for a GaN-based quasi-square-wave (QSW) buck converter integrated with a PCB air-core inductor. First, the impact of the switching frequency and dead time on the zero-voltage switching (ZVS) condition is elaborated. Then, a power loss model accounting for various loss mechanisms is presented. To overcome high GaN body diode reverse conduction loss, an auxiliary diode is employed. Based on the model, a design procedure is developed to optimize the inductor for 10 MHz operation while maximizing efficiency. To validate the design, a 28 V/12 V, 18 W prototype was built and tested. Experimental results demonstrate a peak efficiency of 86.5% at 10 MHz. The auxiliary diode improves efficiency by 4%, verifying reverse conduction loss mitigation. Thermal analysis confirms a full-load case temperature of 62.2 °C, providing a 47.8 °C safety margin compliant with aerospace derating standards. These findings validate the solution for high-frequency, space-constrained aerospace applications. Full article

Peripheral nerve injuries, particularly those involving the sciatic nerve, remain a major clinical challenge due to incomplete functional recovery and the limited translation of preclinical advances into effective therapies. This review synthesizes current evidence on the phase-specific evaluation of sciatic nerve regeneration in preclinical models, integrating behavioral, sensory, electrophysiological, and morphological approaches across the acute, subacute (Wallerian degeneration), early regenerative, and late regenerative phases. By mapping functional readouts onto the underlying biological events of each phase, we highlight how tools such as the Sciatic Functional Index, Beam Walk test, Rotarod test, nerve conduction studies, and nociceptive assays provide complementary and often non-interchangeable information about motor, sensory, and neuromuscular recovery. We further examine emerging therapeutic strategies, including intraoperative electrical stimulation, immunomodulation, platelet-rich plasma, bioengineered scaffolds, conductive and piezoelectric conduits, exosome-based hydrogels, tacrolimus delivery systems, and small molecules, emphasizing the importance of aligning their mechanisms of action with the dynamic microenvironment of peripheral nerve repair. Despite substantial advancements in experimental models, an analysis of publication trends and registries reveals a persistent translational gap, with remarkably few clinical trials relative to the high volume of preclinical studies. To illustrate how mechanistic insights can be complemented by molecular-level characterization, we also present a targeted computational analysis of alpha-lipoic acid (ALA,) including frontier orbital energies, physicochemical descriptors, and docking interactions with IL-6, TGF-β, and a growth-factor receptor—performed solely for this molecule due to its documented structural availability and relevance. By presenting an integrated, phase-specific framework for functional assessment and therapeutic evaluation, this review underscores the need for standardized, biologically aligned methodologies to improve the rigor, comparability, and clinical relevance of future studies in sciatic nerve regeneration. Full article

Low-viscosity epoxy-containing diluents are used to reduce the initial viscosity of highly filled, wear-resistant epoxy systems and to improve filler wetting and dispersion. This study determined physical parameters by an atomic-increment approach and electronic descriptors using the Parametric Method 3 (PM3) semi-empirical method. Clear relationships were established between the effective molar cohesion energy and the solubility parameter with van der Waals volume. Linear dependencies were also obtained between the diluent surface tension and spreading coefficients on model high-hardness fillers, including silicon carbide, boron carbide, and normal corundum. The activity of epoxy diluents depends on the lowest unoccupied molecular orbital energy. These diluents influence processing and the final physical and mechanical properties of composites, making their selection critical for strength, hardness, and wear resistance. Computational analysis enables prediction of diluent behavior, reducing experimental time and cost. Integrating physical and quantum-chemical data into epoxy diluent design accelerates the search for optimal components and improves production of durable, high-performance epoxy composites. Full article

In the era of smart garments, textile electrodes for electromyography (EMG) or functional electric stimulation (FES) represent a very interesting and promising area of development and exploitation. In this frame, we conducted a patent landscape analysis of textile solution for EMG sensing and FES actuation, using Espacenet as a reference database and Orbit Intelligent platform as a data analysis tool. The landscape analysis focused on the following aspects: filing trends, top applicants in this domain, main publication countries, forward citations, and collaborations between applicants. Following the screening process, a total of 97 patent families were subjected to subsequent analysis. China and the United States account for the majority of patents. The main applicants by volume of the topics studied are universities or research public entities. Full article

Acetaminophen (APAP) is a widely used pharmaceutical increasingly detected as a contaminant in aquatic environments due to its persistent nature and incomplete removal by conventional wastewater treatment. This study investigates the adsorption performance and mechanisms of commercial activated carbon (M) and its hydrothermally modified form (MH) for APAP removal. Characterization via elemental analysis, X-ray photoelectron spectroscopy (XPS), and N₂ adsorption isotherms revealed that hydrothermal treatment reduced oxygen content and enhanced micro- and mesopore volumes, resulting in a more homogeneous and carbon-rich surface. Batch adsorption experiments conducted under varying pH (5–7) and temperature (30–40 °C) conditions showed that MH achieved up to 94.3% APAP removal, outperforming the untreated carbon by more than 15%. Kinetic modeling indicated that adsorption followed a pseudo-second-order mechanism (R² > 0.99), and isotherm data fitted best to the Langmuir model for MH and the Freundlich model for M, reflecting their differing surface properties. Adsorption was enhanced at lower pH and higher temperatures, consistent with an endothermic and pH-dependent mechanism. Complementary density functional theory (DFT) simulations confirmed that π–π stacking is the dominant interaction between APAP and the carbon surface. The most favorable configuration involved coplanar stacking with non-oxidized graphene (ΔG = −33 kJ/mol), while oxidized graphene models exhibited weaker interactions. Natural Bond Orbital (NBO) analysis further supported the prevalence of π–π interactions over dipole interactions. These findings suggest that surface deoxygenation and improved pore architecture achieved via hydrothermal treatment significantly enhance APAP adsorption, offering a scalable strategy for pharmaceutical pollutant removal in water treatment applications. Full article

Background: Accurate reconstruction of the orbit after trauma or oncological resection requires reliable anatomical references. In unilateral cases, the contralateral orbit can guide repair, but bilateral injuries or pathologies remove this option. To address this problem, we developed a new morphological classification of orbits based on three linear dimensions. Methods: A total of 499 orbits from patients of Caucasian descent (age 8–88 years) were analyzed using three-dimensional models generated from cone-beam and fan-beam CT scans. Orbital depth (D), height (H), and width (W) were measured, and proportional indices were calculated. K-means clustering (k = 3) identified recurring morphotypes, validated by linear discriminant analysis (LDA) and supported by ANOVA, Kruskal–Wallis, and correlation tests (age and sex). Results: Three morphotypes were identified: Tall & Broad (type A, 33.5%), Deep & Broad (type B, 30.2%), and Compact (type C, 36.2%). All dimensions differed significantly between groups (ANOVA, p < 1 × 10⁻¹⁶; η² = 0.40–0.51). Male orbits were significantly deeper and wider than female ones (p < 0.001). LDA demonstrated excellent separation with 97.5% accuracy. A simplified decision algorithm achieved 82.1% classification accuracy. In situations where only orbital depth could be measured, an alternative cut-off-based method reached 61.5% accuracy, with type B and C better distinguished than type A. Conclusions: The proposed classification provides a reproducible framework for describing orbital morphology. It may serve as a reference in cases where local anatomy is disrupted or the contralateral orbit is unavailable. Even millimeter-scale differences in orbital dimensions may correspond to clinically relevant changes in orbital volume and globe position, underlining the potential usefulness of this system in surgical planning. Full article

In this paper, we provide a complete analysis of the most general spherical solution of the Lyra scalar-tensor (LyST) gravitational theory based on the proper definition of a Lyra manifold. Lyra’s geometry features the metric tensor and a scale function as fundamental fields, resulting in generalizations of geometrical quantities such as the affine connection, curvature, torsion, and non-metricity. A proper action is defined considering the correct invariant volume element and the scalar curvature, obeying the symmetry of Lyra’s reference frame transformations and resulting in a generalization of the Einstein–Hilbert action. The LyST gravity assumes zero torsion in a four-dimensional metric-compatible spacetime. In this work, geometrical quantities are presented and solved via Cartan’s technique for a spherically symmetric line element. Birkhoff’s theorem is demonstrated so that the solution is proven to be static, resulting in the Lyra–Schwarzschild metric, which depends on both the geometrical mass (through a modified version of the Schwarzschild radius $r_S$) and an integration constant dubbed the Lyra radius $r_L$. We study particle and light motion in Lyra–Schwarzschild spacetime using the Hamilton–Jacobi method. The motion of massive particles includes the determination of the $r_{\mathrm{ISCO}}$ and the periastron shift. The study of massless particle motion shows the last photon’s unstable orbit. Gravitational redshift in Lyra–Schwarzschild spacetime is also reviewed. We find a coordinate transformation that casts Lyra–Schwarzschild spacetime in the form of the standard Schwarzschild metric; the physical consequences of this fact are discussed. Full article

Graves’ orbitopathy (GO) is a debilitating autoimmune disorder that may require surgical orbital decompression in severe cases with risk of proptosis and optic neuropathy. This report presents a case treated with navigation-assisted three-wall orbital decompression, planned with preoperative imaging and assessed using postoperative analysis. Intraoperative navigation enabled precise localization of critical structures, improving osteotomy execution. Postoperatively, orbital volume increased by 3.5 cm³ (right eye) and 4.0 cm³ (left eye), while proptosis was reduced by 6 mm in both eyes. These changes correlated with intraocular pressure normalization and functional improvement. This was further supported by a postoperative Clinical Activity Score (CAS) of 0, indicating active orbital inflammation. Image-guided surgery (IGS) achieved an average proptosis reduction of 3.8 mm, slightly superior to that of non-guided techniques. Although IGS enhances precision and functional outcomes, it requires longer surgical time and incurs higher costs, highlighting the need for prospective studies on long-term efficacy This case supports the importance of integrating advanced imaging and navigation-assisted techniques in GO management to improve both functional and aesthetic outcomes. Full article

Radiation-induced keratoconjunctivitis sicca (KCS) is a significant late complication in dogs receiving radiation therapy for intranasal tumors, particularly with hypofractionated intensity-modulated radiation therapy (IMRT). This retrospective case-control study was performed to identify anatomical and dosimetric risk factors for KCS in 15 canine patients treated with IMRT delivered in 4–6 weekly fractions of 8 Gy. Orbital structures were retrospectively contoured, and dose–volume metrics (D50) were calculated. Receiver operating characteristic (ROC) curve analysis and odds ratios were used to evaluate the associations between radiation dose and KCS development. Six dogs (33%) developed KCS within three months post-treatment. Statistically significant dose differences were observed between affected and unaffected eyes for the eyeball, cornea, and retina. ROC analyses identified dose thresholds predictive of KCS: 13.8 Gy (eyeball), 14.9 Gy (cornea), and 17.0 Gy (retina), with the retina showing the highest odds ratio (28.33). To ensure clinical relevance, KCS was diagnosed based on decreased tear production combined with corneal damage to ensure clinical relevance. This study proposes dose thresholds for ocular structures that may guide treatment planning and reduce the risk of KCS in canine patients undergoing IMRT. Further prospective studies are warranted to validate these thresholds and explore mitigation strategies for high-risk cases. Full article

The growing density of space objects in low Earth orbit (LEO), driven by the deployment of large satellite constellations, has elevated the risk of orbital collisions and the need for high-precision conjunction analysis. Traditional methods based on Two-Line Element (TLE) data suffer from limited accuracy and insufficient uncertainty modeling. This study proposes a hybrid collision assessment framework that combines Monte Carlo simulation, spline-based refinement of the time of closest approach (TCA), and a multi-stage deterministic refinement process. The methodology begins with probabilistic sampling of TLE uncertainties, followed by a coarse search for TCA using the SGP4 propagator. A cubic spline interpolation then enhances temporal resolution, and a hierarchical multi-stage refinement computes the final TCA and minimum distance with sub-second and sub-kilometer accuracy. The framework was validated using real-world TLE data from over 2600 debris objects and active satellites. Results demonstrated a reduction in average TCA error to 0.081 s and distance estimation error to 0.688 km. The approach is computationally efficient, with average processing times below one minute per conjunction event using standard hardware. Its compatibility with operational space situational awareness (SSA) systems and scalability for high-volume screening make it suitable for integration into real-time space traffic management workflows. Full article

The quality of life (QoL) perception has been studied in neurological diseases; however, there is limited information linking brain morphological characteristics, QoL, and cognition. Human behavior and perception are associated with specific brain areas that interact through diffuse electrochemical networking. We used magnetic resonance imaging (MRI) to analyze the brain region volume (BRV) correlation with the scores of Rand’s 36-item Short Form Survey (SF-36) and cognitive domains (memory and dementia status). We analyzed data from 420 adult participants in the Maracaibo Aging Study (MAS). Principal component analysis with oblimin axis rotation was used to gather redundant information from brain parcels and SF-36 domains. Canonical correlation was used to analyze the relationships between SF-36 domains and BRV (adjusted for intracranial cavity), as well as sex, age, education, obesity, and hypertension. The average age (±SD) of subjects was 56 ± 11.5 years; 71% were female; 39% were obese; 12% had diabetes, 52% hypertension, and 7% dementia. No sex-related differences were found in memory and orientation scores, but women had lower QoL scores. The 1st and 2nd canonical correlation roots support the association of SF-36 domains (except social functioning and role emotional) and total brain volume, frontal lobe volume, frontal pole, lateral orbital lobe, cerebellar, and entorhinal areas. Other variables, including age, dementia, memory score, and systolic blood pressure, had a significant influence. The results of this study demonstrate significant correlations between BRV and SF-36 components, adjusted for covariates. The frontal lobe and insula were associated with the mental health component; the lateral-orbital frontal lobe and entorhinal area were correlated with the physical component. Full article

Background/Objectives: Dry eye disease (DED) is a multifactorial inflammatory disease that disrupts the ocular surface, causing tear film instability, epithelial damage, and chronic inflammation. Mesenchymal stem cell-derived exosomes (MSC-exos) are promising therapeutics with immunomodulatory and regenerative properties. This study investigates the therapeutic effects of umbilical cord MSC-derived exosomes (UCMSC-exos) in a severe dry eye model, induced by a surgical resection of the infra-orbital (ILG) and extra-orbital lacrimal gland (ELG) in rats. Methods: Clinical evaluations, including tear volume measurement, slit lamp biomicroscopy, fluorescein staining, and spectral domain optical coherence tomography (SD-OCT), were performed to assess corneal neovascularization, corneal abrasion, and epithelial/stromal thickness. Histopathological analysis, immunohistochemistry, and mRNA gene expression were conducted to evaluate corneal tissue changes and inflammatory marker expression. Results: The results show that the treatment group exhibited significantly reduced corneal neovascularization compared to the control group (p = 0.030). During the first month, the Exo group also had a significantly lower corneal fluorescein staining area (p = 0.032), suggesting accelerated wound healing. SD-OCT analysis revealed that the corneal epithelial thickness in the treatment group was closer to normal levels compared to the control group (p = 0.02 and p = 0.006, respectively). UCMSC-exos treatment also modulated the expression of α-SMA and apoptosis in the cornea. Additionally, the gene expression of inflammatory cytokines (IL-1β and TNF-α) were downregulated. Conclusions: These findings suggest that MSC-exosome therapy offers a novel, cell-free regenerative approach for managing severe DED, modulating inflammatory response. Full article