Search Results (5,308)

Background/Objectives: The correlation between in vivo morphological and functional changes in the degenerating retina in a large animal model of retinitis pigmentosa (RP) has not been characterized longitudinally. Herein, spectral domain optical coherence tomography (SD-OCT) was used to monitor the dynamic morphological changes in the Pro23His rhodopsin transgenic (TgP23H) pig model of RP and was correlated with electroretinography (ERG) in the rapid, early phase of photoreceptor degeneration. Methods: TgP23H and wild-type (WT) hybrid pig littermates at the ages of postnatal days 30 (P30), P60, and P90 were studied. The thickness of different retinal layers was quantified using SD-OCT and compared with histology. Retinal function was evaluated with ERG at corresponding time points. Results: In the WT pigs, retinal morphology on SD-OCT was consistent throughout the observation period. In the TgP23H pigs, the retinal thickness decreased significantly from P30 to P90. Moreover, the relative intensity of the ellipsoid zone (EZ) progressively decreased, while the intensity of the interdigitation zone–retinal pigment epithelium (IZ-RPE) progressively increased during this period. Morphological changes in SD-OCT corresponded with histology, as well as the progressively decreased amplitude of the ERG photopic a- and b-waves in the TgP23H pigs. Conclusions: Retinal degeneration can be quantified using SD-OCT by measuring retinal thickness and the intensity of the EZ and IZ-RPE bands in the TgP23H pig. The SD-OCT results correspond with the histologic and ERG assessments of retinal degeneration. These data provide a foundation for future preclinical studies investigating potential new therapeutic strategies in a large animal model of retinitis pigmentosa. Full article

Background: The Arterial Velocity Pulse Index (AVI) and Arterial Pressure–Volume Index (API) are novel non-invasive indices of arterial stiffness derived from cuff-oscillometric measurements. Previous studies have shown that elevated AVI and API are associated with the severity of coronary artery disease and the ability to predict future cardiovascular events. However, the hemodynamic and echocardiographic characteristics of patients with concomitantly high AVI and API remain unclear. Methods: We retrospectively analyzed 112 consecutive cardiovascular outpatients (mean age 69.1 ± 12.2 years, 64.3% male) seen between January and April 2019 at Yokohama City University Hospital. The AVI and API were measured using a multifunctional sphygmomanometer (PASESA AVE1500, Shisei Datum, Japan) and averaged over a maximum of three measurements. Patients were classified into four groups according to previously established cutoff values (AVI ≥ 27, API ≥ 32). Central arterial pulse wave parameters were assessed using SphygmoCor XCEL (AtCor Medical, Sydney, Australia), and echocardiographic parameters were obtained according to standard protocols. Intergroup differences were analyzed using the Kruskal–Wallis test with Steel–Dwass post hoc comparisons. Results: Compared with the low-risk group (low AVI/low API), the high-risk group (high AVI/high API) had significantly higher brachial systolic BP (139.2 [132.8–149] vs. 128 [120–136.7] mmHg, p = 0.0011), central systolic BP (127.5 [122.3–139] vs. 117.7 [110.3–123.7] mmHg, p = 0.0018), and central pulse pressure (56.2 [51.4–60.3] vs. 37.7 [32–43] mmHg, p < 0.001). The forward and reflected wave amplitudes were significantly greater, with prolonged ejection duration and aortic T2 time. The Buckberg subendocardial viability ratio was significantly lower in the high-risk group (129.5 [119.7–145.2] vs. 148.3 [130–168.3], p = 0.040). Echocardiography revealed reduced e′ velocity (5 [4.1–5.8] vs. 6.7 [5.2–8] cm/s, p = 0.035) and increased E/e′ (13.2 [11.1–15.1] vs. 9.7 [7.9–11.3], p = 0.026) in the high-risk group, suggesting the presence of impaired diastolic function without reduced LVEF. Conclusions: Patients with high AVI and API exhibited greater central and peripheral arterial stiffness, higher systolic and pulse pressures, and impaired diastolic function compared with those with low values. These findings support the use of a cardiovascular pathophysiological model in which elevated AVI/API identify individuals at increased risk of progression to heart failure and ischemic heart disease. Full article

Multi-channel common-aperture optical systems, which excel at simultaneous multi-spectral information acquisition, are widely used for image fusion. However, complex systems for long-distance multi-band detection suffer from difficulties in assembly and adjustment and light vignetting. To resolve this, the paper proposes a modular design method that splits the optical path into independent modules: the common-aperture optical path adopts an off-axis reflective beam-shrinking structure to extend the focal length and ensure 100% light input, compared with coaxial multi-channel common-aperture systems. The relay optical path of each spectral channel uses a continuous zoom design for smooth detection–recognition switching. Based on the method, a three-channel common-aperture system is developed integrating visible light (VIS), short-wave infrared (SWIR), and mid-wave infrared (MWIR). The modulation transfer function (MTF) and wavefront distribution of the common-aperture optical path approach the diffraction limit. After integration with the relay optical paths, the system, without global optimization, can achieve the following performance: the root mean square (RMS) across the full field of view (FOV) at different focal lengths for each channel is smaller than the detector pixel size (3.45 μm for VIS, 15 μm for SWIR/MWIR); the MTF exceeds 0.2 at the cutoff frequency. Subsequently, the results of the tolerance analysis verify the feasibility of the design for each module and the advantage of the modular layout in the assembly and adjustment of the system. Finally, the paper discusses the influence of parallel plates on the wavefront distortion of the system and proposes optimization thinking using freeform surfaces. The design results of the study validate the feasibility of the modular layout in simplifying the design and assembly of multi-channel common-aperture optical systems. Full article

Resilience to climate change is a complex concept, especially in metropolitan areas where diverse services and stakeholders interact. Promoting sustainable climate adaptation, a resilience assessment method focused on regional areas and nature-based solutions is presented, along with its open-access, web-based platform, supporting resilience assessment, planning, and monitoring. Floods, droughts, heat or cold waves, windstorms, and forest fires can be assessed. A framework for holistic assessment and other framework, addressing critical infrastructure, are integrated. Four resilience dimensions are assessed: organizational (governance, social aspects, finance); spatial (exposure, impacts, and mapping); functional (service management, interdependencies); and physical (infrastructure robustness, redundancy). Strategic services comprise, e.g., water, waste, and natural areas. Resilience capacities, e.g., to prevent, respond, and recover from disruptions, are also assessed. The paper emphasizes new developments and assessment. Practical step-by-step guidance aligned with assessment purposes is included, aiming to address observed limitations (e.g., fragmented service provision, communication silos, data constraints). Overall results of a Spanish metropolitan area (AMB) and an exploratory application to an Austrian rural case (SLR) are also presented. Following the guidelines, AMB progressed from an essential to a comprehensive assessment. Overall, almost 1/3 of the metrics are advanced or progressing. SLR assessed its resilience capabilities regarding electrical infrastructure. Full article

This work presents a millimeter-wave half-mode substrate integrated waveguide filter with high selectivity, using through glass via technology. Compared to a traditional printed circuit board, the benefits of high precision and integration afforded by the glass-based process enable the substrate-integrated waveguide to be employed at a higher operating frequency. A novel negative coupling structure is proposed for achieving a quasi-elliptic function response, and its coupling mechanism is investigated to explore the properties of the finite transmission zeros. The proposed coupling slots allow for flexible adjustment of the coupling between the half-mode substrate integrated waveguide cavities from positive to negative by modulating the corresponding geometrical parameters. As a prototype, a glass-based fourth-order bandpass filter is synthesized, simulated, fabricated and measured. Subsequently, good matching is captured, confirming the validity of the topology. The proposed glass-based negative coupling structure is promising for realizing substrate integrated waveguide filters with a quasi-elliptic function response, especially operating at millimeter-wave band. Full article

Schrödinger’s path to the quantum mechanical wave equation was heuristic and guided more by physical intuition than formal deduction. Here we derive the Schrödinger equation for the particle’s wave function $\mathsf{\Psi }$, assuming that the complex function $\mathsf{\Psi }(\mathrm{t},\overrightarrow{r})$ has a meaning of the probability amplitude to find the particle at time $t$ at point $\overrightarrow{r}$ and the relations $E=\hslash \omega$, $\overrightarrow{p}=\hslash \overrightarrow{k}$ expressing particle energy and momentum in terms of the frequency and wave vector of the associated probability wave. Full article

Offshore oil exploration and the volume of imported crude oil shipping have increased steadily, elevating the risk of oil spills. An advanced offshore oil film identification method is proposed to realize the accurate and robust recognition and segmentation of oil films from marine radar images in offshore oil spill detection. This method integrates feature engineering with an improved Beetle Antennae Search (BAS) optimization algorithm, aiming to address the key issues of low discrimination between oil films and complex marine backgrounds and insufficient spill boundary localization accuracy in radar image analysis. First, the raw radar image was transformed into the Cartesian coordinate system, and a filtering procedure was applied to attenuate interference. Subsequently, the gray distribution and local contrast of the denoised image was further improved. Afterwards, the complexity of the grayscale distribution within each feature map was quantified using Shannon entropy. The Top-K feature maps with the highest entropy values were subsequently used to construct an information-rich subset. The subset was then processed through a pixel-wise averaging strategy to generate a coupled feature image. Then, Otsu threshold was used to refine ocean wave regions. Finally, the oil films were segmented with an improved BAS optimization algorithm. The fitness function of the improved BAS algorithm was augmented through the integration of edge fitting accuracy, and a target-proximity penalization scheme. Through an adaptive step-length modulation paradigm and Perceptual Mechanism, it can achieve a marked improvement in search accuracy and achieving precise segmentation of oil slicks. The detection accuracy of the proposed method is significantly enhanced relative to the traditional BAS algorithm and existing marine radar oil spill detection methods. The IOU, Dice, recall and F1-score reached 81.2%, 89.6%, 85.2%, and 90.1% respectively. This method not only advances the methodological rigor of spill detection but also provides critical data support for the development of more effective control and remediation practices. Full article

Background/Objectives: Lupus Nephritis (LN) is a major complication of Systemic Lupus Erythematosus (SLE) leading to significant morbidity. While biopsy is the gold standard, non-invasive tools are needed for longitudinal monitoring. This study aims to evaluate the diagnostic utility of Shear Wave Elastography (SWE) in detecting subclinical renal damage (fibrosis) in SLE patients with a history of LN who are currently in clinical remission (inactive disease), and to compare its efficacy with Doppler ultrasonography (DUS). Methods: This cross-sectional study included 80 SLE patients and 41 age- and sex-matched healthy controls. Crucially, all SLE patients were in the clinically inactive disease (SLEDAI-2K < 6) at the time of evaluation. Patients were stratified into two groups: those with a history of LN (LN Group, n = 37) and those without (Non-LN SLE Group, n = 43). Strict exclusion criteria were applied to eliminate non-SLE renal comorbidities. Renal parenchymal stiffness (kPa) was measured using SWE, and the renal resistive index (RI) was assessed using DUS. SWE findings were correlated with renal function tests and disease activity scores. Results: Despite being in clinical remission, the LN group exhibited significantly higher renal stiffness values (Median: 1.60 kPa) compared to the non-LN SLE group (1.40 kPa, p < 0.001) and healthy controls (1.32 kPa, p < 0.001). No significant difference was observed between the non-LN SLE group and controls. Unlike SWE, renal RI values showed no statistically significant difference among the groups (p > 0.05). Correlation analysis revealed that renal stiffness was positively associated with prior serum creatinine and disease activity (SLEDAI-2K), and negatively associated with eGFR. Conclusions: SWE is superior to DUS (RI) in detecting renal parenchymal changes in LN patients. The persistence of elevated stiffness during the inactive disease suggests that SWE captures cumulative chronic damage (remodeling and fibrosis) rather than just acute inflammation. Consequently, SWE holds promise as a non-invasive surrogate for monitoring disease chronicity in SLE patients. Full article

Semiconductor optical amplifiers (SOAs) are central to the development of ultrafast, low-power all-optical signal processing systems. Their strong nonlinear response, compact size, and compatibility with photonic integration platforms make them key enablers for implementing all-optical logic functions beyond the limitations of electronic switching. This review offers a comprehensive analysis of the principal SOA technologies used in all-optical logic gate implementations, including conventional bulk and quantum well SOAs, quantum dot SOAs (QD-SOAs), photonic crystal SOAs (PhC-SOAs), reflective SOAs (RSOAs), and carrier reservoir SOAs (CR-SOAs). For each architecture, we examine the carrier dynamics, gain recovery mechanisms, saturation behavior, and fabrication considerations, together with their associated nonlinear effects such as cross-gain modulation, cross-phase modulation, and four-wave mixing. We further evaluate reported implementations of key logic operations—AND, NAND, OR, NOR, XOR, and XNOR—highlighting performance trade-offs in terms of speed, extinction ratio, operational power, integration complexity, and scalability. The review concludes with current challenges and emerging research directions aimed at realizing fully integrated, high-speed, and energy-efficient all-optical logic systems based on next-generation SOA technologies. Full article

Elastic wave scattering in polycrystalline materials has been a long-lasting topic in seismology and physical acoustics. Numerous analytical scattering models have been reported for polycrystals with random grain orientations. However, the elastic wave scattering in polycrystals with a preferred grain orientation (crystallographic texture) has not been well studied. This study develops a general ultrasonic scattering model that correlates the scattering coefficients and attenuation coefficients with orientation distribution coefficients (ODCs) for polycrystalline materials with a crystallographic texture. These models are valid for aggregates of triclinic grains with arbitrary texture symmetry. Since different terminologies for orientation distribution functions (ODFs) are adopted in quantitative texture analysis, the relations between different terminologies are also summarized in this study. Furthermore, for two special cases—hexagonal polycrystalline materials with a fiber texture and cubic polycrystalline materials with orthotropic texture symmetry—explicit expressions for the ultrasonic backscattering coefficient through ODCs are derived. The explicit relationship between ultrasonic backscattering and ODCs not only manifests how the individual texture coefficients impact ultrasonic scattering but also makes it possible to determine ODCs up to the eighth order experimentally from ultrasonic scattering measurements. This type of forward model also can be applied to the microstructure characterization of textured polycrystals. Full article

Supercritical CO₂ pipeline transportation is a critical component of the carbon capture, utilization and storage (CCUS) industry chain, where long distance operation introduces inherent risks of accidental leakage. During the leakage process of supercritical CO₂ pipelines, throttling pressure reduction and the Joule–Thomson effect generate distinct negative pressure wave characteristics. The magnitude of the leakage directly impacts localization effectiveness, particularly under small leakage conditions where negative pressure wave signals are less pronounced, so the leakage is difficult to effectively detect. To solve this problem, the mutual correlation function model for pipeline leakage was developed by using the mutual correlation analysis method, and it was verified by the dense-phase CO₂ leakage data from Trondheim University of Technology. Based on the TGNET software, the actual pipeline model of the Yanchang oilfield is established, and the captured leakage signal is imported into MATLAB for differential pressure conversion, using the verified cross-correlation function model of the differential pressure signal to calculate the time difference between the arrival of the negative pressure wave at the two ends of the pipeline. Finally, the actual leakage location was determined. The simulation results indicate that the leakage detection method based on mutual correlation analysis of negative pressure wave signals exhibits varying localization performance under different leakage rates. By enhancing negative pressure wave characteristics and utilizing mutual correlation analysis, this method effectively addresses the challenges of indistinct negative pressure wave features and difficult localization during small leakage conditions. When leakage exceeds 5%, the relative error is controlled within ±5.40%, meeting the preliminary localization requirements for rapid identification and regional determination in engineering applications. Through the application of actual engineering cases, it is shown that this method has high accuracy in pipeline leakage detection. These findings provide theoretical and methodological support for supercritical CO₂ pipeline leakage detection in the CCUS projects currently under construction. Full article

School burnout is an increasing concern in highly competitive educational contexts. As artificial intelligence (AI) becomes embedded in classrooms, it shapes both learning processes and students’ stress experiences. Grounded in Mindset Theory and Conservation of Resources framework, this longitudinal study examined whether AI learning support moderates the link between stress mindset and school burnout. A sample of 850 Chinese middle school students (Mage = 15.09, 41% boys) completed two waves of surveys one year apart. Regression results showed that viewing stress as enhancing predicted lower subsequent burnout after controlling for baseline burnout and demographics. Although AI learning support did not directly predict burnout, its interaction with stress mindset was significant: the negative association between a positive stress mindset and burnout was observed when AI learning support was high. These findings suggest that AI can function as an external resource that amplifies adaptive beliefs, offering new pathways for fostering resilience in digital learning environments. Full article

Near-field scanning microwave microscopy (NSMM) offers the ability to probe local electromagnetic properties beyond the classical Abbe diffraction limit, but achieving high resolution over practical scan areas remains challenging. In this work, we introduce a novel three-dimensional (3D) NSMM probe consisting of a split-ring resonator (SRR) coupled to a microstrip line and loaded with vertically extended metallic bars. The 3D loading enhances electric-field localization in the sensing region by introducing field singularities. Full-wave numerical simulations are used to extract the field-spread function ($FSF$) of the probe and to quantify how probe geometry, stand-off distance, and bar dimensions control the $FSF$ and its spatial-frequency (k-space) content. An imaging model is then developed in which the NSMM image is represented as a convolution between the object and $FSF$ in one and two dimensions. This framework demonstrates that progressively localized $FSFs$, obtained through 3D loading and resonator miniaturization, systematically improve image fidelity and preserve higher spatial frequencies. The probe is fabricated using printed circuit board technology (PCB) with vertically attached metallic bars, and its performance is validated by imaging a dielectric slab containing a cylindrical air-filled void. The measured line profiles and two-dimensional images are in good agreement in general characteristics with the convolution-based model, confirming that the proposed 3D SRR-based probe operates as a spatial filter whose engineered near-field distribution governs the achievable resolution in NSMM imaging. Full article

Reaction–diffusion equations provide a fundamental framework for modelling spatial population dynamics and invasion processes in mathematical biology. Among these, Fisher’s equation combines diffusion with logistic growth to describe the spread of an advantageous gene and the formation of travelling population fronts. In this work, we investigate the one-dimensional Fisher’s equation using Lie symmetry analysis to obtain a deeper analytical understanding of its wave propagation behaviour. The Lie point symmetries of the partial differential equation are derived and used to construct similarity variables that reduce Fisher’s equation to ordinary differential equations. These reduced equations are then solved by a combination of direct integration and the tanh method, yielding explicit invariant and travelling-wave solutions. Symbolic computations in MAPLE are employed to compute the symmetries, verify the reductions, and generate illustrative plots of the resulting wave profiles. The computed solutions capture sigmoidal fronts connecting stable and unstable steady states, providing clear information about wave speed and shape. Overall, this study demonstrates that Lie group methods, combined with hyperbolic-function techniques, offer a powerful and systematic approach for analysing Fisher-type reaction–diffusion models and interpreting their biologically relevant invasion dynamics. Full article

Coordinated control across multiple signalized intersections is essential for mitigating congestion propagation in urban road networks. However, existing DQN-based approaches often suffer from unstable action switching, limited interpretability, and insufficient capability to model spatial spillback between adjacent intersections. To address these limitations, this study proposes a Policy-Regulated and Aligned Deep Q-Network (PRA-DQN) for cooperative multi-intersection signal control. A differentiable policy function is introduced and explicitly trained to align with the optimal Q-value-derived target distribution, yielding more stable and interpretable policy behavior. In addition, a cooperative reward structure integrating local delay, movement pressure, and upstream–downstream interactions enables agents to simultaneously optimize local efficiency and regional coordination. A parameter-sharing multi-agent framework further enhances scalability and learning consistency across intersections. Simulation experiments conducted on a 2 × 2 SUMO grid show that PRA-DQN consistently outperforms fixed-time, classical DQN, distributed DQN, and pressure/wave-based baselines. Compared with fixed-time control, PRA-DQN reduces maximum queue length by 21.17%, average queue length by 18.75%, and average waiting time by 17.71%. Moreover, relative to classical DQN coordination, PRA-DQN achieves an additional 7.53% reduction in average waiting time. These results confirm the effectiveness and superiority of the proposed method in suppressing congestion propagation and improving network-level traffic performance. The proposed PRA-DQN provides a practical and scalable basis for real-time deployment of coordinated signal control and can be readily extended to larger networks and time-varying demand conditions. Full article