Search Results (655)

Precise control of thin liquid film deposition is crucial in applications where film stability and internal liquid flow significantly impact the dry film shape or the efficiency of sample or drug delivery. No prior work has automated the extraction and measurement uncertainty quantification of film geometric parameters from dual-view optical visualization with minimal user input. We present Python-based software that extracts time-resolved film thickness, width, and the positions of three contact lines from visual data using computer vision. The utility of such analysis is demonstrated by depositing 30% glycerol on a flexible tape through a circular nozzle orifice. The nozzle is positioned at a distance of h = 0.3 mm from the tape at an angle of attack α = 45°, with deposition controlled at a volume flow rate $\dot{V}$ = 30 μL min⁻¹ and tape velocity v = 1.0 mm s⁻¹. Expanded measurement uncertainties are 21 μm, 22 μm, and 53 μm for the upstream static, downstream static, and upstream dynamic contact line positions, respectively, with maximum relative uncertainties of 10.3% and 8.2% for film thickness and width. Static contact line oscillations remain within measurement uncertainty, whereas the upstream dynamic contact line exhibits resolvable oscillations. This dual-view framework provides high-resolution insights into liquid film dynamics, which is crucial for comprehensive control of liquid film deposition. Full article

Accurate, non-contact vital-sign monitoring promises a scalable alternative to conventional sensors, yet low signal quality and long recording times have limited real-life adoption. We present a dual-modality system that combines Eulerian video magnified remote photoplethysmography (rPPG) from facial videos with optical flow-based shoulder tracking to estimate heart rate (HR) and respiratory rate (RR) from ultra-short 15 s recordings. With 200 participants, each providing 2 videos, 387 videos passed strict usability criteria, excluding flicker, blur, occlusion, and low illumination. For 15 s recordings, the HR estimates reached 98.5% accuracy within a ±10 beats per minute tolerance (MAE = 3.25, RMSE = 4.88, r = 0.93; p < 0.05) and the RR estimates achieved 98.4% accuracy within a ±5 respirations per minute tolerance (MAE = 0.69, RMSE = 0.87, r = 0.90; p < 0.05), exceeding prior studies that required 30 to 60 s recording lengths. Computational analysis on a standard home computer confirmed feasibility, with near real-time performance achievable on optimized hardware. By integrating complementary modalities and rigorous video quality control, the system overcomes low-SNR challenges, delivering high-fidelity, clinically validated vital signs monitoring. These results establish a robust, scalable, and precise framework for clinical and home care, demonstrating that accurate, contact-free HR and RR monitoring can now be achieved in seconds, making rapid, real-life vital signs assessment practical and accessible. Full article

Programmable photonic integrated circuits implement optical switching and processing by interconnecting reconfigurable 2 × 2 cells in mesh topologies. Directional couplers are widely used in these cells, often combined with phase-shifting mechanisms to enable tunability. However, conventional directional couplers in dense meshes typically require submicron gaps and tight etching tolerances, which increase sensitivity to fabrication variations and can introduce excess loss and variability. In addition, interconnected waveguides (e.g., S-bends and crossings) increase layout complexity, footprint, and bending-related penalties, while thermo-optic control may introduce power consumption and thermal crosstalk. Here, we propose a shallow-rib strip directional coupler in hydrogenated amorphous silicon (a-Si:H) for 1 µm × 1 µm multimode waveguides. The proposed geometry enables efficient coupling for waveguide separations ≥ 1 µm by shifting the coupling control from the lateral gap to the slab height, allowing smoother transitions and a relaxed fabrication flow. The analysis combines coupled-mode theory and beam propagation method simulations. As an application example, the layout of a 4 × 4 thermo-optically reconfigurable switching matrix is designed and simulated using 2 × 2 shallow-rib strip coupler cells. Full article

This paper presents a cover lens concept for camera modules based on surface acoustic waves (SAW) to mitigate the degradation of physical AI optical sensor field-of-view performance caused by surface contamination. The proposed approach utilizes a single-phase unidirectional transducer (SPUDT) that intentionally breaks left–right symmetry through a geometrically asymmetric electrode array to generate SAW, thereby removing droplet contamination. First, the acoustic streaming induced inside a single sessile droplet by the SAW was visualized, and the dynamic behavior of the droplet upon SAW actuation was observed using a high-speed camera. The internal flow developed into a recirculating vortex structure with directional deflection relative to the SAW propagation direction, indicating a symmetry-broken streaming pattern rather than a purely symmetric circulation. Upon the application of the SAW, the droplet was confirmed to move a total of 7.2 mm along the SAW propagation direction, accompanied by interfacial deformation and oscillation. Next, an analysis of transport trajectories for five sessile droplets dispensed at different y-coordinates ($y_1$–$y_5$) revealed that all droplets were transported along the x-axis regardless of their initial positions. Furthermore, the analysis of transport velocity as a function of droplet viscosity (1 $\mathrm{c}\mathrm{P}$ and 10 $\mathrm{c}\mathrm{P}$) and volume (2$\mathrm{\mu }\mathrm{L}$, 4$\mathrm{\mu }\mathrm{L}$, and 6 $\mathrm{\mu }\mathrm{L}$) demonstrated that the transport velocity gradually increased with driving voltage but decreased as viscosity increased under identical actuation conditions. Finally, the proposed cover lens was applied to an automotive front camera module to verify its effectiveness in improving object recognition performance by removing surface contamination. Based on its simple structure and driving principle, the proposed technology is deemed to be expandable as a surface contamination cleaning technology for various physical AI perception systems, including intelligent security cameras and drone camera lenses. Full article

Background and Objectives: Septic shock is marked by profound circulatory and cellular dysfunction, with mortality rates of 25–40% despite guideline-based resuscitation. Normalization of macrohemodynamic variables often fails to restore tissue perfusion, a concept known as hemodynamic incoherence. Persistent microcirculatory dysfunction is associated with organ failure and poor outcomes, underscoring the limitations of systemic monitoring alone. This focused narrative review synthesizes current evidence on microcirculatory monitoring in septic shock, with emphasis on bedside and emerging optical technologies, and evaluates their role as adjuncts to traditional hemodynamic assessment for perfusion-targeted resuscitation. Materials and Methods: A concept-driven search of PubMed/MEDLINE (January 2015 to January 2026) was performed, incorporating MeSH and free-text terms for septic shock, microcirculation, hemodynamic coherence, and monitoring modalities. Foundational pre-2015 studies were included for context. Articles were screened using predefined inclusion/exclusion criteria to minimize bias, with thematic qualitative synthesis. A PRISMA-inspired flow diagram was used to summarize the study selection process. Results: Microcirculatory alterations in septic shock include reduced functional capillary density, perfusion heterogeneity, and impaired oxygen extraction, persisting despite macrohemodynamic correction. Bedside markers, such as capillary refill time (CRT) and mottling, track microvascular recovery more closely than lactate. When used to guide resuscitation, CRT-based strategies show a non-significant mortality trend in randomized evaluation, with later studies reporting benefit in composite clinical outcomes. Optical technologies offer non-invasive insights: photoplethysmography (PPG) and perfusion index (PI) show prognostic value and early detection of incoherence; automated CRT (aCRT) enhances reproducibility; advanced modalities, such as laser speckle contrast imaging (LSCI), near-infrared spectroscopy (NIRS), and sublingual videomicroscopy, provide detailed physiological data but face standardization challenges. Recent interventional evidence, including peripheral perfusion-targeted RCTs, supports improved outcomes, though large-scale trials remain limited. Conclusions: Microcirculatory monitoring provides complementary, physiologically relevant information to macrohemodynamic assessment in septic shock. Emerging bedside tools, such as PI and aCRT, are poised for routine use, while multimodal integration may enable personalized management. Future research should prioritize standardization, AI-driven analysis, and randomized trials to confirm outcome benefits. Full article

Mechanical recycling of polyethylene terephthalate (PET) is a key strategy for circular packaging applications; however, repeated thermo-mechanical processing leads to progressive polymer degradation. In this study, the effect of controlled repeated extrusion on the degradation behavior of bottle-grade PET was systematically investigated under laboratory conditions. Mechanical recycling was simulated using a co-rotating twin-screw extruder, where PET was subjected to up to four consecutive processing cycles corresponding to a cumulative residence time of 8 min. Progressive processing resulted in chain scission, reflected by a decrease in intrinsic viscosity from approximately 0.80 to 0.65 dL·g⁻¹ and a corresponding reduction in molecular weight. Melt flow rate increased accordingly, indicating a gradual loss of melt strength. Differential scanning calorimetry revealed that the glass transition and melting temperatures remained nearly unchanged, while the degree of crystallinity increased from approximately 23.0% to 29.5%, accompanied by changes in crystallization behavior. These structural changes led to reduced ductility, with elongation at break decreasing from about 84% to 60%. Optical analysis showed systematic material darkening, and a strong linear correlation between lightness (L*) and intrinsic viscosity was observed. By isolating intrinsic thermo-mechanical degradation effects under controlled processing conditions, this study enables a clearer definition of realistic reuse limits for mechanically recycled bottle-grade PET. The results indicate that bottle-grade PET retains properties compatible with demanding applications only after a limited number of thermo-mechanical processing cycles, whereas further processing restricts its usability to less demanding applications such as fibers, films, and non-food packaging. Full article

Micro-expressions (MEs) are involuntary facial movements that reveal genuine emotions, holding significant value in fields like deception detection and psychological diagnosis. However, micro-expression recognition (MER) is fundamentally challenged by the entanglement of subtle emotional motions with identity-specific features. Traditional methods, such as those based on Robust Principal Component Analysis (RPCA), attempt to separate identity and motion components through fixed preprocessing and coarse decomposition. However, these methods can inadvertently remove subtle emotional cues and are disconnected from subsequent module training, limiting the discriminative power of features. Inspired by the Bruce–Young model of facial cognition, which suggests that facial identity and expression are processed via independent neural routes, we recognize the need for a more dynamic, learnable disentanglement paradigm for MER. We propose LFD-TCMEN, a novel network that introduces an end-to-end learnable feature disentanglement framework. The network is synergistically optimized by a multi-task objective unifying orthogonality, reconstruction, consistency, cycle, identity, and classification losses. Specifically, the Disentangle Representation Learning (DRL) module adaptively isolates pure motion patterns from subject-specific appearance, overcoming the limitations of static preprocessing, while the Temporal-Complemented Motion Enhancement (TCME) module integrates purified motion representations—highlighting subtle facial muscle activations—with optical flow dynamics to comprehensively model the spatiotemporal evolution of MEs. Extensive experiments on CAS(ME)³ and DFME benchmarks demonstrate that our method achieves state-of-the-art cross-subject performance, validating the efficacy of the proposed learnable disentanglement and synergistic optimization. Full article

3D printing offers great potential for rapid and cost-effective fabrication of microfluidic lab-on-a-chip systems. Through a comparative approach, we implemented staggered herringbone mixer (SHM), Tesla mixer, and split and recombine mixer (SAR), along with a basic unperturbed channel into one chip and performed comparative mixing efficiency experiments. We also introduced a phaseguide-based, T-shaped stop structure at the Y-shaped inlets for bubble-free and parallel filling. The structures were analyzed with two poorly mixable dye solutions at flow rates ranging from 1 µL/min to 200 µL/min. The mixing efficiency was evaluated using optical gray value analysis and compared against diffusion-based mixing. The fluid-aligning phaseguides in the 3D-printed system were shown to work. Among the three different mixing structures tested, SHM exhibited the best mixing efficiency at all tested flow rates. Uniformly designed SHM structures contain a region of poor mixing between the two zones of turbulence. In a non-uniform design, fluid breakers were placed between two SHM units to redirect poorly mixed fluids to the edges, resulting in 100% mixing efficiency across all measured flow rates. These results, especially SHM with fluid breakers, support the development of cost-effective injection-molded lab-on-a-chip systems with improved mixing functionalities at close range instead of simple long-length meandric systems. Full article

Techno-economic analysis (TEA) plays a vital role in assessing the feasibility and scalability of emerging technologies, especially in the context of innovation and development. Central to any effective TEA is a reliable and detailed model of capital and operational costs. This paper reports the development of such a model for optical networks in the framework of the SEASON project, aimed at supporting a broad spectrum of techno-economic evaluations. The model is constructed using publicly available data and expert insights from project participants. Its generalizable design allows it to be used both within the SEASON project and as a reference for other studies. By harmonizing assumptions and cost parameters, the model fosters consistency across different analyses. It includes cost and power consumption data for a wide range of commercially available optical network components (including transceivers for point-to-multipoint communications), introduces a statistical framework for estimating values for emerging technologies, and provides a cost model for multiband-doped fiber amplifiers. To demonstrate its practical relevance, the paper applies the model to two case studies: an evaluation of how the cost of various multiband node architectures scales with network traffic in meshed topologies and a comparison of different transport solutions to carry fronthaul flows in the radio access network. Full article

Tantalum pentoxide (Ta₂O₅) films deposited on fused silica substrates are critical components of high-power laser systems. Ion-assisted electron beam evaporation (IAD-EBE) is the mainstream technique for fabricating Ta₂O₅ films. However, it commonly requires extensive experimental efforts for deposition quality optimization, while each coating cycle is extremely time-consuming. To solve this issue, this work establishes a dataset targeting the surface roughness (Rq) and refractive index (n) of Ta₂O₅ films using atomic force microscopy, as well as ellipsometer and deposition experiments. Influence of assisting ion source beam voltage (V)/current (I) and Ar (Q₁)/O₂ (Q₂) flow rate on the n and Rq of Ta₂O₅ films are analyzed. Combining energy-field mechanism analysis with a Bayesian optimization approach (PI-BO), both deposition quality prediction and feature analysis of process parameters are achieved. The determination coefficient/mean absolute error for the prediction models of n and Rq reach 0.927/0.013 nm and 0.821/0.049 nm, respectively. Based on sensitivity analysis, the weight factors of V, I, Q₁, and Q₂ affecting n/Rq of Ta₂O₅ films are determined to be 0.616/0.274, 0.199/0.144, 0.113/0.582, and 0.072/0.000. V and Q₂ are identified as the core factors for regulating deposition quality. The optimal ranges for V and Q₂ are 600~700 V and 70~80 sccm, respectively. This study proposes a PI-BO method for predicting Rq and n of Ta₂O₅ films under small-data conditions, while determining the preferred parameter ranges and their sensitivity weight factors. These findings provide effective theoretical support and technical guidance for IAD-EBE strategy design and optimization of optical films in high-power laser systems. Full article

Accurate measurement of wall shear stress (WSS) is essential for both fundamental and applied fluid dynamics, where it governs boundary-layer behavior, drag generation, and the performance of flow-control systems. Yet, existing WSS sensing methods remain limited by low spatial resolution, complex instrumentation, or the need for user-dependent calibration. This work introduces a method based on artificial intelligence (AI) and Oil-Film Interferometry, referred to as AI-OFI, that transforms a classical optical technique into an automated and sensor-like platform for local WSS detection. The method combines the non-intrusive precision of Oil-Film Interferometry with modern deep-learning tools to achieve fast and fully autonomous data interpretation. Interference patterns generated by a thinning oil film are first segmented in real time using a YOLO-based object detection network and subsequently analyzed through a modified VGG16 regression model to estimate the local film thickness and the corresponding WSS. A smart interrogation-window selection algorithm, based on 2D Fourier analysis, ensures robust fringe detection under varying illumination and oil distribution conditions. The AI-OFI system was validated in the high-Reynolds-number Long Pipe Facility at the Centre for International Cooperation in Long Pipe Experiments (CICLoPE), showing excellent agreement with reference pressure-drop measurements and conventional OFI, with an average deviation below 5%. The proposed framework enables reliable, real-time, and operator-independent wall shear stress sensing, representing a significant step toward next-generation optical sensors for aerodynamic and industrial flow applications. Full article

To address the impact of environmental and equipment factors on signal identification in highway tunnel drainage pipeline blockage monitoring, this study aims to elucidate the influence patterns of pipeline flow rate, optical fiber deployment scheme, and fiber performance on blockage-induced acoustic signals. A full-scale concrete pipeline experimental platform was established. Data were acquired using a HIFI-DAS V2 sensing system. The time–frequency domain characteristics of acoustic signals under different flow rates (50 m³/h and 100 m³/h), fiber deployment schemes (inside the pipe, outside the pipe, and outside a soundproofing layer), and fiber materials (six typical types) were analyzed and compared. The degree of influence of each factor on signal amplitude and dominant frequency components was quantified. The experimental results indicate that: Compared to a flow rate of 50 m³/h, the amplitude characteristic value at the blockage channel exhibited a marked increase at 100 m³/h, accompanied by an increase in the number and amplitude of dominant frequency components. While the dominant frequency components of the acoustic signals were less stable across the three deployment schemes, the overall amplitude at the blockage channel was consistently higher than that at non-blockage channels. When the fiber was deployed farther from the fluid core (outside the soundproofing layer), the dominant frequencies essentially disappeared, with energy distributed in a broadband form. The peak amplitude and array energy of the sensitive vibration sensing fiber were 2 times and 3.6 times those of the worst-performing type, respectively. Furthermore, its physical properties are better suited to the tunnel environment, effectively enhancing signal acquisition stability and the signal-to-noise ratio. Comprehensive analysis demonstrates that deploying sensitive fibers inside the pipe is more conducive to the accurate identification of blockage events. Moreover, uniform dominant frequency components and threshold criteria are not recommended along the entire length of the drainage pipe. This research provides theoretical and experimental support for parameter optimization of DAS systems to achieve high-precision pipeline blockage monitoring in complex tunnel environments. Full article

Accurately assessing collapse risks of high-elevation, concealed rock mass blocks within the steep cliffs of Bijiashan, Three Gorges Reservoir Area, is challenging. This study employed a multidimensional approach—integrating airborne Light Detection and Ranging (LiDAR), the transient electromagnetic method (TEM), close-range photogrammetry, horizontal drilling, and borehole optical imaging—to characterize the rock mass structure of the WD1 cliff belt and delineate 52 individual blocks. Stability analysis incorporated stereographic projection for macro-scale assessment and employed mechanical models specific to three primary failure modes (toppling, sliding, falling). Finite element strength reduction quantified the stress–strain response of a representative block under natural and rainstorm conditions. Particle Flow Code (PFC) simulated dynamic instability of the exceptionally large block W1-37. Results indicate the WD1 rock mass is highly fractured, with base sections prone to weakness. Toppling failure dominates (90.4%). Under rainstorm conditions, the average Factor of Safety (FOS) decreased by 14.7%, and 73.1% of the blocks that were stable under natural conditions were destabilized—specifically transitioning to marginally stable or substable states—often triggering chain-reaction instability characterized by “crack propagation—base buckling”. W1-37 exhibited staged failure under rainstorm: “strain localization at fissure tips—penetration of basal cracks—overturning of the upper rock mass”. Its frontal rock reached a peak sliding velocity of 15.17 m/s, indicative of base-breaking toppling. The integrated “multi-technology survey—multi-method evaluation—multi-scale simulation” framework provides a quantitative basis for risk assessment of rock mass disasters in the Three Gorges Reservoir Area and offers a technical paradigm for similar high-steep canyon regions. Full article

Maintaining color constancy in polymer extrusion processes is a key difficulty in manufacturing applications, as fluctuations in processing parameters greatly influence pigment dispersion and the quality of the finished product. Preliminary historical data mining analysis was conducted in 2009. This work concentrates on Opaque PC Grade 5, which constituted 2.43% of the pigment; it contained 10 PPH of resin2 with a Melt Flow Index (MFI) of 6.5 g/10 min and 90 PPH of resin1. It also employs a fixed resin composition with an MFI of 25 g/10 min. This research identified the significant processing parameters (PPs) contributing to the lowest color deviation. Interactions between processing parameters, for the same color formulation, were analyzed using statistical methods under various processing conditions. A principle-driven General Trends (GT) diagnostic procedure was applied, wherein each parameter was individually varied across five levels while holding others constant. Particle size distribution (PSD) and colorimetric data (CIE Lab*) were systematically measured and analyzed. To complete this, correlations for the impact of temperature (Temp) on viscosity, particle characteristics, and color quality were studied by characterizing viscosity, Digital Optical Microscopy (DOM), and particle size distribution at various speeds. The samples were characterized for viscosity at three temperatures (230, 255, 280 °C) and particle size distribution at three speeds: 700, 750, 800 rpm. This study investigates particle processing features, such as screw speed and pigment size distribution. The average pigment diameter and the fraction of small particles were influenced by the speed of 700–775 rpm. At 700 rpm, the mean particle size was 2.4 µm, with 61.3% constituting particle numbers. The mean particle size diminished to 2 µm at 775 rpm; however, the particle count proportion escalated to 66% at 800 rpm. This research ultimately quantifies the relative influence of particle size on the reaction, resulting in a color value of 1.36. The mean particle size and particle counts are positively correlated; thus, reduced pigment size at increased speed influences color response and quality. The weighted contributions of the particles, 51.4% at 700 rpm and 48.6% at 800 rpm, substantiate the hypothesis. Further studies will broaden the GT analysis to encompass multi-parameter interactions through design experiments and will test the diagnostic assessment procedure across various polymer grades and colorants to create robust models of prediction for industrial growth. The global quality of mixing polycarbonate compounding constituents ensured consistent and smooth pigment dispersion, minimizing color streaks and resulting in a significant improvement in color matching for opaque grades. Full article

Background: KMT2A partial tandem duplication (PTD) occurs in approximately 5–10% of acute myeloid leukemia (AML) cases and is associated with poor prognosis. While its cytogenetic and molecular features are well described, the immunophenotypic characteristics of AML with KMT2A-PTD remain incompletely defined. Methods: We identified 47 cases of AML with KMT2A-PTD by optical genome mapping. All cases underwent flow cytometric immunophenotypic analysis and next-generation sequencing using an 81-gene panel. Results: The cohort included 32 men and 15 women with a median age of 67 years (range, 19–87). Thirty-eight cases were de novo AML, and nine were secondary to myelodysplastic syndrome and/or myeloproliferative neoplasm. Most cases (93%) demonstrated a normal or non-complex karyotype. The most frequent mutations involved FLT3-ITD (47%), DNMT3A (43%), and RUNX1 (23%). Thirty-one cases (66%) were granulocytic, while 16 (34%) showed granulocytic and/or monocytic differentiation. Blasts uniformly expressed HLA-DR and frequently expressed CD117 (91%) and CD34 (79%). Increased expression of CD123 (74%) and CD117 (43%) and decreased expression of HLA-DR (74%) and CD38 (69%) were common. Aberrant CD25 expression was observed in 51% of cases. Increased CD123 and aberrant CD25 expression were significantly associated with FLT3-ITD mutations (both p < 0.0001) but not with other recurrent mutations. There was no correlation between FLT3-ITD mutation and expression levels of CD117, CD38 or HLA-DR (all p > 0.05). Conclusions: AML with KMT2A-PTD shows distinctive immunophenotypic features with increased CD123 and aberrant CD25 expression, both associated with FLT3-ITD. These markers may have diagnostic and therapeutic relevance in this AML subtype. Full article