Search Results (1,203)

There is an increasing demand for ultrasound imaging technologies, particularly wearable and portable systems, for continuous physiological monitoring applications. Although some recent flexible ultrasound devices have adopted polymer encapsulations, typical rigid transducer designs still include metal housings and costly electrodes, contributing to increased device weight and fabrication cost. To address these limitations, we developed an aluminum-electrode/3D-printed polymer-housing ultrasound transducer (APUT) utilizing a polyvinylidene fluoride piezoelectric film. Compared to a gold-electrode/metal-housing ultrasound transducer, the APUT material costs and total weight were approximately 66% and 86% lower, respectively. Acoustic evaluation revealed a center frequency of 24.5 MHz and a fractional bandwidth of 60.9%, with axial and lateral resolutions of 51 and 152 μm, respectively. Furthermore, during a 3-h pulsed operation test, the APUT exhibited an initial increase in capacitance followed by a relatively stable response, with no progressive surface-temperature increase detected within the accuracy of the measurement method. Finally, successful ex vivo imaging of chicken breast tissue confirms the APUT’s biomedical applicability, highlighting its potential as a wearable, portable, and disposable ultrasound platform. Full article

This study proposes a safety-enhanced path planning system that integrates a Control Barrier Function (CBF)-based Safety Shield with Deep Reinforcement Learning (DRL). This framework addresses the critical limitations of conventional DRL-based Unmanned Surface Vehicle (USV) navigation models, which can output hazardous control commands in edge cases and violate the International Regulations for Preventing Collisions at Sea (COLREGs). The proposed system continuously operates during navigation via an Encounter Classifier that identifies multi-vessel situations (such as Head-on, Crossing, and Overtaking) in real time. The nominal control inputs generated by the DRL policy are verified and safely filtered through a Control Barrier Function-Quadratic Programming (CBF-QP) optimization layer immediately prior to execution, incorporating ship safety radii and asymmetric COLREGs constraints. Furthermore, we introduce a ‘Shielded Training’ mechanism that penalizes the agent based on the magnitude of the shield’s interventions during the training loop. This effectively diminishes the policy’s over-reliance on the safety filter and guides the network toward discovering robust, inherently safe trajectories. Extensive simulations conducted under diverse single- and multi-vessel encounter scenarios quantitatively demonstrate that the proposed method substantially reduces collision and COLREGs violation rates compared to baseline DRL-only or reward-shaping methods, while maintaining excellent computational scalability and real-time responsiveness. Consequently, by unifying the adaptive environmental exploration of reinforcement learning with model-based runtime safety constraints derived from control theory, this study provides a practical runtime assurance framework for future marine deployment. Full article

A post-flight analysis of unmanned aerial vehicle (UAV) imagery has the potential to result in a delay in the inspection of source water. This delay can occur when visible debris or changes in the water surface necessitate a prompt response. The present study does not evaluate in-flight operation; rather, it presents a bench-level feasibility assessment of two deployment tasks—broad two-class screening and close-range debris classification—using lightweight YOLO detectors on an edge-AI camera in a host-fed configuration that approximates the timing constraints of a future UAV workflow. The YOLOv8, YOLO11, and YOLO26 models were lightweighted through structural pruning (YOLOv8) or architecture scaling (YOLO11 and YOLO26). These models were then refined through a process of fine-tuning, exported to the camera, and evaluated in terms of several metrics. The metrics encompassed training-environment accuracy, the accuracy of device-returned outputs, round-trip latency, and snapshot-based operating-load estimates. The dataset under consideration is extensive, comprising 4813 training images and 575 validation images, accompanied by 13,051 and 1615 annotations, respectively. The depth-pruned YOLOv8s variant demonstrated a significant reduction in mean round-trip latency, from 426.87 milliseconds to 231.58 milliseconds (45.75%), while the mAP@0.5 metric exhibited a decrease from 0.7018 to 0.6650, and the mAP@0.5:0.95 metric demonstrated a decline from 0.5433 to 0.5290. A class-level analysis reveals that aggregate accuracy is primarily influenced by the weaker floating-debris class, whose AP@0.5 ranges from 0.29 to 0.46, in contrast to the 0.82 to 0.94 range observed for pond/reservoir. In comparison to a matched baseline that was trained for an equivalent number of epochs with the sampler disabled, debris-biased sampling contributes 1.5 ± 0.6 mAP@0.5 points for YOLO11 and 3.6 ± 0.2 points for YOLO26 across three seed-matched pairs. The primary effect of this method is to increase floating-debris recall by 4.7–5.9 percentage points, with a concomitant small reduction in precision. The latency reduction increased the broad-inspection rate by 1.85×, provided approximately 195 milliseconds of idle margin within a 1-hertz cycle, and increased the paired far/near rate by 1.59× with two models resident on the camera. Three-seed repetitions of compact-model fine-tuning yielded 0.6717 ± 0.0033 and 0.6290 ± 0.0028 mAP@0.5. These results express detector compression in terms of operational monitoring capacity rather than model-size reduction alone, while also showing that compression by itself does not resolve the weak-class limitation that governs source-water inspection accuracy. Full article

Background: Ovarian cancer is the most lethal gynecologic malignancy, and CA-125 has limited early-stage sensitivity. We developed and evaluated Foretell Ovary, an ensemble machine-learning classifier that integrates tumor-educated-platelet RNA markers and routine hematologic parameters for non-invasive ovarian cancer detection, and compared it head-to-head with CA-125. Methods: A multi-site prospective cohort study enrolled 460 South Korean participants (67 ovarian cancer, 15 borderline ovarian tumors, 197 benign gynecological conditions, and 181 asymptomatic controls) at six clinical sites between September 2024 and March 2026. The cohort was split into training (n = 279) and independent test (n = 181) sets under a pre-specified ACTB cycle threshold ≤ 28 per-protocol rule (test n = 169). The classifier blended a random forest and two calibrated logistic-regression sub-models built on eight platelet RNA markers, 24 complete blood count parameters, and 30 marker-by-hematology combination features. Performance was assessed at a pre-frozen cutoff of 0.44 and compared against CA-125 (35 U/mL cutoff) in a matched subset (n = 100). Results: Foretell Ovary achieved an area under the receiver operating characteristic curve (AUC) of 0.923, sensitivity of 87.5% (100.0% for Stage II–IV), specificity of 89.0%, and negative predictive value of 97.7% in the test set. In the matched subset, Foretell Ovary outperformed CA-125 on every metric (AUC 0.839 vs. 0.723; sensitivity 85.0% vs. 65.0%), with the largest gap in pre-menopausal participants (+25 percentage points in sensitivity). A three-tier risk-grading scheme retained no ovarian cancer in the low-risk grade. Conclusions: Foretell Ovary offers more accurate non-invasive detection of ovarian cancer than CA-125, particularly in pre-menopausal women, offering the flexibility to be used alone or combined with CA-125. Prospective validation studies are warranted. Full article

Serial femtosecond crystallography (SFX) using X-ray free-electron lasers (XFELs) enables the determination of macromolecular and chemical structures along with minimizing radiation damage. Sample delivery using the fixed-target (FT) scanning method minimizes both sample consumption and physical damage during delivery. When XFELs penetrate the FT sample holder, background scattering generated from the holder material can interfere with data processing, which consequently indicates the importance of selecting an appropriate FT sample holder material according to specific experimental conditions. We introduce a polyethylene terephthalate (PET) film-based sample holder that can be applied to data collection for both small-molecule and macromolecule XFEL diffraction studies. Background scattering analysis revealed that the PET film-based sample holder produced relatively low X-ray scattering in the high-resolution range (<10 Å) compared with a nylon mesh-based sample holder composed of polyimide and nylon mesh. Conversely, background scattering generated from the PET film was relatively higher in the low-resolution range (>10 Å) than that with the polyimide film; however, this low-resolution background was negligible for data processing. Thin PET films were manually perforated to promote the deposition of microcrystals in random orientations. The crystal samples were then deposited onto the films and sealed with an additional PET film to prevent dehydration. Using the PET film-based sample holder, we successfully collected diffraction data from barium titanate without unwanted background scattering from the sample holder. Furthermore, the room-temperature structure of glucose isomerase was determined using the PET film-based sample holder. Therefore, PET film-based sample holders can be applied to both small-molecule and macromolecular SFX data collection. Full article

The urgent need for bio-based functional materials has driven a shift away from fossil-fuel-sourced materials toward renewable lignocellulosic biomass (LCB). This comprehensive review explores the advancements in LCB carbonization between 2020 and 2026, marking a shift from traditional, low-yield combustion processes toward highly selective and sustainable thermochemical conversion pathways. The primary objective of this review is to evaluate the integration of green pretreatment strategies, conversion technologies, and efficient valorization of the aqueous effluents and by-products. The goal of green pretreatment is to overcome the inherent recalcitrance of LCB without the use of harsh chemicals and reaction conditions, specifically highlighting the effectiveness of deep eutectic solvents (DESs) and ionic liquids (ILs). The review also evaluates the emerging conversion technologies, including hydrothermal carbonization (HTC), microwave-assisted pyrolysis (MAP), and the synergistic co-pyrolysis of LCB with synthetic polymeric wastes. Another novel concept in preparing hard carbon and other related materials is the “lignin-first” biorefinery strategy, which facilitates the subsequent production of high-value aromatic monomers, platform chemicals, and biofuels. The engineered carbon materials are increasingly utilized well beyond their traditional use as solid fuels. The products have been proven to be excellent for use in high-performance energy conversion and storage, serving as renewable bio-based electrode materials for supercapacitors and carbon electrodes in next-generation batteries. Full article

Rochia nilotica is an economically important marine gastropod in Pacific Island countries, valued for its nacreous shell used in ornaments. The brown macroalga Sargassum horneri accumulates in large quantities along coastal regions, causing significant ecological and economic burdens. We evaluated the effects of S. horneri-based feed on the growth performance of juvenile R. nilotica under controlled tank conditions in Chuuk Lagoon, Micronesia. Juveniles (initial shell width ≈ 12.7 mm) were reared for 120 days and fed either a formulated diet (disc-shaped pellets, <1 cm in diameter) containing S. horneri or a traditional live-rock diet providing natural biofilms. Notable biological differences in shell width and height were observed after 2 months, with final mean values of 19.86 ± 1.76 mm and 15.92 ± 1.25 mm in the S. horneri group (94% survival), compared with 16.40 ± 1.26 mm and 13.14 ± 0.96 mm in the natural diet group (86% survival). Although greater growth and survival were observed in the tank receiving the formulated diet, fully replicated multi-tank experiments are required to definitively confirm whether these differences were caused directly by the dietary treatment. Given its abundance and environmental impact, recycling S. horneri biomass as a sustainable feed source could support trochid aquaculture and resource restoration and contribute to circular bioeconomy practices in Pacific Island countries. Full article

Although airway organoids provide a physiologically relevant platform for modeling human airway inflammation, their utility is often limited by substantial heterogeneity in epithelial differentiation and functional responsiveness across Matrigel domes. Here, we present a non-destructive, imaging-guided framework to predict epithelial cytokine responses and enable the selection of functionally consistent airway organoid domes. Mature human airway organoids were stimulated with house dust mite (HDM) extract and dome-level inflammatory responsiveness was quantified by RT-qPCR for thymic stromal lymphopoietin (TSLP) and interleukin-33 (IL-33). Both cytokines exhibited wide dome-to-dome variability and showed a significant positive correlation, indicating coordinated allergic inflammatory regulation. Meanwhile, bright-field dome images were analyzed to segment individual organoids, define robust regions of interest, and extract quantitative morphological and texture descriptors based on gray-level co-occurrence matrix features. Organoid-level descriptors were aggregated into a single dome-level feature vector using distributional statistics, thereby capturing both central tendency and heterogeneity within each dome. Using these engineered dome-level features, we trained a deep tabular learning model (TabNet) to classify qPCR-defined inflammatory responsiveness. The resulting model achieved strong and consistent cross-validated performance for both targets, reaching balanced accuracies of 0.910 for TSLP and 0.833 for IL-33, demonstrating that bright-field phenotypes contain predictive signatures of cytokine activation. This approach provides a scalable enrichment strategy for robustly responsive organoid–Matrigel domes without destructive assay. It improves reproducibility in organoid-based airway inflammation studies and supports standardized dome selection for downstream mechanistic and translational applications. Full article

Melt-pool depth governs interlayer bonding and porosity in laser powder bed fusion and underpins part qualification, yet predicting it reliably remains difficult. Fast conduction models reach useful accuracy only after the absorptivity is fitted to the depths they are meant to predict, and inverse analyses have been used the same way, to recover a calibrated parameter rather than to test the model. Here, the absorptivity is fixed independently instead, a measured coupling for IN718 and, for IN625 and 316L, a published closed-form relation never fitted to the present depths. This converts a moving-source conduction model from an object of calibration into one of validation. The melt boundary is located by root-finding rather than on a grid, so no discretization error enters the diagnosis. Across 231 single tracks, the model reproduces conduction-regime depth and half-width to within a few percent and underpredicts increasingly once keyholing begins. Inverting each measured depth for the absorptivity conduction would require yielding a fitting-free diagnosis: no conduction-regime track demands a non-physical value, and the inferred value converges near 0.38 against inputs of 0.27 to 0.34, whereas every keyhole-classified track demands a value above unity. Because an inferred absorptivity also absorbs unmodeled transport, downward convection was emulated as an anisotropic effective diffusivity; at the enhancement reported for Marangoni flow, no keyhole track becomes explicable. A measured Ti-6Al-4V absorptivity rise of a factor 1.9 supports the mechanism. An enthalpy-indexed correction and data-driven baselines remain alloy-specific, whereas the physics-based model retains its advantage under cross-alloy extrapolation. All findings are for single tracks on bare plates. Full article

Generative artificial intelligence (AI) has diffused rapidly, yet adoption has not reliably progressed to AI transformation (AX). Firms grant tool access but fail to redesign workflows, clarify accountability, govern risks, or measure value. The gap is a socio-technical systems problem, not a productivity problem: AI tools are inserted into existing routines without redesigning task interdependencies, decision rights, oversight loops, or performance feedback. This paper develops AX-5R, a socio-technical systems architecture that converts fragmented AI use into accountable, governable, and measurable work systems. Synthesizing seven literature streams, it maps failure modes to five interdependent design functions: readiness, redesign, role, risk, and return. AX-5R treats transformation as joint optimization of technical and social subsystems requiring configurational alignment. A supplementary ablation probe generated 252 artifacts across three workflows and seven prompt arms from two language models, scored by blinded cross-provider judges; the full frame outscored a sham five-part control and its four artifact-relevant ablations, significant under two-sided Holm-corrected testing, with an independent human-expert-rating check. With a failure-mode derivation matrix, implementation artifacts, and six testable propositions, the framework specifies a minimum architecture in which readiness sets boundaries, redesign restructures tasks, role assigns accountability, risk establishes control, and return supplies learning feedback. Full article

Subcooled flow boiling experiments were conducted to investigate the effect of multi-swirl inserts on heat transfer, critical heat flux, and pressure drop under one-sided high-heat-flux heating conditions. Water was used as the working fluid, and four cooling-channel configurations were tested: a smooth circular tube, a single-swirl insert, a two-element multi-swirl insert, and a four-element multi-swirl insert. The experiments were performed under controlled pressure, inlet temperature, and flow velocity, while the heat flux was increased stepwise until the critical heat flux (CHF) occurred. The boiling curves showed that the multi-swirl inserts reduced the wall superheat compared with the smooth tube and the single-swirl insert. The maximum heat transfer coefficient increased from 61.2 kW/m² K for the smooth tube to 66.8, 115, and 154 kW/m² K for the single-swirl, two-element multi-swirl, and four-element multi-swirl inserts, corresponding to enhancements of 9.2%, 87.9%, and 151.6%, respectively. The CHF also increased from 3927 kW/m² for the smooth tube to 5086, 6086, and 7472 kW/m² for the corresponding insert configurations, corresponding to CHF enhancements of 29.4%, 55.0%, and 90.3%, respectively. The results show that multi-swirl inserts enhance subcooled flow boiling heat transfer and increase CHF under one-sided high-heat-flux heating conditions. A performance evaluation criterion (PEC) analysis further indicated that the hydraulic penalty should be considered when selecting the insert configuration for a target heat-flux range. Full article

High-entropy alloys (HEAs) offer attractive combinations of mechanical performance, thermal stability, and compositional flexibility, making them promising candidates for advanced structural applications. Laser-based additive manufacturing, particularly laser powder bed fusion (LPBF) and laser-directed energy deposition (LDED), enables the fabrication of geometrically complex HEA components with non-equilibrium microstructures. However, the distinct thermal histories of LPBF and LDED, with typical cooling rates of approximately 10⁵–10⁷ K s⁻¹ and 10²–10⁴ K s⁻¹, respectively, strongly govern solidification behavior, elemental segregation, residual stress development, defect formation, and mechanical properties. Although previous reviews have discussed additively manufactured HEAs, an integrated framework linking composition design, printability, LPBF/LDED processing, microstructural evolution, post-processing, and industrial qualification remains limited. Therefore, this review establishes a unified composition–process–structure–property framework for laser additively manufactured HEAs. Fundamental HEA concepts, LPBF/LDED process characteristics, solidification behavior, phase formation, defect evolution, and mechanical performance from ambient to elevated temperatures are systematically discussed across representative FCC, refractory, and dual-phase HEA systems. This review emphasizes that printability should be considered during alloy design by correlating composition-dependent solidification characteristics, cracking susceptibility, phase stability, and defect formation with mechanical performance. Post-processing treatments are shown to modify residual stress, microsegregation, precipitation behavior, porosity, and deformation mechanisms, although their benefits must be balanced against thermal softening or brittle phase formation. Finally, CALPHAD, integrated computational materials engineering (ICME), machine learning (ML), and in situ monitoring are identified as promising tools for accelerating alloy and process optimization, while reproducible process windows, defect-control criteria, databases, and qualification protocols remain essential for industrial implementation. Full article

This study reports the growth and structural analysis of β-Ga₂O₃ films on 4° off-axis (000±1) Si- and C-face 4H-SiC substrates by plasma-assisted molecular-beam epitaxy (PAMBE). Pre-growth treatments of 4H-SiC substrates were conducted by employing: (I) unintentional oxygen exposure, (II) intentional Ga pre-exposure, (III) a Ga flash-off process followed by Ga pre-exposure, and (IV) intentional oxygen-plasma pre-exposure prior to β-Ga₂O₃ growth, which led to different growth behaviors. The intentional Ga pre-exposure and Ga flash-off followed by Ga pre-exposure treatments modified the initial Si-face surface condition and were consistent with the mitigation of oxygen-induced surface degradation, including possible SiO_x-related effects. In contrast, unintentional oxygen exposure and intentional oxygen-plasma pre-exposure produced RHEED evolution consistent with substantial surface disordering and possible amorphous SiO_x formation on the Si-face 4H-SiC substrate, leading to disordered nucleation and degraded film growth. Growth on the C-face 4H-SiC substrate resulted in more ordered β-Ga₂O₃ films, suggesting that the C-face surface is less susceptible to SiO_x-related degradation under the present oxygen-containing growth environment. The combined in situ RHEED, AFM, and HRXRD results indicate that substrate polarity and pre-growth surface treatments strongly influence the initial nucleation, morphology, and crystalline quality of β-Ga₂O₃ films on 4H-SiC. These findings provide a useful strategy for controlling oxide film growth on easily oxidized substrates under oxygen environments. Full article

The growing demand for sustainable construction materials has sparked interest in innovative cementitious components that improve performance while mitigating environmental impact. This study explores the influence of red phosphorus (P) on the crystallization dynamics and electrochemical stability of Portland cement. Specifically, we investigate how varying phosphorus concentrations (0–10%) affect phase evolution and structural integrity. A comprehensive suite of analytical techniques, including field emission scanning electron microscopy (FE-SEM), energy-dispersive spectroscopy (EDS), electron probe microanalysis (EPMA), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS), was employed to characterize crystallization behavior. Additionally, open circuit potential (OCP), potentiodynamic polarization tests, and electrochemical impedance spectroscopy (EIS) were utilized to evaluate electrochemical properties. Quantitative defect analysis showed that the number of pores increased from 150 ± 22 to 420 ± 22 ea/mm², the crack width increased from 0.10 ± 0.01 to 1.40 ± 0.60 μm, and the crack length increased from 1.20 ± 0.20 to 4.20 ± 1.21 μm. In addition, OCP shifted from −0.16 ± 0.01 to −0.27 ± 0.03 V, I_corr increased from 2 × 10⁻⁷ ± 1 × 10⁻⁸ to 8 × 10⁻⁷ ± 3 × 10⁻⁸ A/cm², and R_p decreased from 10.5 ± 0.4 to 6.0 ± 0.2 kΩ with increasing P composition, indicating deterioration of the microstructural and electrochemical stability of the cement matrix. These findings provide quantitative guidance for controlling phosphorus utilization in cement formulations. Full article

Regional sea-level trends derived from satellite altimetry deviate substantially from the global mean, but the relative roles of externally forced change and internally generated climate variability remain difficult to separate from the short satellite record. Here, we examine the 32-year Data Unification and Altimeter Combination System (DUACS) gridded multi-mission satellite altimetry product (January 1993–December 2024) together with 100 100-year samples from an unforced Community Earth System Model (CESM) pre-industrial control simulation. Empirical orthogonal function (EOF) analysis of satellite sea-level anomalies reveals a leading mode explaining 10.9% of total variance, with an Interdecadal Pacific Oscillation (IPO)-like dipolar pattern and high correlation with the IPO index (r = 0.92). A similar IPO-like mode appears consistently in the unforced CESM samples. Because previous large-ensemble studies indicate that the externally forced sea-level response is generally broader and structurally distinct from this dipolar internal mode, this agreement supports the interpretation that the satellite-observed leading pattern is strongly consistent with internally generated variability, although a partial forced contribution, particularly in the tropical Pacific, cannot be excluded. Based on CESM simulations, the empirical contribution of internal variability to regional trend uncertainty decreases approximately inversely with record length. The resulting location-specific estimate can be scaled by the local EOF amplitude and is largest in regions where the dominant internal-variability mode has large amplitudes, including the western tropical Pacific and Indian Ocean. However, this estimate represents only the internally generated component inferred from a single unforced CESM simulation. It does not include DUACS mapping errors, inter-mission calibration uncertainty, geophysical correction uncertainty, glacial-isostatic-adjustment-related bias, or uncertainty in the forced sea-level response. Thus, this study provides a model-based framework for estimating the internal-variability contribution to regional sea-level trend uncertainty, rather than a formal detection-and-attribution separation or a complete uncertainty bound for satellite-altimeter-derived regional sea-level trends. Full article