Search Results (427)

Nme1Cas9 is an encouraging genome-editing tool with high fidelity and compactness, but its applications are limited by poor catalytic efficiency compared with SpyCas9. Understanding the dynamic activation mechanism of the HNH nuclease domain is the key to breaking the kinetic bottleneck. Here, we integrated Steered Molecular Dynamics (SMD) with the Traveling-Salesman-based automated Path Searching (TAPS) algorithm to reconstruct the atomic-level activation landscape of the L1-HNH module. The simulations suggest a complex “Lifting-Rearrangement-Sliding” pathway, revealing the critical role of a “Backbone Sliding” conformation; in this step, the HNH domain rotates across the R-loop surface. A thermodynamic analysis using free energy decomposition by MM/PBSA indicates that the intrinsic instability of the wild-type HNH/R-loop interface constitutes the predominant energetic barrier. Hyperactive variants (S593Q/W596K and S593Q/W596R) can overcome this barrier by substantially increasing binding affinity to the R-loop through a “Geometry–Electrostatics Synergism”: S593Q improves interfacial proximity, whereas W596K/R acts as an “Electrostatic Anchor.” The results of unbiased MD simulations demonstrate that strengthened interfacial interactions effectively promote spontaneous conformational drift toward the activated state. This computational study proposes a novel in silico model for “Dynamic Interface Engineering” in which reinforcing transient interfacial contacts during conformational sliding can be an effective strategy in developing high-efficiency CRISPR-Cas effectors. Full article

Electromagnetic imaging in a slab medium presents significant challenges due to complex wave reflections and refractions at the interfaces of different layers. Multiple scattering and interference increase ill-posedness and nonlinearity, degrading reconstruction accuracy and stability. Under transverse magnetic (TM) and transverse electric (TE) excitations, we compare the CNN-refined reconstructions based on the Back Propagation Scheme (BPS) and the Dominant Current Scheme (DCS) to solve the Electromagnetic Inverse Scattering (EMIS) problem. Numerical results demonstrate that our proposed method can accurately reconstruct buried objects of various sizes and positions, even in the presence of noise. In particular, the DCS-CNN framework yields superior reconstruction performance compared to the BPS-CNN approach, highlighting the advantage of integrating the DCS with DL for imaging in a slab medium. Overall, this work validates the feasibility and effectiveness of combining preliminary imaging with DL, offering practical potential for solving complex inverse scattering problems. Full article

Fixed-step real-time electromagnetic-transient (EMT) simulation of large power networks typically relies on parallel partitioning, where transmission-line elements serve as step-synchronous decoupling boundaries between subsystems. In distribution and subtransmission studies, however, many line sections are electrically short and have propagation delays smaller than the simulation step. Classical Bergeron models then lose their pure one-step delay structure and require interpolation or sub-stepping, which undermines step determinism and limits the availability of decoupling boundaries, thereby constraining partition quality and scalability. This paper proposes an interpolation-free hybrid Bergeron–π boundary-line model with zero-sequence impedance modification (HB-π-ZIM). A one-step uncoupled per-phase Bergeron section enforces a delay equal to the simulation step to provide a strictly step-synchronous interface. Shunt compensation removes the artificial shunt susceptance introduced by the enforced delay, and a passive RL two-port synthesis reconstructs the residual series impedance so that, at the fundamental frequency, the terminal positive- and zero-sequence series impedances and shunt admittances match the conventional lumped-pi model. Case studies show close agreement with the lumped-pi benchmark under representative balanced and unbalanced transients, while parallel tests on a 327-node network demonstrate near-linear speedup (9.31 times on 10 cores) when HB-π-ZIM is applied only to cut-set lines. The proposed model therefore enlarges the feasible set of decoupling boundaries in short-line-dominated networks and enables scalable fixed-step real-time EMT simulation. Full article

Multiple-Input–Multiple-Output Ground-Penetrating Radar (MIMO-GPR), collecting multiview–multistatic data, is now becoming an assessed diagnostic tool, enabling enhanced reconstruction accuracy and subsurface target detection due to the exploitation of multiple Tx/Rx channels. In this context, the present work deals with a 2D radar imaging approach for contactless MIMO GPR based on the equivalent permittivity concept. The imaging problem is formulated as a linearized inverse scattering problem under Born approximation, and a ray propagation model, based on equivalent permittivity spatially varying along depth, is adopted to account for the wave propagation through the air–soil interface. The resulting linear inverse problem is solved by means of an adjoint inversion, enabling reliable target reconstruction. Despite the approximation introduced by the present formulation, numerical simulations show that the proposed imaging strategy is sufficiently accurate from an engineering viewpoint and is computationally efficient. Full article

Agrivoltaics offer a sustainable solution to the growing competition between food and energy production. However, their adoption is often constrained by the design and operation challenges associated with optimising the complex trade-off between crop yield and photovoltaic (PV) output. Digital twins can mitigate these risks, yet most agricultural digital twins operate as fragmented digital shadows, lacking high-fidelity modelling, advanced simulation, and bidirectional control capabilities. This study presents a comprehensive, end-to-end digital twin framework to address these limitations. The framework integrates a high-resolution 3D orchard model, reconstructed via UAV photogrammetry, with a CesiumJS-based web interface linked to a modular IoT architecture built on Node-RED, Message Queuing Telemetry Transport (MQTT) protocol and InfluxDB for real-time monitoring and control. A PV simulation engine supports the design, simulation and optimisation of agrivoltaic systems. Bidirectional communication was validated through remote actuation of a physical solar tracker, demonstrating integration among the 3D environment, sensor data and control systems to achieve a closed-loop digital twin. Simulation analyses suggested that panel orientation and row spacing exert a dominant influence on crop-level light distribution. Simulation results demonstrated that a 90° azimuth configuration achieved the highest daily energy yield of 53.97 kWh but reduced peak crop-level irradiance to 205 W/m². In contrast, the baseline 0° configuration offered a balanced output of 40.86 kWh with a peak light availability of 338 W/m². The validated, interoperable digital twin architecture provides a reference model for the design, simulation, monitoring and control of an agrivoltaic system, reducing investment uncertainty and supporting sustainable food–energy co-production. Full article

Background and Objectives: The pathways mediating the beneficial effect of tibial stump preservation for anterior cruciate ligament (ACL) reconstruction remain insufficiently clarified. This study investigated key vascular, neural, and stromal aspects of cellular remodeling processes occurring across lesion stages in tibial remnant pre-reconstruction. Materials and Methods: Biopsies were obtained from 25 patients undergoing arthroscopic ACL reconstruction (paired free-end and tibial insertion sampling) and 10 from quasi-normal, macroscopically intact ligaments (controls). We evaluated intergroup differences in microvascular density using a t-test. Group comparisons for angiogenesis (CD34), neural components (S100, neurofilament-associated proteins—NFAPs), and stromal activation (vimentin and actin) were conducted using Chi-square or Fisher’s exact tests. Results: ACL remnants revealed a significantly higher microvascular density (37 ± 2.3 vs. 18 ± 3.2 vessels/mm², p < 0.001), in addition to a markedly increased prevalence of synovial angiogenesis (90% vs. 20%, p < 0.001), stellate stromal cells (94% vs. 10%, p < 0.001), and CD34-positive fibrocytes (92% vs. 10%, p < 0.001) compared to control tissues. Elevated intraligamentous neovascularization (with borderline significance) was also found in these tissues (38% vs. 0%, p = 0.045). Both injured and control ACLs showed widespread S100-positive neural fibers, suggesting maintained Schwann cell integrity despite ligament disruption. In contrast, control ligaments showed a substantially richer NFAP+ neural network, particularly in small-caliber fibers and free nerve endings, pointing to preferential vulnerability of small-caliber neural elements during ACL rupture. Vimentin expression changes—from homogeneous fibrocytic staining to diffuse reticular overexpression in fibrotic lesions—were accompanied by the emergence of stellate myofibroblast-like cells, supporting advanced stromal remodeling. Absent in controls, actin immunoreactivity increased with lesion severity, indicating a progressive myofibroblastic response driven by perivascular cells during ligament remodeling. Conclusions: The tibial ACL remnant is a biologically active, compartmentalized repair niche driven by coordinated vascular, neural, and stromal responses, with reparative activity concentrated at the synovial–epiligament interface. These findings support the biological rationale for preserving tibial remnant for ACL reconstruction. Full article

The accurate measurement of dynamic forces is pivotal for advancing manufacturing process monitoring and enhancing equipment intelligence. To address the challenges of contact interface force field nonlinearity in existing PVDF piezoelectric film force sensors and the inability of a monolithic PVDF piezoelectric film to measure multi-dimensional forces, this study designs a uniform-load double-bossed elastic force-transmitting diaphragm to achieve contact interface force field reconstruction between the sensor’s elastic sensing structure and the sensitive element group. Building upon the load-bearing surface domain segmentation technique, the silver ink electrode on the front surface of a complete circular PVDF piezoelectric film is segmented into four independent sector-shaped rings. Each sector ring, together with its underlying PVDF piezoelectric film, constitutes a sensitive element, and these four sensitive elements are integrated to form the sensitive element group. The three-dimensional force measurement method of this sensitive element group in the Cartesian coordinate system is investigated. The measurement of three-dimensional force is realized by leveraging the tensile-compressive piezoelectric effect of each sensitive element in conjunction with a pre-stressed assembly structure. Quasi-static calibration test results indicate that the charge sensitivities of the force sensor in the X-, Y-, and Z-directions are 52.63 pC/N, 55.96 pC/N, and 9.02 pC/N, respectively, with a linearity ≤4.6%. Dynamic calibration test results reveal that the force measurement module exhibits a natural frequency of 4675.5 Hz. Experimental investigations into the response of triaxial cutting forces to variations in cutting speed, feed rate, and cutting depth were conducted, which verified the sensor’s ability to capture dynamic three-dimensional cutting forces. This study provides an effective solution for the structural design and three-dimensional force measurement methodology of PVDF piezoelectric film force sensors. Full article

Wool fibers undergo significant structural changes during industrial stretching, which directly impact their mechanical properties and textile performance, making monitoring of the stretching process essential for optimizing wool products. In this study, we demonstrate the effective use of polarized second harmonic generation (P-SHG) imaging for monitoring the wool fiber stretching process. P-SHG is highly sensitive to non-centrosymmetric structures, enabling clear observation of changes in α-keratin alignment and the reconstruction of cortical interfaces during stretching. Quantitative P-SHG analysis revealed a significant decrease in the effective pitch angle (θ_e) from 54° ± 1° to 33° ± 3° after stretching, confirming the dipole orientation changes in keratin molecules. These findings were further validated through additional characterization techniques, including scanning electron microscopy (SEM), polarizing optical microscopy (POM), X-ray diffraction (XRD), and Raman spectroscopy (RS). The results show that the industrial stretching process of wool alters the morphology at the surface scale, enhances the alignment of macroscopic fibers, and induces a transition from α-helix to β-sheet. Our technique is simple, effective, and capable of in situ monitoring of the structural changes in wool fibers, making it highly promising for applications in the wool industry. Full article

Background: Accurate evaluation of pressure distribution at the socket–limb interface is essential for improving prosthetic fit and comfort in transfemoral amputees. This study aimed to develop a proof-of-concept framework that integrates machine learning–based segmentation with the finite element method (FEM) to explore the feasibility of an initial workflow for residual-limb analysis during socket application. Methods: MRI data from a transfemoral amputee were processed using a custom image segmentation algorithm to extract adipose tissue, femur, and ischium, achieving high F-measure scores. The segmented tissues were reconstructed into 3D models, refined through outlier removal and surface smoothing, and used for FEM simulations in LS-DYNA. Pressure values were extracted at nine sensor locations and compared with experimental measurements to provide a preliminary qualitative assessment of model behaviour. Results: The results showed consistent polarity between measured and simulated values across all points. Moderate correspondence was observed at eight low-pressure locations, whereas a substantial discrepancy occurred at the ischial tuberosity (IS), the primary load-bearing site. This discrepancy likely reflects the combined influence of geometric deviation in the reconstructed ischium and the non-physiological medial boundary condition required to prevent unrealistic tissue displacement. This limitation indicates that the current formulation does not support reliable quantitative interpretation at clinically critical locations. Conclusions: Overall, the proposed framework provides an initial demonstration of the methodological feasibility of combining automated anatomical modeling with FEM for exploratory pressure evaluation, indicating that such an integrated pipeline may serve as a useful foundation for future development. While extensive refinement and validation are required before any quantitative or clinically meaningful application is possible, this work represents an early step toward more advanced computational investigations of transfemoral socket–limb interaction. Full article

In response to thermal failure risks in ultra-high voltage (UHV) bushing online monitoring devices and maintenance equipment—caused by high heat generation of electronic components and the intrinsically low thermal conductivity of conventional resin encapsulation materials—this study proposes a novel modification strategy based on flash Joule heating (FJH). Distinct from conventional interface modification methods, the proposed approach enables cross-scale, in situ microsoldering between multi-walled carbon nanotubes (MWCNTs) and carbon fibers (CFs), constructing a multiscale reinforcement network with integrated thermal transport and mechanical load transfer pathways. The transient ultra-high-temperature thermal shock generated by FJH not only effectively removes inert impurities on CF surfaces but also drives carbon structural reconstruction, enabling graphitic-level welding of MWCNTs onto the fiber surface. This micro-welded architecture fundamentally differs from traditional filler dispersion or interface coating strategies, which often suffer from the trade-off between interfacial thermal transport and mechanical bonding. By contrast, the FJH-induced carbon–carbon bonded nodes form a continuous conductive and load-bearing network at the micro–nano scale. Characterizations using scanning electron microscopy (SEM), Raman spectroscopy, and X-ray photoelectron spectroscopy (XPS) confirm successful in situ welding of MWCNTs onto CF surfaces. Meanwhile, FJH treatment effectively removes oxygen-containing functional groups and surface impurities. Analysis of carbon bonding evolution indicates that the welding efficiency reaches its maximum at 90 V. Macroscopic performance tests demonstrate that, compared with epoxy resin, the thermal conductivity of the multiscale reinforced system increases by approximately 168%, while the mechanical strength improves by 62.72%. This study provides new theoretical insights and technical pathways for the development of next-generation polymer composite materials with both high thermal conductivity and high mechanical strength. Full article

In underwater reconnaissance and patrol, AUV has to sense and judge traversability in cluttered areas that include reefs, cliffs, and seabed infrastructure. A narrow sonar field of view, occlusion, and current-driven disturbances leave the vehicle with local, time-varying information, so decisions are made with incomplete and uncertain observations. A path-planning framework is built around two coupled components: spatiotemporal graph neural network prediction and conditional normalizing flow (CNF)-based probabilistic environment reconstruction. Forward-looking sonar and inertial navigation system (INS) measurements are fused online to form a local environment graph with temporal encoding. Cross-temporal message passing captures how occupancy and maneuver patterns evolve, which supports path prediction under dynamic reachability and collision-avoidance constraints. For regions that remain unobserved, CNF performs conditional generation from the available local observations, producing probabilistic completion and an explicit uncertainty output. Conformal calibration then maps model confidence to credible intervals with controlled miscoverage, giving a consistent probabilistic interface for risk budgeting. To keep pace with ocean currents and moving targets, edge weights and graph connectivity are updated online as new observations arrive. Compared with Informed Random Tree star (RRT*), D* Lite, Soft Actor-Critic (SAC), and Graph Neural Network-Probabilistic Roadmap (GNN-PRM), the proposed method achieves a near 100% success rate at 20% occlusion and maintains about an 80% success rate even under 70% occlusion. In dynamic obstacle scenarios, it yields about a 4% collision rate at low speeds and keeps the collision rate below 20% when obstacle speed increases to 3 m/s. Ablation studies further demonstrate that temporal modeling improves success rate by about 7.1%, CNF-based probabilistic completion boosts success rate by about 13.2% and reduces collisions by about 17%, while conformal calibration reduces coverage error by about 6.6%, confirming robust planning under heavy occlusion and time-varying uncertainty. Full article

For high-speed compound helicopters, such as the S-97 Raider, the reflection and diffraction effects of vertical/horizontal tails on pusher propeller noise are inevitable. To investigate the noise distortion effect of the rear-mounted pusher propeller, this study first relies on the Chinese Laboratory of Rotorcraft Navier-Stokes (CLORNS) solver, adopting the high-resolution Perturbed polynomial reconstructed Targeted Essentially Non-Oscillatory scheme (TENO-P) combined with the Delayed Detached Eddy Simulation based on the Spalart–Allmaras (SA-DDES) turbulence model to resolve the multi-scale rotor flowfield. Additionally, a continuous and conserved acoustic source extraction method is proposed to eliminate non-physical waves at the one-way Computational Fluid Dynamics and Computational AeroAcoustics (CFD–CAA) coupling interface, addressing the temporal inconsistency between flowfield evolution and acoustic propagation. Finally, numerical investigations are conducted on the instantaneous acoustic wave propagation and acoustic directivity of the pusher propeller under the influence of vertical/horizontal tails. The results show that significant acoustic distortion occurs when pusher propeller-generated noise interacts with vertical/horizontal tails. This interaction not only produces reflected and diffracted acoustic waves but also leads to wavefront discontinuities, the formation of short acoustic waves, and changes in acoustic directivity. The maximum variation in the sound pressure level reaches 10 dB at local azimuths. The distortion effect of tails on pusher propeller noise is closely correlated with the number of propeller blades. The interaction process between the propeller and tails becomes more complex with the increase in blade count, resulting in the generation of shorter acoustic waves. For the six-blade rotor, the originally continuous acoustic wave branch can be split into up to four short waves. This study confirms that the proposed Hybrid Computational AeroAcoustics (HCAA) method holds significant application prospects in the aeroacoustic research of compound helicopters. Full article

The service reliability of critical catenary components is strongly influenced by damage evolution at dynamic contact interfaces. In this study, a numerical framework is developed to simulate the dynamic contact behavior and wear progression of catenary droppers by coupling Archard’s wear law with an adaptive remeshing strategy. Surface degradation is explicitly incorporated into the contact formulation through an improved boundary representation, enabling a quantitative linkage between interface damage and the corresponding mechanical responses. The simulations indicate that, after geometric reconstruction of the worn surface, the contact interface exhibits a pronounced stress-gradient evolution. The most severe damage is predicted at the contact region between the central strand and one outer strand, and the spatial damage pattern is primarily governed by discontinuous contact. Moreover, thermally induced material softening has a limited effect on the peak contact stress, which is dominated instead by the applied load and local contact geometry. The proposed framework provides a computational basis for assessing dropper wear and estimating catenary lifetime, thereby supporting reliability-oriented maintenance and safer rail operations. Full article

The Esquel pallasite provides a valuable record of metal–silicate interaction in differentiated planetesimals, yet many aspects of its formation and thermal evolution remain uncertain. Here, we present a comprehensive multi-technique characterization of a single Esquel specimen, integrating SC-XRD, Raman spectroscopy, SEM–EDS, XPS, magnetic force microscopy, and X-ray computed tomography. Olivine grains are shown to be structurally pristine, with the first full crystallographic refinement for Esquel confirming a single-domain silicate lattice. XPS demonstrates a stoichiometric silicate surface containing only lattice O²⁻, Si⁴⁺, Mg²⁺, and Fe²⁺, indicating that olivine remained chemically unaltered. The Fe–Ni metal preserves diffusion-controlled taenite–kamacite exsolution, compositionally distinct plessite, accessory schreibersite and troilite as resolved by SEM. Quantitative Ni zoning, evaluated through interface-to-center gradients and a width–center-Ni correlation method, yields a self-consistent cooling rate of ~10–20 °C/Myr. MFM reveals microscale magnetic structures that correlate directly with Fe–Ni chemical zoning, providing magnetic confirmation of slow cooling. CT analysis further identifies interconnected metal networks, inclusions, and micro-porosity reflecting melt migration and late-stage modification. These results establish Esquel as an exceptionally well-preserved pallasite and demonstrate the value of integrated, multi-scale analytical workflows for reconstructing early Solar System processes. Full article

At present, pedestrian navigation systems using smartphones have become common in daily activities. For their ubiquitous, accurate, and reliable services, map information collection is essential for constructing comprehensive spatial databases. Previously, we have developed a map information collection tool to extract building information using Google Maps, optical character recognition (OCR), geolocation, and web scraping with smartphones. However, indoor navigation often suffers from inaccurate localization due to degraded GPS signals inside buildings and Simultaneous Localization and Mapping (SLAM) estimation errors, causing position errors and confusing augmented reality (AR) guidance. In this paper, we present an improved map information collection tool to address this problem. It captures 360° panoramic images to build 3D models, apply photogrammetry-based mesh reconstruction to correct geometry, and georeference point clouds to refine latitude–longitude coordinates. For evaluations, experiments in various indoor scenarios were conducted. The results demonstrate that the proposed method effectively mitigates positional errors with an average drift correction of 3.15 m, calculated via the Haversine formula. Geometric validation using point cloud analysis showed high registration accuracy, which translated to a 100% task completion rate and an average navigation time of 124.5 s among participants. Furthermore, usability testing using the System Usability Scale (SUS) yielded an average score of 96.5, categorizing the user interface as ’Best Imaginable’. These quantitative findings substantiate that the integration of 360° imaging and photogrammetric correction significantly enhances navigation reliability and user satisfaction compared with previous sensor fusion approaches. Full article