Search Results (111)

Solar panels are an important device converting light energy into electricity not only from the sun but also from artificial light sources such as light emitting diodes (LEDs) or lasers. Recent advances in solar cell technologies enable them to be flexible, allowing them to be attached to things with different sizes and shapes. Therefore, it is challenging for AI-equipped systems to automatically recognize and distinguish flexible solar panels from other surrounding objects in realistic, complicated environments. Traditional recognition methods usually suffer from low recognition accuracy and high computational cost. Hence, this paper proposes a deep learning method for solar panel recognition using a complete work flow that includes data acquisition and dataset construction, YOLOv8-based model training, real-time solar panel recognition, and extended functionality. The proposed method demonstrates the accurate identification of realistic flat and flexible solar panels, including bent and partially shaded panels, with a mean average precision (mAP)@0.5 of 99.4% and an mAP@0.5:0.95 of 90.4%. The Pareto front for the multi-objective loss function minimization problem is also investigated to determine the optimal set of weighting parameters for the loss components. Furthermore, another functionality is added to detect the sizes of different solar panels if multiple ones co-exist. These features provide a promising foundation for further usage of the proposed deep learning approach to recognize flexible solar panels in realistic contexts. Full article

Accurate displacement field measurement by holographic interferometry requires robust analysis of high-density fringe patterns, which is hindered by speckle noise inherent in any interferogram, no matter how perfect. Conventional skeletonization methods, such as edge detection algorithms and active contour models, often fail under these conditions, producing fragmented and unreliable fringe contours. This paper presents a novel skeletonization procedure that simultaneously addresses three fundamental challenges: (1) topology preservation—by representing the fringe family within a physics-informed, finite-dimensional parametric subspace (e.g., Fourier-based contours), ensuring global smoothness, connectivity, and correct nesting of each fringe; (2) extreme noise robustness—through a robust strip integration functional that replaces noisy point sampling with Gaussian-weighted intensity averaging across a narrow strip, effectively suppressing speckle while yielding a smooth objective function suitable for gradient-based optimization; and (3) sub-pixel accuracy without phase extraction—leveraging continuous bicubic interpolation within a recursive quasi-optimization framework that exploits fringe similarity for precise and stable contour localization. The method’s performance is quantitatively validated on synthetic interferograms with controlled noise, demonstrating significantly lower error compared to baseline techniques. Practical utility is confirmed by successful processing of a real interferogram of a bent plate containing over 100 fringes, enabling precise displacement field reconstruction that closely matches independent theoretical modeling. The proposed procedure provides a reliable tool for processing challenging interferograms where traditional methods fail to deliver satisfactory results. Full article

Pipeline leakage is a common issue in many pressurized pipeline systems, with significant hazards, making it a current research hotspot. To reveal the fundamental characteristics of leakage in straight pipelines and 90° elbows transporting different media and thereby predict leakage locations, this paper conducts numerical calculations of the internal flow, while also predicting the pipeline leakage location monitoring model. The study finds that under air medium conditions, the nonlinear function model demonstrates excellent prediction accuracy, with R² > 0.99 for the water₃ condition. Under water medium conditions, the model’s fitting performance gradually weakens with increasing inlet pressure, with R² dropping to 0.77. For a bent pipe, when air is used as the medium, the pressure peak at the large bend angle increases significantly under high inlet pressure. In contrast, when water is the medium, the local pressure reconstruction effect in the bent pipe exhibits a linear strengthening trend as the inlet pressure increases. Full article

In this paper, we investigate the use of Bent functions, particularly the Maiorana–McFarland (M–M) construction, as a nonlinear preprocessing method to enhance machine learning-based detection systems for Distributed Denial of Service (DDoS) and Cross-Site Scripting (XSS) attacks. Experimental results demonstrated consistent improvements in classification performance following the M–M Bent transformation. In labeled DDoS data, classification performance was maintained at 100% accuracy, with improved Kappa statistics and lower misclassification rates. In labeled XSS data, classification accuracy was reduced from 100% to 87.19% to reduce overfitting. The transformed classifier also mitigated overfitting by increasing feature diversity. In DDoS and XSS unlabeled data, accuracy improved from 99.85% to 99.92% in unsupervised learning cases for DDoS, and accuracy improved from 98.94% to 100% in unsupervised learning cases for XSS, with improved cluster separation also being noted. In summary, the results suggest that Bent functions significantly improve DDoS and XSS detection by enhancing the separation of benign and malicious traffic. All of these aspects, along with increased dataset quality, increase our confidence in resilience detection in a cyber detection pipeline. Full article

Capsaicin, a naturally occurring polyphenol, is known to affect energy expenditure and muscle fatigue and modulate contractions in skeletal muscle. The L-type Ca²⁺ channels are known to be an important ion channel involved in the various muscle functions and the effect of capsaicin on the skeletal L-type Ca²⁺ channels is currently unknown. In this study, the effects of capsaicin and capsaicin analogs on depolarization-induced Ca²⁺ effluxes through L-type Ca²⁺ channels in transverse tubule membranes from rabbit skeletal muscle and L-type Ca²⁺ currents recorded using the whole-cell patch clamp technique in rat myotubes were examined. Capsaicin, in the concentration range of 3–100 µM, inhibited depolarization-induced Ca²⁺ effluxes. The effect of capsaicin was not reversed by TRPV1 antagonist SB-366791 (10 µM). While vanilloids (30 µM) including vanillin, vanillyl alcohol, and vanillylamine were ineffective, other capsaicinoids (30 µM) including dihydrocapsaicin, nonivamide, and nordihydrocapsaicin significantly inhibited Ca²⁺ effluxes, suggesting that hydrocarbon chains are required for inhibition. In rat myotubes, capsaicin inhibited L-type Ca²⁺ currents with an IC₅₀ value of 27.2 μM in the presence of SB-366791. Furthermore, in docking studies and molecular dynamic simulations, capsaicinoids with an aliphatic tail showed stronger binding and stable bent conformations in CaV1.1, forming hydrogen bonds with Ser1011 and Thr935 and hydrophobic/π–alkyl contacts with Phe1008, Ile1052, Met1366, and Ala1369, resembling the binding mode of amlodipine. In conclusion, the results indicate that the function of L-type Ca²⁺ channels in mammalian skeletal muscle was inhibited by capsaicin and capsaicin analogs in a TRPV1-independent manner. Full article

Flexible biosensors offer rapid and low-cost diagnostics but are often limited by the mechanical and electrochemical instability of polymer-based designs in biological media. Here, we introduce a metallic flexible microcrack transducer that exploits the intrinsic deformability of superelastic nickel–titanium (NiTi) for label-free impedimetric detection. Mechanical bending of NiTi wires spontaneously generates martensitic-phase microcracks whose metal–gap–metal geometry forms the active transduction sites, where functional interfacial layers and captured analytes modulate the local dielectric environment and govern the impedance response. Our approach imparts a novel dielectric character to the alloy, enabling its unexplored application in the megahertz (MHz) frequency domain (0.01–10 MHz) where native NiTi is merely conductive. Functionalization with Escherichia coli (E. coli)-specific antibodies renders these microdomains biologically active. This effectively transforms the mechanically induced microcracks into tunable impedance elements driven by analyte binding. The γ-bent NiTi sensors achieved stable and quantitative detection of E. coli ATCC 25922 in sterile human urine, with a detection limit of 64 colony forming units (CFU) mL⁻¹ within 45 min, without redox mediators, external labels, or amplification steps. This work pioneers the use of martensitic microcrack networks, mimicking self-healing behavior in a superelastic alloy as functional transduction elements, defining a new class of metallic flexible biosensors that integrate mechanical robustness, analytical reliability, and scalability for point-of-care biosensing. Full article

The deposition of particulate matter on rough pipe surfaces is critical in fields such as energy, chemical engineering, and air pollution control. This study employs a combined approach utilizing the Renormalized Group (RNG) k-ɛ model and the discrete phase model (DPM). The particle deposition characteristics in circular bent pipe channels with different dimple positions were investigated. To improve simulation fidelity, a model for particle-wall rebound was developed using user-defined function (UDF). The results indicate that the dimple structure influences the deposition location of particles. Particle deposition is minimal on the lower surface and leeward side of the dimple structure. For operating conditions where St ≤ 0.27, θ = 15° yields the optimal effect on enhancing the particle deposition rate, achieving a maximum increase of 18.2%. For conditions where St ≥ 0.461, the optimal angle is θ = 30°, resulting in a maximum deposition rate increase of 14.126%. The deposition rate of dimple structures varies depending on their installation location. In this study, the deposition rate was lowest at θ = 65°. The dimple structure can serve as a sacrificial element, providing protection for the rest of the bent pipe. In the future, channels incorporating this structure can be applied to removal or air purification equipment. Full article

Co-electrolysis of CO₂ and H₂O offers a promising route for efficient and controllable syngas production from greenhouse gases and water. However, the atomic-scale reaction mechanism remains elusive, especially on complex oxide surfaces. In this study, we employ density functional theory (DFT) to investigate the adsorption and activation of CO₂ and H₂O on the FeMoO-terminated (001) surface of Sr₂Fe_1.5Mo_0.5O₆ (SFM), a double perovskite of growing interest for solid oxide electrolysis. Our results show that CO₂ strongly interacts with surface lattice oxygen, adopting a bent configuration with substantial charge transfer. In contrast, H₂O binds more weakly at Mo sites through predominantly electrostatic interactions. Co-adsorption analyses reveal a bidirectional interplay: pre-adsorbed H₂O enhances CO₂ binding by altering its adsorption geometry, whereas pre-adsorbed CO₂ weakens H₂O adsorption due to competitive site occupation. This balance suggests that moderate co-adsorption may facilitate proton–electron coupling, while excessive coverage of either species suppresses activation of the other. Bader charge analysis, charge density differences, and projected density of states highlight the key role of Fe/Mo–O hybridized states near the Fermi level in mediating surface reactivity. These results, obtained for a perfect defect-free surface, provide a theoretical benchmark for disentangling intrinsic molecule–surface and molecule–molecule interactions, and offer guidance for designing high-performance perovskite electrocatalysts for CO₂ + H₂O co-electrolysis. Full article

Soft robot motion performance has long been a core focus in scientific research. This study investigates the motion capabilities of soft robots constructed using poly(N-isopropylacrylamide) (PNIPAM) hydrogels, with key innovations in material design and functional enhancement. By optimizing the hydrogel formulation and incorporating molybdenum disulfide (MoS₂) to endow it with photothermal response properties, the material achieves muscle-like controllable contraction and expansion deformation—a critical breakthrough in mimicking biological motion mechanics. Building on this material advancement, the research team developed a series of soft robotic prototypes to systematically explore the hydrogel’s motion characteristics. A flytrap-inspired soft robot demonstrates rapid opening–closing movements, replicating the swift responsiveness of natural carnivorous plants. For terrestrial locomotion, a hexapod crawling robot utilizes the photo-induced stretch-recovery mechanism of both horizontally configured and pre-bent feet to achieve stable directional propulsion. Most notably, a magnetically driven rolling robot integrates magnetic units to realize versatile multimodal movement: it achieves a stable rolling speed of 1.8 cm/s across flat surfaces and can surmount obstacles up to 1.5 times its own body size. This work not only validates the strong potential of PNIPAM hydrogel-based soft robots in executing complex motion tasks but also provides valuable new insights for the development of multimodal soft robotic systems, paving the way for future innovations in adaptive and bio-inspired robotics. Full article

Background: Mandibular defects caused by trauma or tumor resection pose significant challenges in both functional and aesthetic reconstruction. Additive manufacturing (AM) technologies offer promising solutions for surgical planning and personalized treatment. Objectives: This review aims to evaluate current trends in the application of AM technologies for mandibular resection and reconstruction, with a particular focus on material selection, clinical integration, and technology-specific advantages. Methods: A structured literature review was performed using PubMed, Scopus, Web of Science, and Google Scholar. Studies published between January 2020 and May 2025 were screened using the following inclusion criteria: original peer-reviewed English-language research involving AM in mandibular surgery. The exclusion criteria included review articles, non-English sources, and non-mandibular studies. A total of 77 studies met the inclusion criteria and were analyzed in this review. Results: Based on the literature review conducted from 2020 to 2025, the most common restorative methods for the mandible using additively manufactured models include reconstruction with a titanium surgical plate bent to the curvature of the edges and angle of the mandible or a personalized titanium or PEEK surgical plate made directly based on the patient’s diagnosis. Implants made of Ti-6AL-4V ELI and bioceramic scaffolds are also used in the reconstruction process. They are developed based on patient diagnostic data and effectively replace the loss of mandibular bone structure. In addition, based on models and surgical guides created using additive manufacturing techniques, the performance of autogenous grafts from the fibula or iliac crest has improved significantly when used with a titanium implant plate. Conclusions: Additive manufacturing supports highly personalized and accurate mandibular reconstruction. The advantages of these methods include a reduced overall duration of procedures, a lower health risk for patients due to less reliance on general anesthesia, a near perfect match between the implant and the remaining hard tissues, and satisfactory aesthetic outcomes. However, success depends on the appropriate selection AM technology and material, particularly in load-bearing applications. Full article

Background and Objectives: Orbital floor fractures are challenging to treat, due to the complex orbital anatomy and limited surgical access. Emerging technologies—such as virtual surgical planning (VSP), 3D printing, patient-specific implants (PSIs), and intraoperative navigation—offer promising advancements to improve the surgical precision and clinical outcomes. This review systematically evaluates and synthesizes current technological modalities with respect to their accuracy, operative duration, cost-effectiveness, and postoperative functional outcomes. Materials and Methods: A systematic review was conducted according to the PRISMA 2020 guidelines. The PubMed, Scopus, and PRIMO databases were searched for clinical studies published between 2019 and September 2024. Out of 229 articles identified, 9 met the inclusion criteria and were analyzed using the PICO framework. Results: VSP and 3D printing enhanced diagnostics and presurgical planning, offering improved accuracy and reduced planning time. Pre-bent PSIs shaped on 3D models showed superior accuracy, lower operative times, and better cost efficiency compared to intraoperative mesh shaping. Custom-designed PSIs offered high precision and clinical benefit but required a longer production time. Intraoperative navigation improved implant positioning and reduced the complication rates, though a detailed cost analysis remains limited. Conclusions: VSP, 3D printing, and intraoperative navigation significantly improve surgical planning and outcomes in orbital floor reconstruction. Pre-bent PSIs provide a time- and cost-effective solution with strong clinical performance. While customized PSIs offer accuracy, they are less practical in time-sensitive settings. Navigation systems are promising tools that enhance outcomes and may serve as an alternative to custom implants when time or resources are limited. Full article

Shape-sensing optical fibers have become increasingly important in applications requiring flexible navigation, spatial awareness, and deformation monitoring. Fiber Bragg Grating (FBG) sensors inscribed in multi-core optical fibers have been democratized over the years and nowadays offer a compact and robust platform for shape reconstruction. In this work, we propose a novel, computationally efficient method for determining the 3D tip position of a bent multi-core FBG-based optical fiber using a second-order polynomial approximation of the fiber’s shape. The method begins with a calibration procedure, where polynomial coefficients are fitted for known bend configurations and subsequently modeled as a function of curvature using exponential decay functions. This allows for real-time estimation of the fiber tip position from curvature measurements alone, with no need for iterative numerical solutions or high processing power. The method was validated using miniaturized test structures and achieved sub-millimeter accuracy (<0.1 mm) over a 4.5 mm displacement range. Its simplicity and accuracy make it suitable for embedded or edge-computing applications in confined navigation, structural inspection, and medical robotics. Full article

(1) Background: This study aimed to assess whether older adults exhibit greater discrepancies between intended and actual motor unit recruitment, which could affect the quality of muscle activation and potentially increase the risk of falls. (2) Methods: Forty-eight physically active older women were assessed (65 ± 6 years, 164 ± 6 cm, and 76 ± 7 kg). The bioelectrical activity (EMG) of the vastus lateralis oblique (VLO) and vastus medialis oblique (VMO) muscles were assessed during isometric testing with the knee joint bent to 75 degrees. The participants were instructed to press against a stable bar for 5 s at a specific percentage of their perceived force level (at 15%, 30%, and 60% of MVC) when the EMG activity was recorded. Balance was assessed using a stabilometric platform in a standing position. (3) Results: In all three thresholds, the bioelectrical activity of the VLO and VMO muscles significantly deviated from what was expected under the assumption of a nearly linear relationship between muscle force and bioelectrical activity. In each of the three thresholds, it did not exceed 10% MVC and significantly differed only between the 15% and 60% MVC thresholds. No significant differences were found between the dominant and non-dominant sides. A significant relationship was observed between the sway area (Area 95%) and the activity of the non-dominant limb VLO muscle. (4) Conclusions: Our results suggest that older adults experience deficits in muscle activation perception, leading to discrepancies between intended and actual muscle engagement, which may affect functional task performance and potentially increase fall risk. Full article

R-loops are nucleic acid structures composed of an RNA-DNA hybrid (RDH) duplex and a displaced single-stranded DNA (ssDNA), which are fundamentally involved in key biological functions, including transcription and the preservation of genome stability. In an R-loop, the RDH duplex is bent by the folded secondary structures of the displaced ssDNA. Previous experiments and simulations indicated the high bendability of DNA below the persistence length. However, the bendability of a short RDH duplex remains unclear. Here, we report that an RDH duplex exhibits higher bendability than a DNA duplex on the short length scale using single-molecule cyclization experiments. Our molecular dynamics simulations show that an RDH duplex has larger intrinsic curvature and structural fluctuations and more easily forms kinks than DNA, which promote the bending flexibility of RDH from unlooped structures. Interestingly, we found that an RDH duplex composed of a C-rich DNA strand and a G-rich RNA strand shows significantly higher bendability than that composed of a G-rich DNA strand and a C-rich RNA strand in the same CpG island promoter regions, which may contribute to the formation of an R-loop. These findings shape our understanding towards biological processes involving R-loops through the high and sequence-dependent bendability of an RDH duplex. Full article

This communication introduces a novel antenna miniaturization approach by strategically loading ferrites in distinct near-field regions. By identifying electric (E)- and magnetic (H)-field dominant zones in the antenna near-field, region-specific ferrites are strategically selected: high permittivity (ε_r) materials for E-field zones and high permeability (µ_r) materials for H-field zones. This strategy maximizes miniaturization while minimizing losses and the increase in antenna weight resulting from ferrite loading. To validate this method, a bent inverted-F antenna was designed and measured. The experimental results demonstrate that loading ferrites in E-field regions reduces the operating frequency from 2555–2620 MHz to 2230–2293 MHz with 68% efficiency, 20% higher than traditional full-coverage loading. Equivalent circuit analysis further reveals that selective loading increases capacitance/inductance for miniaturization while suppressing losses. This work establishes a new paradigm for a functional-material-based antenna design and offers a new research route for the fabrication of functional materials, aligning with 5G/6G demands for compact, integrated, low-loss systems. Full article