Search Results (2,443)

Let $\beta$ be a contact form on a compact smooth manifold X and $v_{\beta }$ its Reeb vector field. This study applies the general results of different authors regarding Hodge structures that are transversal to a given foliation to the special case of 1-dimensional foliation generated by the Reeb flow $v_{\beta }$. The de Rham differential complex ${\Omega }_{\mathsf{basic}}^{*}(X,v_{\beta })$ of so-called basic forms relative to $v_{\beta }$-flow differential forms is the focus of this investigation. By definition, basic forms vanish when being contracted with $v_{\beta }$, and so do their differentials. We prove that under the change of $\beta ⇝{\beta }_1=\beta +df$, where a function $f:X\to \mathbb{R}$ such that $df\left(v_{\beta }\right)>-1$, the differential complexes ${\Omega }_{\mathsf{basic}}^{*}(X,v_{{\beta }_1})$ and ${\Omega }_{\mathsf{basic}}^{*}(X,v_{\beta })$ are canonically isomorphic. We investigate when the 2-form $d\beta$ and its powers deliver nontrivial elements in the basic de Rham cohomology $H_{\mathsf{basic}d\mathcal{R}}^{*}(X,v_{\beta })$ of the differential complex ${\Omega }_{\mathsf{basic}}^{*}(X,v_{\beta })$. Answers to these questions contrast sharply in the cases of a closed X and an X with boundary. Building on the work of Raźny, we show that on a closed manifold X equipped with a transversal to the Reeb flow Hodge structure that satisfies the Basic Hard Lefschetz Property, the basic de Rham cohomology $H_{\mathsf{basic}d\mathcal{R}}^{*}(X,v_{\beta })$ is a topological invariant of X. Full article

Wollastonite is a natural meta-silicate mineral material with fibrous characteristics. In this paper, wollastonite with different aspect ratios obtained after grinding was used as a mineral admixture to replace cement for preparing ultra-high-toughness cement-based composites (UHTCCs). The effects of wollastonite on the fluidity, compressive strength, flexural strength, and tensile properties of UHTCCs were investigated, and the crack morphology and micro-topography of the tensile specimens after fracture were observed. The experimental results show that when the wollastonite replacement ratio exceeds 4%, it exerts a negative effect on the fluidity of UHTCCs, and wollastonite with a larger aspect ratio has a more significant negative impact. Relying on the bridging effect, replacing cement with wollastonite can significantly improve the flexural strength and compressive strength of UHTCCs. However, when the replacement ratio exceeds 6%, the strength enhancement effect of wollastonite with a larger aspect ratio begins to decrease. When the cement replacement ratio of wollastonite is up to 6%, it can increase the initial cracking strength, tensile strength and tensile strain of UHTCCs. At the same replacement ratio, wollastonite with a larger aspect ratio shows a better reinforcing effect. According to the observation of post-fracture crack morphology, the cracks of UHTCCs change from the original smooth cracks to tortuous ones after cement is partially replaced by wollastonite. Replacing a part of cement with wollastonite optimizes the performance relationship among PE fibers, the matrix, and the PE fiber–matrix interface, and it enhances their synergistic effect. This not only raises the initial tensile cracking strength of UHTCCs but also improves its tensile strain. In particular, wollastonite with a larger aspect ratio exhibits a more pronounced reinforcing effect. Full article

Fourier-transform spectroscopy is a widely used technique for determining the spectral and thermal properties of a target. However, target temperature variations during measurement can compromise the spectral accuracy. Temperature fluctuations induce oscillations superimposed on the target spectrum. These oscillations, referred to as scene-change artifacts, degrade the spectral accuracy. The literature is divided, with theoretical predictions suggesting negligible artifacts and growing experimental evidence reporting significant artifacts. This paper presents a theory and experimental validation of scene-change artifacts originating from target temperature variations. Traditionally, the interferogram offset is assumed to be constant, an invalid assumption for a changing scene. The error is subsequently Fourier-transformed, producing scene-change artifacts. Accurately estimating the truth spectrum is often challenging. To address this, we propose the signal-to-scene-change-artifact ratio, a metric that quantifies the impact of scene-change artifacts without knowledge of the truth spectrum. The artifacts will be eliminated by estimating the interferogram offset using smooth offset correction. Furthermore, the interferogram offset enables determination of the target’s temperature with a greater accuracy and an increased temporal resolution compared to using the spectra. These results will demonstrate that a smooth offset correction can improve the spectrum and temperature accuracy on thermally variant targets when measured with a Fourier-transform spectrometer. Full article

This paper develops a unified finite-bit distributed optimization framework for UAV swarms operating over bandwidth-limited communication graphs. We consider strongly convex and smooth global objectives decomposed over local UAV cost functions and study three communication-efficient algorithmic regimes. First, we design a quantized distributed gradient-tracking descent scheme with fixed finite-bit communication and show that, under bounded quantization errors, the method converges R-linearly to a quantization-dependent neighborhood of the global optimizer. Second, we introduce an adaptive quantization strategy that dynamically adjusts the number of transmitted bits according to the current convergence stage. By forcing the quantization distortion to decay proportionally to the optimization error, the proposed adaptive scheme recovers exact linear convergence to the optimal solution while substantially reducing the cumulative communication load. Third, we develop a fully distributed 1-bit communication mode in which UAVs exchange only sign information and use coordinate-wise majority voting to aggregate both descent and consensus directions. The robust linear-contraction property is proved to a small neighborhood under a sign-Polyak–Lojasiewicz condition and a probabilistic majority-correctness assumption. Full article

The anchovy (Engraulis japonicus) is a highly abundant but underutilized fish resource in China, primarily due to its extreme post-harvest perishability. This study expanded the utilization of anchovy by developing a blended surimi from anchovy and golden threadfin bream, an I-optimal mixing design experiment was performed to optimize the formulation, and the effects of soy protein isolate (SPI), egg white powder (EWP), and yeast protein (YP) on the gel properties were investigated. The results of sensory evaluation and model prediction indicated that SPI had the most pronounced positive effect on the sensory characteristics of the gels, especially improving the elasticity, followed by EWP. Furthermore, the SPI-rich sample exhibited superior gel strength and chewiness, which was attributed to the increased β-sheet structure and the highest content of disulfide bonds in the protein network. And the water hold capacity of SPI-rich sample increased by 6.0%. The YP-rich group showed the strongest hydrophobic interactions and exhibited a significant enhancement in water hold capacity of 7.7%, which also provided a notable improvement in gel strength. The results showed that EWP contributed to the smoothness of the surimi, but it had no significant impact on water distribution, water-holding capacity, or the content of disulfide bonds within the gel network. Moreover, the EWP-rich group exhibited reduced the gel strength, hardness, and chewiness of the gel, resulting in the lowest overall sensory score of the surimi. Therefore, the optimal composite ratio was determined to be SPI:EWP:YP = 5.45%:2.55%:2.00%. These findings provided a precise blending strategy for developing high-quality surimi products from anchovy, offering a viable technical pathway for the value-added utilization of this resource. Full article

For electric vehicles, accurate real-time estimation of the road friction coefficient is critical for maintaining stability, as the millisecond-level response of electric motors and the integration of regenerative braking demand higher perception fidelity than traditional internal combustion vehicles. This paper proposes a methodological framework for road friction estimation specifically designed for intelligent E-Chassis based on micro-signal features of intelligent tires and deep learning. An intelligent tire system, integrated with tri-axial accelerometers and strain gauges, was installed on the front-left wheel of a test vehicle to capture raw dynamic signals during transitions from cement to snow-covered surfaces across a velocity gradient of 10–50 km/h. The Savitzky–Golay convolutional smoothing algorithm was applied to reconstruct the high-frequency raw signals, enabling the extraction of a five-dimensional feature vector comprising vehicle velocity, peak strain, contact patch width, peak-to-peak acceleration, and signal standard deviation. The study revealed a natural filtering effect originating from the porous elastic properties of snow, resulting in a 60–70% reduction in signal standard deviation compared to cement, accompanied by a cliff-like feature collapse at the moment of snow entry. A BP neural network model with a 5-7-1 architecture achieved an identification accuracy of 96.2% on the test set, facilitating a rapid real-time prediction of the friction coefficient transitioning from 0.75 to 0.23. Unlike traditional methods, the proposed approach does not rely on high slip ratios and can complete identification within the first physical rotation cycle. This provides a robust physical criterion for the torque vectoring and regenerative braking stability of intelligent electric vehicles in extreme environments. Full article

Coastal reclaimed areas are characterized by complex strata and high groundwater levels, and pile foundations in such areas often suffer from insufficient uplift resistance. Compared with conventional cast-in-place piles, squeezed branch piles exhibit superior uplift performance; however, studies on squeezed branch piles in reclaimed areas remain limited. To investigate the uplift bearing performance of squeezed branch piles in the complex strata of coastal reclaimed areas, in situ full-scale uplift tests were conducted in the Shenzhen Binhai Avenue (Headquarters Base Section) traffic reconstruction project. Based on the actual physical and mechanical properties of the soil strata, a three-dimensional numerical model was established and validated against the load–displacement curves obtained from the in situ full-scale uplift tests. On this basis, the uplift bearing performance of squeezed branch piles, the differences in uplift bearing performance between branch and plate structures, and their applicable strata were analyzed. The plate structure and different branch configurations of squeezed branch piles exhibit distinct symmetric configuration characteristics, and these configuration differences influence the overall uplift bearing performance. The results show that the load–displacement curves of the uplift piles are generally smooth, without obvious abrupt rises or drops, exhibiting a gradual variation pattern, and the maximum pile-head displacements are all less than 100 mm. The mobilization of the bearing capacity of the branch and plate structures exhibits a distinct temporal and sequential pattern, with the plate structures at shallower embedment depths mobilized earlier than those at greater depths. Compared with conventional cast-in-place pile foundations, the presence of branches and plates endows squeezed branch piles with better elastic mechanical behavior and higher rebound ratios during unloading. Under identical stratum and loading conditions, the uplift bearing performance of the plate is 133% higher than that of the six-radial-branch configuration, while that of the six-radial-branch configuration is 34% higher than that of the four-radial-branch configuration. It is recommended to adopt the six-radial-branch configuration in clayey sandy gravel strata and the plate configuration in gravelly clayey soil and completely weathered coarse-grained granite strata, whereas neither branches nor plates are recommended in soil-like strongly weathered coarse-grained granite strata. Full article

Entropic soft-min operators are widely used to obtain smooth approximations of minimum and argmin mechanisms in optimization, machine learning, and reinforcement learning. The quality of this approximation is controlled by an inverse temperature parameter that governs the trade-off between smoothness and fidelity, yet its selection is usually based on global heuristics or worst-case bounds that do not account for the geometry of the candidate cost vector. This study investigates the calibration of the inverse temperature parameter from a geometry-aware perspective, with explicit guarantees on the approximation error between the entropic soft-min and the exact minimum value. After establishing the structural properties of the relaxation error, including monotonicity with respect to the inverse temperature and its dependence on the geometry of the near-optimal set, we introduce a conformal calibration rule that selects the smallest inverse temperature, ensuring that a prescribed upper quantile of the approximation error remains below a target tolerance with distribution-free finite-sample validity. The resulting selector adapts to the geometry distribution represented in the calibration population and provides a principled alternative to mean-based and worst-case tuning rules. Numerical experiments, including geometry-controlled benchmarks and a contextual bandit setting illustrating the impact of geometry-aware calibration on decision-making under estimated action values, show that the proposed method accurately tracks oracle calibration temperatures, preserves the desired operator-level coverage, and makes explicit how geometric heterogeneity governs the effective sharpness required by the soft-min approximation. Additional shifted evaluations illustrate the role of exchangeability in the validity guarantee and the consequences of transferring temperatures across populations with different near-optimal geometries. Full article

This study investigates the femtosecond laser surface texturing approach to tune the wetting properties of glass substrates applied for photovoltaic panels. Two types of microstructured LIPSS-containing motifs—parallel channels and intersecting (crossing) patterns—were fabricated and evaluated through comprehensive durability tests, including thermal cycling, UV exposure, chemical immersion, mechanical abrasion, and dust retention assessment. Wettability measurements showed that both textures exhibit stable hydrophilicity behavior, with the intersecting patterns exhibiting the fastest wetting dynamics; in many cases, complete surface wetting occurred within the first few minutes, preventing a measurable contact angle at later stages. The durability tests caused only minor smoothing of the textured features, and the overall micro- and nanostructures remained intact. Optical characterization revealed that the laser-induced textures maintained high transmittance with no significant degradation after environmental exposure. Overall, the results demonstrate that femtosecond laser texturing provides a robust, coating-free method for producing stable and tunable wetting behavior on glass, offering a promising pathway for the future creation of durable, highly hydrophilic self-cleaning surfaces in photovoltaic systems. Full article

While macroscopic stress significantly impacts the performance of metallic components, the underlying atom–electron coupling mechanisms governed by distinct crystal symmetries remain insufficiently understood. To address this gap, this work systematically investigates the structural and electronic evolution of representative metallic materials under applied stress. Experimentally, X-ray diffraction (XRD) revealed complex macroscopic residual stress distributions in cold rolled titanium alloy and silicon steel. Motivated by these engineering observations, first-principles density functional theory (DFT) calculations were conducted to uncover the underlying physical mechanisms. Specifically, the responses of face-centered cubic (FCC) aluminum and copper, body-centered cubic (BCC) iron, and hexagonal close-packed (HCP) titanium crystals were investigated under tension and compression using the RPBE functional. Stress-dependent elastic properties, density of states (DOS), band structures, and phonon spectra were calculated. Results show that tension softens all metals (Al becomes mechanically unstable), whereas compression stiffens their lattices. Electronically, tensile loading sharpens DOS peaks near the Fermi level and shifts conduction bands closer to it, whereas compression smooths DOS peaks and shifts bands away. Phonon analysis indicates Cu and Ti remain dynamically stable, while Al and Fe exhibit phonon mode softening under high tension. These stress-induced changes highlight crucial atom–electron coupling mechanisms, providing a theoretical basis for tailoring metallic performance via stress engineering. Full article

Titanium alloys are widely used in dental implants due to their excellent mechanical properties. However, their inertness and poor antibacterial activity cause interfacial loosening and failure, shortening service life. This study integrates surface microtexturing with coating technologies, employing modified light-curing composite resins to boost the bioactivity of medical titanium alloys via surface modification. The results reveal that surface microtexturing enlarges the coating-substrate contact area by 42.5% compared with rough surfaces, concurrently diminishing stress per unit area, and the coating on microtextured Ti-6Al-4V (TC4) surfaces achieves adhesion with a damaged area of only 0.5%, thereby notably enhancing adhesion between the coating and TC4 matrix. In comparison, with rough surfaces (surface roughness of 0.658 μm), smooth TC4 planes (surface roughness of 0.014 μm) show a significantly reduced bacterial colony count (from 130 ± 6 to 42 ± 3) with an antibacterial rate of 67.7%, as the water contact angle on TC4 surfaces increases with decreasing roughness (reaching 80.95° on the smoothest surface), making bacterial adhesion more challenging and reducing colonization. The composite resin coating based on a mixture of titanium-doped hydroxyapatite and titanium dioxide (Ti-HA/TiO₂) further improves the antibacterial rate to 74.6% through a photocatalytic synergistic effect and endows TC4 with excellent remineralization capacity—mineralization deposits appear on the coated surface after 3 days of immersion in artificial saliva, while no obvious deposits are found on uncoated rough and smooth surfaces even after 7 days—thereby enhancing its bioactivity effectively. This study on the modification of Ti-based implant surfaces will enrich the field by introducing new technologies and methodologies. These advancements provide a theoretical basis for improvement of the remineralization capacity and antibacterial properties of Ti-based dental implants, thereby promoting broader biomedical applications. Full article

For the complex problems of multi-aircraft cooperative game guidance with No-Fly Zone (NFZ) avoidance and cross-task constraint propagation, a deep deterministic policy gradient algorithm with temporal awareness and priority cooperative optimization (TP-MADDPG) is proposed. Based on the three-body cooperative guidance, a new coupled guidance task is formed by adding the NFZ avoidance constraint. At the same time, considering the constraint compatibility problem in dynamic task switching, the cooperative aircraft are modeled as independent agents with differentiated policy networks. First, a nonlinear kinematic model of the three-body game constructed by Evader–Pursuer–Defender is established. And four complex constraint conditions, namely homing guidance, NFZ avoidance, collision avoidance, and cooperative guidance, are modeled separately. Secondly, the Long Short-Term Memory-based (LSTM) Actor–Critic framework is proposed to dynamically capture the evolution patterns of adversarial scenarios by mining hidden correlations in historical state-action sequences. This enables smooth policy transitions between the cooperative guidance phase and subsequent homing guidance phase, effectively addressing the challenges of environmental non-stationarity and temporal task dependencies. Then, a priority-driven adaptive sampling mechanism is proposed along with a heterogeneous roles cooperative reward function to specifically address credit assignment imbalance and sparse reward problems, respectively. The sampling mechanism capitalizes on the efficient retrieval properties of SumTree data structures while integrating bias correction techniques to expedite policy gradient convergence. The reward function utilizes the reward shaping method to formulate cooperative reward components that explicitly capture behavioral correlations among agents. Finally, simulations show that the proposed method significantly outperforms multi-agent reinforcement learning baselines, effectively improving the performance of cooperative game guidance under complex constraints. Full article

This study reveals the structure–property relationship between Cu powder characteristics on 6063 Al alloy surface and the interface behavior of cold spray coatings. Through systematic experiments, we examined the effects of different oxygen content in atomized Cu powder to deposition thickness and coating interface adhesion strength. Results showed that #2 Cu powder exhibited smooth surfaces with clear particle distribution and low oxygen content, while #1 powder contained more fine particles and higher oxygen content. Under identical process conditions, #2 cold spray coatings achieved thickness distributions ranging from 73.94 μm to 162.27 μm with excellent density, whereas #1 products displayed uneven thickness distribution (minimum 34.27 μm, maximum 136.69 μm) and crack formed between coatings. The adhesion strength between #2 products substrate and coating exceeded 70 MPa, which was 61 MPa higher than #1’s maximum adhesion strength. Full article

Precision soil management is fundamental to the sustainable production of high-quality tea, yet the spatial integration of fertility and heavy metal safety remains a significant challenge. This study aimed to delineate multi-dimensional management zones (MZs) in the tea plantations of Tianmuhu, Jiangsu Province, by evaluating three clustering algorithms: K-means (KM), Fuzzy C-means (FCM), and Iterative Self-Organizing Data Analysis Technique (ISODATA). A total of 70 representative soil samples were analyzed for 10 properties. Descriptive statistics revealed pronounced spatial heterogeneity, particularly for Hg (CV = 71.04%) and P (CV = 61.83%). Pearson correlation and Principal Component Analysis (PCA) demonstrated strong synergistic relationships among organic matter (OM), nitrogen (N), and potassium (K) (r = 0.49–0.69, p < 0.01), which formed a distinct Fertility Factor on PC1. Conversely, PCA identified divergent sources for heavy metals, with Cr primarily governed by pedogenic processes (PC2), while Cd were associated with anthropogenic inputs. Guided by these distinct spatial drivers, this study separately delineated fertility and heavy metal safety MZs. The optimal number of clusters was determined by balancing statistical validity with spatial operationality via the Silhouette Coefficient (SC) and Smoothness Index (SI), with results indicating that a 2–3 zone scheme yielded the most favorable scores. Comparative analysis showed that for soil fertility, ISODATA outperformed KM and FCM by effectively capturing the high variability of P and producing statistically distinct zones (p < 0.05). For heavy metal pollution, FCM provided better partitioning by reflecting the continuous gradients of composite contaminants. Validation results showed that while 61% of the area was classified as high-fertility (ISODATA), approximately 63–75% fell into relatively higher heavy metal accumulation categories. This dual-objective zoning framework provides a scientific basis for site-specific fertilization and targeted environmental monitoring in the regional tea industry. Full article

Axial Flux Permanent Magnet Synchronous Motors (AFPMSMs) are gaining increasing attention for their application in electric vehicle (EV) drive systems. Their high torque density and compact axial geometry make them attractive for high-performance EV drive systems. However, cogging torque remains a major challenge, degrading low-speed drivability, noise performance, and control stability. This article proposes a magnet skew on rotor modulation structure using a genetic algorithm (GA) to reduce cogging torque in AFPMSMs utilizing a 12/15 non-integer pole/slot arrangement. The objective of optimization is to simultaneously reduce cogging torque under identical electromagnetic constraints. A complete three-dimensional finite element model (3D-FEM) incorporating nonlinear magnetic material properties has been developed to evaluate the electromagnetic field distribution and torque components. The results indicate that a 12/15 non-integer pole/slot arrangement improves harmonic distribution and extends the operating range with lower cogging torque compared to integer pole/slot designs. Combined with GA-optimized skew angles, this reduces peak-to-peak cogging torque to less than 50%. This design is ideally suited for the traction requirements of electric vehicles, including premium electric vehicles where smooth operation at low speeds is critical. Full article