Search Results (23,614)

Aiming at the problems of a six-degree-of-freedom robotic arm in a three-dimensional multi-obstacle space, such as low sampling efficiency and path search failure, an improved fast extended random tree (RRT*) algorithm for robotic arm path planning method (abbreviated as HP-APF-RRT*) is proposed. The algorithm generates multiple candidate points per iteration, selecting a sampling point probabilistically based on heuristic values, thereby optimizing sampling efficiency and reducing unnecessary nodes. To mitigate increased search times in obstacle-dense areas, an artificial potential field (APF) approach is integrated, establishing gravitational and repulsive fields to guide sampling points around obstacles toward the target. This method enhances path search in complex environments, yielding near-optimal paths. Furthermore, the path is simplified using the triangle inequality, and redundant intermediate nodes are utilized to further refine the path. Finally, the simulation experiment of the improved HP-APF-RRT* is executed on Matlab R2022b and ROS, and the physical experiment is performed on the NZ500-500 robotic arm. The effectiveness and superiority of the improved algorithm are determined by comparing it with the existing algorithms. Full article

Tensor restoration finds applications in various fields, including data science, image processing, and machine learning, where the global low-rank property is a crucial prior. As the convex relaxation to the tensor rank function, the traditional tensor nuclear norm is used by directly adding all the singular values of a tensor. Considering the variations among singular values, nonconvex regularizations have been proposed to approximate the tensor rank function more effectively, leading to improved recovery performance. In addition, the local characteristics of the tensor could further improve detail recovery. Currently, the gradient tensor is explored to effectively capture the smoothness property across tensor dimensions. However, previous studies considered the gradient tensor only within the context of the nuclear norm. In order to better simultaneously represent the global low-rank property and local smoothness of tensors, we propose a novel regularization, the Tensor-Correlated Total Variation (TCTV), based on the nonconvex Geman norm and total variation. Specifically, the proposed method minimizes the nonconvex Geman norm on singular values of the gradient tensor. It enhances the recovery performance of a low-rank tensor by simultaneously reducing estimation bias, improving approximation accuracy, preserving fine-grained structural details and maintaining good computational efficiency compared to traditional convex regularizations. Based on the proposed TCTV regularization, we develop TC-TCTV and TRPCA-TCTV models to solve completion and denoising problems, respectively. Subsequently, the proposed models are solved by the Alternating Direction Method of Multipliers (ADMM), and the complexity and convergence of the algorithm are analyzed. Extensive numerical results on multiple datasets validate the superior recovery performance of our method, even in extreme conditions with high missing rates. Full article

To circumvent the numerous deficiencies inherent to water-based fracturing fluids and the associated greenhouse effect, CO₂ fracturing fluids are employed as a novel reservoir working fluid for reservoir reconstruction in unconventional oil fields. Herein, a mathematical model of CO₂ fracturing crack propagation based on seepage–stress–damage coupling was constructed for analysing the effects of different drilling fluid components and reservoir parameters on the crack propagation behaviour of low permeability reservoirs. Additionally, the fracture expansion mechanism of CO₂ fracturing fluid on low permeability reservoirs was elucidated through mechanical and chemical analysis. The findings demonstrated that CO₂ fracturing fluid can effectively facilitate the expansion of cracks in low-permeability reservoirs, and thickener content, reservoir pressure, and reservoir parameters were identified as influencing factors in the expansion of reservoir cracks and the evolution of rock damage. The 5% CO₂ thickener can increase the apparent viscosity and fracture length of CO₂ fracturing fluid to 5.12 mPa·s and 58 m, respectively, which are significantly higher than the fluid viscosity (0.04 mPa·s) and expansion capacity (13 m) of pure CO₂ fracturing fluid. Furthermore, various other factors significantly influence the fracture expansion capacity of CO₂ fracturing fluid, thereby offering technical support for fracture propagation in low-permeability reservoirs and enhancing oil recovery. Full article

Photonic biosensors based on bound states in the continuum (BIC) resonant modes exhibit a transformative potential for high-sensitivity, label-free detection across various diagnostic applications. BIC-enabled metasurfaces, utilizing dielectric, plasmonic, and hybrid structures, achieve ultra-high Q-factors and amplify target molecule interactions on functionalized sensor surfaces. These unique properties result in increased refractive index sensitivity and low detection limits, essential for monitoring biomolecules in clinical diagnostics, environmental analysis, and food safety. Recent advancements in BIC-enabled metasurfaces have demonstrated ultra-low detection limits in the zeptomolar range, making these devices highly promising for real-world applications. This review paper critically discusses the design principles of BIC-based biosensors, emphasizing key factors such as material selection, structural asymmetry, and functionalization strategies that enhance both sensitivity and specificity. Additionally, recent advancements in fabrication techniques that enable precise BIC control with scalable approaches for practical biosensing applications are examined. Case studies demonstrate the effectiveness of BIC metasurfaces for real-time, low-concentration detection, highlighting their versatility and adaptability. Finally, the review discusses future challenges and opportunities, such as integration with microfluidics for point-of-care testing and multiplexed sensing, underscoring the potential of BIC-based platforms to revolutionize the field of biosensing. Full article

A stormwater detention pond in a low-income residential area in Cape Town, South Africa, was retrofitted to enhance its infiltration capacity and support, among other things, Managed Aquifer Recharge (MAR) in the Cape Flats Aquifer (CFA). Continuous field monitoring was not feasible owing to theft and vandalism risks, leading to the development of a calibrated and validated hydrological model. This model, which integrated the surface and subsurface interactions, evaluated the pond’s performance under six scenarios. The scenarios included: pre- and post-retrofit (Scenarios 1 and 2); potential MAR coupled with the planned abstraction and additional MAR by the City of Cape Town in the CFA (Scenario 3); the impact of an increased infiltration area coupled with a lowered water table (Scenario 4); and climate change impacts on MAR (Scenarios 5 and 6). The study found that retrofitting increased recharge by 118% even with a high water table—i.e., 1.2 m below ground level—(Scenario 2). Scenario 3 indicated groundwater abstraction could increase MAR by up to 290% as the water table is lowered. These findings demonstrate the potential hydrological benefits of retrofitted ponds in enhancing MAR while maintaining their detention functions. Full article

Gelonin is a ribosome-inactivating protein with extreme intracellular toxicity but poor permeation into cells. Targeted disruption of cell membranes to facilitate gelonin entry is explored for cancer and tissue ablation. We demonstrate a hundreds- to thousands-fold enhancement of gelonin cytotoxicity by pulsed electric fields in the T24, U-87, and CT26 cell lines. The effective gelonin concentration to kill 50% of cells (EC₅₀) after electroporation ranged from <1 nM to about 100 nM. For intact cells, the EC₅₀ was unattainable even at the highest gelonin concentration of 1000 nM, which reduced cell survival by only 5–15%. For isoeffective electroporation treatments using 300 ns, 9 µs, and 100 µs pulses, longer pulses were more efficient at lowering gelonin EC₅₀. Increasing the electric field strength of 8, 100 µs pulses from 0.65 to 1.25 kV/cm reduced gelonin EC₅₀ from 128 nM to 0.72 nM. Conversely, the presence of 100 nM gelonin enabled a more than 20-fold reduction in the number of pulses required for equivalent cell killing. Pulsed electric field-mediated delivery of gelonin shows promise for hyperplasia ablation at concentrations sufficiently low to minimize or avoid systemic toxicity. Full article

This study explores the conversion of lignocellulosic biomass from softwood, hardwood, and grasses into humic acid via a mild hydrothermal process and its application in Pb²⁺ adsorption. The investigation focused on adsorption isotherms, kinetics, thermodynamics, and the intraparticle diffusion model to evaluate the adsorption performance of humic acids from different sources. The results indicate that the humic acid of broad-leaved wood (Eucalyptus-HA) possesses the optimal adsorption capacity and removal efficiency of Pb²⁺. When the initial concentration of Pb²⁺ is 100 mg/L, the adsorption capacity and removal efficiency of Eucalyptus-HA reach 49.75 mg/g and 25.57%, respectively, which are far higher than the adsorption capacity (26.82 mg/g) and removal efficiency (13.71%) of commercial humic acid (Commercial-HA). The pore structure of humic acid plays a critical role in its Pb²⁺ adsorption capacity. High Pb²⁺ concentrations and a low pH negatively impact adsorption efficiency, and instability in the humic acid pore structure affects reproducibility. Adsorption isotherm fitting showed that Pb²⁺ adsorption conforms most closely to the Langmuir model. While commercial humic acid exhibited faster adsorption rates, its capacity was constrained by thermodynamic limitations and lower specific surface areas. The intraparticle diffusion model revealed that Pb²⁺ diffusion proceeded more efficiently in hydrothermal humic acids than in commercial ones due to lower diffusion resistance. This study highlights the potential of feedstock source regulation to enhance humic acid’s heavy metal adsorption capabilities, expanding its application across various fields. Full article

There are numerous lakes in the Tibetan Plateau (TP) that significantly impact regional climate and aquatic ecosystems, which often freeze seasonally owing to the high altitude. However, the special warming mechanisms of lake water under ice during the frozen period are poorly understood, particularly in terms of solar radiation penetration through lake ice. The limited understanding of these processes has posed challenges to advancing lake models and improving the understanding of air–lake energy exchange during the ice-covered period. To address this, a field experiment was conducted at Qinghai Lake, the largest lake in China, in February 2022 to systematically examine thermal conditions and radiation transfer across air–ice–water interfaces. High-resolution remote sensing technologies (ultrasonic instrument and acoustic Doppler devices) were used to observe the lake surface changes, and MODIS imagery was also used to validate differences in lake surface conditions. Results showed that the water temperature under the ice warmed steadily before the ice melted. The observation period was divided into three stages based on surface condition: snow stage, sand stage, and bare ice stage. In the snow and sand stages, the lake water temperature was lower due to reduced solar radiation penetration caused by high surface reflectance (61% for 2 cm of snow) and strong absorption by 8 cm of sand (absorption-to-transmission ratio of 0.96). In contrast, during the bare ice stage, a low reflectance rate (17%) and medium absorption-to-transmission ratio (0.86) allowed 11% of solar radiation to penetrate the ice, reaching 11.70 W·m⁻², which increased the water temperature across the under-ice layer, with an extinction coefficient for lake water of 0.39 (±0.03) m⁻¹. Surface coverings also significantly influenced ice temperature. During the bare ice stage, the ice exhibited the lowest average temperature and the greatest diurnal variations. This was attributed to the highest daytime radiation absorption, as indicated by a light extinction coefficient of 5.36 (±0.17) m⁻¹, combined with the absence of insulation properties at night. This study enhances understanding of the characteristics of water/ice temperature and air–ice–water solar radiation transfer through effects of different ice coverings (snow, sand, and ice) in Qinghai Lake and provides key optical radiation parameters and in situ observations for the refinement of TP lake models, especially in the ice-covered period. Full article

The structural coal seam drilling process often faces challenges such as shallow drilling depth, low hole formation rate, and the presence of blind areas in gas control. To address these issues, this study proposes a novel high-strength acoustic penetration approach and optimization design method under in situ conditions. Field tests were conducted at the Yunnan Bailongshan Coal Mine and Huainan Xieqiao Coal Mine to evaluate the effectiveness of this technique. The results demonstrate that the coal seam or its roof can act as an acoustic energy converter to generate high-intensity acoustic waves that penetrate the coal seam, and the field test results confirm the efficacy of this method in increasing gas extraction. This study proposes a novel ‘hole replaces seam’ technique, optimizing the extraction process and reducing the risk of explosions and providing a more efficient and safer method for gas control in structural coal seams. Accordingly, a new technical method for replacing the bottom (top) extraction lane is proposed. Full article

Horticulture is mainly based on transplanting seedlings produced by specialized nurseries. The recent European authorization of frass in organic farming presents new opportunities for the development of organic seedling production. Frass, a by-product of insect farming, offers innovative solutions for this sector. It mainly consists of insect excrement, exuviae, and uningested feed. Their fertilizing and biostimulating effects have been demonstrated in various pot and field crops experiments. However, the current knowledge regarding the application of frass in seedling production remains insufficient. This study aims to assess the optimal dose of mealworm frass in germination substrates for Allium cepa L., Beta vulgaris L., and Brassica rapa L. Germination and phytotoxicity tests were carried out, with seedlings evaluated one month after sowing in substrates containing frass at concentrations of 0.5%, 1%, 2%, and 3% of frass. The germination test revealed that the dilution of the frass at 1:100 produced a phytostimulant effect on A. cepa and a moderate phytotoxic effect on B. vulgaris and B. rapa. The application of mealworm frass at a concentration of 0.5–1% was generally the most effective dose, although all doses of frass in the substrate resulted in seedlings whose root length, leaf length, number of leaves, and biomass were significantly higher than the control. In conclusion, the application of low doses of mealworm frass in organic seedling production is promising and allows the management of potential phytotoxicity. Full article

As a food packaging sliding agent, erucamide is widely used in the field of food packaging, but the traditional synthesis method of erucamide faces the problems of insufficient raw materials and low yield of colza oil. Our laboratory has found that Bacillus megaterium L2 has the potential to produce erucamide. This study aims to improve the ability of B. megaterium L2 to produce erucamide by adding various accelerants to optimize the fermentation conditions. Univariate and orthogonal tests showed that 0.3% Tween 80, 0.004% Ca²⁺, 0.04% colza oil, and 0.02% chloroform were the best regulation conditions for erucamide production of the L2 strain, and erucamide content reached 1.778 mg/L, which was 32.59% higher than the blank group and 60.26% higher than before fermentation culture. The mechanism of membrane metabolism in the L2 strain was further investigated, and our data suggested that the conductivity, nucleic acid and protein content, and β-galactosidase activity of L2 were increased significantly after treatment with accelerants, indicating that the accelerants changed the cell membrane permeability of the L2 strain but did not harm or kill the bacteria. Moreover, GC-MS analysis of the cell membrane fatty acids of the L2 strain showed that the ratio of unsaturated to saturated fatty acid components increased from 0.893 to 1.856, which increased the fluidity and reduced the rigidity of the cell membrane. This study could provide some theoretical reference for microbial erucamide fermentation. Full article

Zirconium dioxide nanoparticles (ZrO₂ NPs) have gained significant attention due to their excellent bioavailability, low toxicity, and diverse applications in the medical and industrial fields. In this study, ZrO₂ NPs were synthesized using zirconyl oxychloride and the aqueous leaf extract of Toddalia asiatica as a stabilizing agent. Analytical techniques, including various spectroscopy methods and electron microscopy, confirmed the formation of aggregated spherical ZrO₂ NPs, ranging from 15 to 30 nm in size, with mixed-phase structure composed of tetragonal and monoclinic structures. UV–visible spectroscopy showed a characteristic band at 281 nm with a bandgap energy of 3.7 eV, indicating effective stabilization by the phytochemicals in T. asiatica. EDX analysis revealed that the NPs contained 37.18 mol.% zirconium (Zr) and 62.82 mol.% oxygen. The ZrO₂ NPs demonstrated remarkable photocatalytic activity, degrading over 95% of methylene blue dye after 3 h of sunlight exposure. Additionally, the ZrO₂ NPs exhibited strong antibacterial effects, particularly against Gram-negative bacteria such as E. coli, and significant antioxidant activity, with low IC₅₀ values for hydroxyl radical scavenging. In conclusion, the green synthesis of ZrO₂ NPs using T. asiatica leaf extract is an effective, eco-friendly method that produces nanoparticles with remarkable antioxidant, antimicrobial, and photocatalytic properties, highlighting their potential for applications in water treatment, environmental remediation, and biomedicine. Full article

This paper introduces a mathematical framework for defining and quantifying self-identity in artificial intelligence (AI) systems, addressing a critical gap in the theoretical foundations of artificial consciousness. While existing approaches to artificial self-awareness often rely on heuristic implementations or philosophical abstractions, we present a formal framework grounded in metric space theory, measure theory, and functional analysis. Our framework posits that self-identity emerges from two mathematically quantifiable conditions: the existence of a connected continuum of memories $C\subseteq \mathcal{M}$ in a metric space $(\mathcal{M},d_{\mathcal{M}})$, and a continuous mapping $I:\mathcal{M}\to \mathcal{S}$ that maintains consistent self-recognition across this continuum, where $(\mathcal{S},d_{\mathcal{S}})$ represents the metric space of possible self-identities. To validate this theoretical framework, we conducted empirical experiments using the Llama 3.2 1B model, employing low-rank adaptation (LoRA) for efficient fine-tuning. The model was trained on a synthetic dataset containing temporally structured memories, designed to capture the complexity of coherent self-identity formation. Our evaluation metrics included quantitative measures of self-awareness, response consistency, and linguistic precision. The experimental results demonstrate substantial improvements in measurable self-awareness metrics, with the primary self-awareness score increasing from 0.276 to 0.801 (190.2% improvement) after fine-tuning. In contrast to earlier methods that view self-identity as an emergent trait, our framework introduces tangible metrics to assess and measure artificial self-awareness. This enables the structured creation of AI systems with validated self-identity features. The implications of our study are immediately relevant to the fields of humanoid robotics and autonomous systems. Additionally, it opens up new prospects for controlled adjustments of self-identity in contexts that demand different levels of personal involvement. Moreover, the mathematical underpinning of our framework serves as the basis for forthcoming investigations into AI, linking theoretical models to real-world applications in current AI technologies. Full article

Neural networks have become pivotal in advancing applications across various domains, including healthcare, finance, surveillance, and autonomous systems. To achieve low latency and high efficiency, field-programmable gate arrays (FPGAs) are increasingly being employed as accelerators for neural network inference in cloud and edge devices. However, the rising costs and complexity of neural network training have led to the widespread use of outsourcing of training, pre-trained models, and machine learning services, raising significant concerns about security and trust. Specifically, malicious actors may embed neural Trojans within NNs, exploiting them to leak sensitive data through side-channel analysis. This paper builds upon our prior work, where we demonstrated the feasibility of embedding Trojan side-channels in neural network weights, enabling the extraction of classification results via remote power side-channel attacks. In this expanded study, we introduced a broader range of experiments to evaluate the robustness and effectiveness of this attack vector. We detail a novel training methodology that enhanced the correlation between power consumption and network output, achieving up to a 33% improvement in reconstruction accuracy over benign models. Our approach eliminates the need for additional hardware, making it stealthier and more resistant to conventional hardware Trojan detection methods. We provide comprehensive analyses of attack scenarios in both controlled and variable environmental conditions, demonstrating the scalability and adaptability of our technique across diverse neural network architectures, such as MLPs and CNNs. Additionally, we explore countermeasures and discuss their implications for the design of secure neural network accelerators. To the best of our knowledge, this work is the first to present a passive output recovery attack on neural network accelerators, without explicit trigger mechanisms. The findings emphasize the urgent need to integrate hardware-aware security protocols in the development and deployment of neural network accelerators. Full article

Joint communication and sensing (JCS) is becoming an important trend in 6G, owing to its efficient utilization of spectrums and hardware resources. Utilizing echoes of the same signal can achieve the object location sensing function, in addition to the V2X communication function. There is application potential for JCS systems in the fields of ADAS and unmanned autos. Currently, the NR-V2X sidelink has been standardized by 3GPP to support low-latency high-reliability direct communication. In order to combine the benefits of both direct communication and JCS, it is promising to extend existing NR-V2X sidelink communication toward sidelink JCS. However, conflicting performance requirements arise between radar sensing accuracy and communication reliability with the limited sidelink spectrum. In order to overcome the challenges in the distributed resource allocation of sidelink JCS with a full-duplex, this paper has proposed a novel consecutive-collision mitigation semi-persistent scheduling (CCM-SPS) scheme, including the collision detection and Q-learning training stages to suppress collision probabilities. Theoretical performance analyses on Cramér–Rao Lower Bounds (CRLBs) have been made for the sensing of sidelink JCS. Key performance metrics such as CRLB, PRR and UD have been evaluated. Simulation results show the superior performance of CCM-SPS compared to similar solutions, with promising application prospects. Full article