To enhance the DC electrical performance of cross-linked polyethylene(XLPE),the graftable antioxidant methacrylic acid 2-hydroxy-3-(4-anilinoanilino)propyl ester(GA),which contains carbonyl and amino groups,and the cr...
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To enhance the DC electrical performance of cross-linked polyethylene(XLPE),the graftable antioxidant methacrylic acid 2-hydroxy-3-(4-anilinoanilino)propyl ester(GA),which contains carbonyl and amino groups,and the crosslinking coagent trimethylolpropane trimethacrylate(TMPTMA),which contains carbonyl groups,are individually or co-grafted onto *** slightly higher deep trap density introduced by higher grafting concentration of TMPTMA results in more significant suppression effect of conductance current and enhanced breakdown strength at a lower temperature,while the suppression effect for the conductance current at 90°C becomes weakened due to limited trap ***,the deeper energy level introduced by GA suppresses the conductance current and improves the electrical strength of XLPE at 90°C more *** co-grafting,the conductance current of XLPE in a wide range temperature can be significantly reduced,especially for the temperature dependence of conductance current,which is beneficial to suppress the field strength *** results of thermally stimulated current and molecular simulation show that the polar groups of two monomers introduce deep charge traps in *** co-grafting system ensures the rationality of the crosslinking reaction kinetics and does not affect the cable manufacturing.
In the field of imaging, the image resolution is required to be higher. There is always a contradiction between the sensitivity and resolution of the seeker in the infrared guidance system. This work uses the rosette ...
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1 Introduction On-device deep learning(DL)on mobile and embedded IoT devices drives various applications[1]like robotics image recognition[2]and drone swarm classification[3].Efficient local data processing preserves ...
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1 Introduction On-device deep learning(DL)on mobile and embedded IoT devices drives various applications[1]like robotics image recognition[2]and drone swarm classification[3].Efficient local data processing preserves privacy,enhances responsiveness,and saves ***,current ondevice DL relies on predefined patterns,leading to accuracy and efficiency *** is difficult to provide feedback on data processing performance during the data acquisition stage,as processing typically occurs after data acquisition.
The integration of machine learning and electrocatalysis presents nota ble advancements in designing and predicting the performance of chiral materials for hydrogen evolution reactions(HER).This study utilizes theoret...
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The integration of machine learning and electrocatalysis presents nota ble advancements in designing and predicting the performance of chiral materials for hydrogen evolution reactions(HER).This study utilizes theoretical calculations and machine learning techniques to assess the HER performance of both chiral and achiral M-N-SWCNTs(M=In,Bi,and Sb)single-atom catalysts(SACs).The stability preferences of metal atoms are dependent on chirality when interacting with chiral *** HER activity of the right-handed In-N-SWCNT is 5.71 times greater than its achiral counterpart,whereas the left-handed In-N-SWCNT exhibits a 5.12-fold *** calculated hydrogen adsorption free energy for the right-handed In-N-SWCNT reaches as low as-0.02 *** enhancement is attributed to the symmetry breaking in spin density distribution,transitioning from C_(2V)in achiral SACs to C_(2)in chiral SACs,which facilitates active site transfer and enhances local spin ***-handed M-N-SWCNTs exhibit superiorα-electron separation and transport efficiency relative to left-handed variants,owing to the chiral induced spin selectivity(CISS)effect,with spin-upα-electron density reaching 3.43×10^(-3)e/Bohr^(3)at active *** learning provides deeper insights,revealing that the interplay of weak spatial electronic effects and appropriate curvature-chirality effects significantly enhances HER performance.A weaker spatial electronic effect correlates with higher HER activity,larger exchange current density,and higher turnover *** curvature-chirality effect undersco res the influence of intrinsic structures on HER *** findings offer critical insights into the role of chirality in electrocatalysis and propose innovative approaches for optimizing HER through chirality.
Accelerating the breaking of the nitrogen nonpolar bond(N≡N)is an important factor to improve the effi ciency of the electro-catalytic nitrogen reduction reaction(e-NRR).In this work,polyoxometalates-derived FeMo-bas...
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Accelerating the breaking of the nitrogen nonpolar bond(N≡N)is an important factor to improve the effi ciency of the electro-catalytic nitrogen reduction reaction(e-NRR).In this work,polyoxometalates-derived FeMo-based ternary oxide materials MoO_(2)-Mo_(4)O_(11)-FeMoO_(4)@X(abbreviated as MoFeO@X,X represents the synthesis temperature of 650,750 and 850℃)were designed and synthesized for e-NRR under ambient *** scanning electron microscopy images of MoFeO@750 show an ellipsoidal-like structure(0.86×0.6μm).The relatively large specifi c surface area,formation of multiple interfaces,together with the synergistic eff ect of iron and molybdenum bimetals,would make MoFeO@X catalyst more easily absorb and activate N_(2)in the ***,the synthesized MoFeO@750 shows an optimal NH_(3)production rate of 16.57μg·h^(−1)·mg cat.^(−1)and Faradaic effi ciency of 12.33%at−0.3 V versus reversible hydrogen electrode(ν***),with outstanding electrochemical and structural stability.
Spike camera is a retina-inspired neuromorphic camera which can capture dynamic scenes of high-speed motion by firing a continuous stream of spikes at an extremely high temporal resolution. The limitation in the curre...
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Unmanned sailboats are driven only by wind, making them good platforms for the synchronous observation of air-sea interfaces over a large range. Compared with traditional unmanned ships, the unmanned sailboat involves...
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Unmanned sailboats are driven only by wind, making them good platforms for the synchronous observation of air-sea interfaces over a large range. Compared with traditional unmanned ships, the unmanned sailboat involves simultaneous sail and rudder control for path tracking in unpredictable marine environments. The system is characterized by strong coupling and nonlinearity, creating challenges for the design of controllers. This paper combines line-of-sight (LOS) guidance with the introduction of a sideslip angle observer and model predictive control. A high-precision path tracking strategy suitable for cooperative sail and rudder control for unmanned sailboats is proposed. First, considering the lateral error easily caused by the large sideslip angle of sailboats, a full-path fixed-time guidance strategy with double fixed-time sideslip angle observers (DFSO) is proposed. Second, different from the previous strategy of decoupling the sail and rudder to control the speed and heading, the proposed cooperative control framework uses Lyapunov-based model predictive control (LMPC). The sailing speed and heading angle are both accounted for in the objective function, and the stability is verified by Lyapunov theory. Finally, the feasibility and superiority of this proposed method are confirmed by numerical simulation experiments involving the path tracking of a four degree of freedom sailboat model integrated with wind and waves in an ocean environment. IEEE
This research focuses on improving the Harris’Hawks Optimization algorithm(HHO)by tackling several of its shortcomings,including insufficient population diversity,an imbalance in exploration ***,and a lack of thoroug...
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This research focuses on improving the Harris’Hawks Optimization algorithm(HHO)by tackling several of its shortcomings,including insufficient population diversity,an imbalance in exploration ***,and a lack of thorough exploitation *** tackle these shortcomings,it proposes enhancements from three distinct perspectives:an initialization technique for populations grounded in opposition-based learning,a strategy for updating escape energy factors to improve the equilibrium between exploitation and exploration,and a comprehensive exploitation approach that utilizes variable neighborhood search along with mutation *** effectiveness of the Improved Harris Hawks Optimization algorithm(IHHO)is assessed by comparing it to five leading algorithms across 23 benchmark test *** findings indicate that the IHHO surpasses several contemporary algorithms its problem-solving ***,this paper introduces a feature selection method leveraging the IHHO algorithm(IHHO-FS)to address challenges such as low efficiency in feature selection and high computational costs(time to find the optimal feature combination and model response time)associated with high-dimensional *** analyses between IHHO-FS and six other advanced feature selection methods are conducted across eight *** results demonstrate that IHHO-FS significantly reduces the computational costs associated with classification models by lowering data dimensionality,while also enhancing the efficiency of feature ***,IHHO-FS shows strong competitiveness relative to numerous algorithms.
Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inher...
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Matrix minimization techniques that employ the nuclear norm have gained recognition for their applicability in tasks like image inpainting, clustering, classification, and reconstruction. However, they come with inherent biases and computational burdens, especially when used to relax the rank function, making them less effective and efficient in real-world scenarios. To address these challenges, our research focuses on generalized nonconvex rank regularization problems in robust matrix completion, low-rank representation, and robust matrix regression. We introduce innovative approaches for effective and efficient low-rank matrix learning, grounded in generalized nonconvex rank relaxations inspired by various substitutes for the ?0-norm relaxed functions. These relaxations allow us to more accurately capture low-rank structures. Our optimization strategy employs a nonconvex and multi-variable alternating direction method of multipliers, backed by rigorous theoretical analysis for complexity and *** algorithm iteratively updates blocks of variables, ensuring efficient convergence. Additionally, we incorporate the randomized singular value decomposition technique and/or other acceleration strategies to enhance the computational efficiency of our approach, particularly for large-scale constrained minimization problems. In conclusion, our experimental results across a variety of image vision-related application tasks unequivocally demonstrate the superiority of our proposed methodologies in terms of both efficacy and efficiency when compared to most other related learning methods.
In pursuit of effective adsorption materials for malodorous gases such as H_(2)S and to broaden the utilization avenues of lignin waste,this study employed the direct pyrolysis method to synthesize three types of alka...
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In pursuit of effective adsorption materials for malodorous gases such as H_(2)S and to broaden the utilization avenues of lignin waste,this study employed the direct pyrolysis method to synthesize three types of alkali lignin graphitized carbons,namely C-800,KC-700,and *** them,KEC-700 exhibits a high specific surface area of 1672.9 m^(2)/g,significantly superior H_(2)S adsorption performance compared to other materials,an adsorption breakthrough time of up to 220 min,and a sulfur capacity of 67.1 mg/*** analysis showed that the more oxygen-containing functional groups of lignin charcoal and the larger specific surface area facilitated the adsorption of H_(2)*** reaching adsorption saturation,the degree of graphitization of lignin carbon *** H_(2)S adsorption products primarily manifest as elemental sulfur and sulfate within the pores of lignin carbon measuring less than 2 *** thermal regeneration,the charcoal effectively eliminates the elemental sulfur adsorption ***,sulfate removal proved unsatisfactory,as the adsorption efficiency of KEC-700 following two thermal regenerations was approximately 41%of that observed for fresh samples.
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