Lithium-sulfur (Li-S) batteries are considered appealing power sources due to their high theoretical energy density (2600 Wh kg-1), low cost, and environmental friendliness. However, their widespread applicability is ...
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Lithium-sulfur (Li-S) batteries are considered appealing power sources due to their high theoretical energy density (2600 Wh kg-1), low cost, and environmental friendliness. However, their widespread applicability is restricted by two scientific problems: sluggish sulfur reaction kinetics and severe polysulfide shuttle effects. Multifarious strategies have been developed to overcome these two obstacles and achieve high sulfur utilization and capacity retention. Among these strategies, the introduction of catalytic materials into the Li-S battery system can greatly accelerate sulfur conversion and effectively inhibit the polysulfide shuttle effects. Herein, we have comprehensively reviewed the recent progress of catalytic engineering for polysulfide conversion in high-performance lithium-sulfur batteries. First, various catalytic materials serve as sulfur hosts, functionalized separators, and electrolyte additives;the mechanisms by which these materials promote the conversion of polysulfides in Li-S batteries have been systematically summarized. The relationship of structure, preparation, property, advantages, and limitations of these catalytic materials are comprehensively presented. Subsequently, the advanced characterization techniques of these catalytic processes are discussed, shedding light on the fundamental understanding of catalytic effects for improved electrochemical performance. Furthermore, future design tactics for high-performance Li-S batteries are discussed.
In recent years,Deep Learning(DL)technique has been widely used in Internet of Things(IoT)and Industrial Internet of Things(IIoT)for edge computing,and achieved good *** more and more studies have shown the vulnerabil...
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In recent years,Deep Learning(DL)technique has been widely used in Internet of Things(IoT)and Industrial Internet of Things(IIoT)for edge computing,and achieved good *** more and more studies have shown the vulnerability of neural ***,it is important to test the robustness and vulnerability of neural *** specifically,inspired by layer-wise relevance propagation and neural network verification,we propose a novel measurement of sensitive neurons and important neurons,and propose a novel neuron coverage criterion for robustness *** on the novel criterion,we design a novel testing sample generation method,named DeepSI,which involves definitions of sensitive neurons and important ***,we construct sensitive-decision paths of the neural network through selecting sensitive neurons and important ***,we verify our idea by setting up several experiments,then results show our proposed method achieves superior performances.
This paper proposes a method of impulse current generator modulated DC arc by combining the advantages of pulse and the RF to solve the low electron energy problem of direct current *** experimental analyzing the elec...
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This paper proposes a method of impulse current generator modulated DC arc by combining the advantages of pulse and the RF to solve the low electron energy problem of direct current *** experimental analyzing the electrical,spectral,and optical characteristics of the arc,the effect of impulse current generator(ICG)on improving electron energy is *** results show that the ICG consumes more energy to enhance the strength of arc discharge,and therefore electron energy is increased in a microsecond *** addition,it is found that the electron energy of the arc discharge can be adjusted by varying inductance,capacitance,and discharge tube:increasing the inductance or capacitance can increase the electron energy firstly and then decrease *** adjusting the three adjustable components,adjusting the inductor is the most effective method,followed by adjusting the capacitor,and adjusting the repetition frequency has the least *** reason is discussed,and it is believed that the results are related to leakage inductance and distributed capacitance.
Precise polyp segmentation is vital for the early diagnosis and prevention of colorectal cancer(CRC)in clinical ***,due to scale variation and blurry polyp boundaries,it is still a challenging task to achieve satisfac...
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Precise polyp segmentation is vital for the early diagnosis and prevention of colorectal cancer(CRC)in clinical ***,due to scale variation and blurry polyp boundaries,it is still a challenging task to achieve satisfactory segmentation performance with different scales and *** this study,we present a novel edge-aware feature aggregation network(EFA-Net)for polyp segmentation,which can fully make use of cross-level and multi-scale features to enhance the performance of polyp ***,we first present an edge-aware guidance module(EGM)to combine the low-level features with the high-level features to learn an edge-enhanced feature,which is incorporated into each decoder unit using a layer-by-layer ***,a scale-aware convolution module(SCM)is proposed to learn scale-aware features by using dilated convolutions with different ratios,in order to effectively deal with scale ***,a cross-level fusion module(CFM)is proposed to effectively integrate the cross-level features,which can exploit the local and global contextual ***,the outputs of CFMs are adaptively weighted by using the learned edge-aware feature,which are then used to produce multiple side-out segmentation *** results on five widely adopted colonoscopy datasets show that our EFA-Net outperforms state-of-the-art polyp segmentation methods in terms of generalization and *** implementation code and segmentation maps will be publicly at https://***/taozh2017/EFANet.
In this paper,a robust and consistent COVID-19 emergency decision-making approach is proposed based on q-rung linear diophantine fuzzy set(q-RLDFS),differential evolutionary(DE)optimization principles,and evidential r...
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In this paper,a robust and consistent COVID-19 emergency decision-making approach is proposed based on q-rung linear diophantine fuzzy set(q-RLDFS),differential evolutionary(DE)optimization principles,and evidential reasoning(ER)*** proposed approach uses q-RLDFS in order to represent the evaluating values of the alternatives corresponding to the *** optimization is used to obtain the optimal weights of the attributes,and ER methodology is used to compute the aggregated q-rung linear diophantine fuzzy values(q-RLDFVs)of each *** the score values of alternatives are computed based on the aggregated *** alternative with the maximum score value is selected as a better *** applicability of the proposed approach has been illustrated in COVID-19 emergency decision-making system and sustainable energy planning ***,we have validated the proposed approach with a numerical ***,a comparative study is provided with the existing models,where the proposed approach is found to be robust to perform better and consistent in uncertain environments.
Background Algae play important roles in urban river ecosystems and are the cornerstones of most water quality monitoring programs. Thus, a better understanding of algal community dynamics is needed to support sustain...
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Background Algae play important roles in urban river ecosystems and are the cornerstones of most water quality monitoring programs. Thus, a better understanding of algal community dynamics is needed to support sustainable management of water resources in urban *** In this study, we quantified the seasonal variations in planktonic and periphytic algal community structure in the highly urban Fenhe River and identified environmental factors affecting algal community structure and diversity. We monitored planktonic(drifting) and periphytic(attached) algal communities in the Taiyuan section of the Fenhe River over one year. The results indicated that Cyanophyta was the dominant phylum in both communities, followed by Bacillariophyta and Chlorophyta. Significant differences were observed in the composition of the planktonic and periphytic algal communities. In particular, the periphytic algal community was more diverse than the planktonic community. Water temperature and pH were the main environmental factors affecting planktonic and periphytic algal community structure, respectively, while nutrients were the most significant factor affecting planktonic and periphytic algal diversity. Ecological modeling indicated that the variations in the algal communities of the Fenhe River are mainly driven by stochastic processes. A co-occurrence network developed for the communities displayed positive interactions between the planktonic and periphytic *** These findings deepen our understanding of the seasonal interaction between planktonic and periphytic algae and the driving factors affecting community structure in the Fenhe River. They also provide a theoretical basis for the managing and protecting water resources in urban river ecosystems.
A backward wave oscillator with parallel multiple beams and multi-pin slow-wave structure(SWS)operating at the frequency above 500 GHz is studied. Both the cold-cavity dispersion characteristics and CST Particle Studi...
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A backward wave oscillator with parallel multiple beams and multi-pin slow-wave structure(SWS)operating at the frequency above 500 GHz is studied. Both the cold-cavity dispersion characteristics and CST Particle Studio simulation results reveal that there are obvious mode competition problems in this kind of terahertz *** that the structure of the multi-pin SWS is similar to that of two-dimensional photonic crystals, we introduce the defects of photonic crystal with the property of filtering into the SWS to suppress high-order ***, a detailed study of the effect of suppressing higher-order modes is carried out in the process of changing location and arrangement pattern of the point defects. The stable, single-mode operation of the terahertz source is realized. The simulation results show that the ratio of the output peak power of the higher-order modes to that of the fundamental mode is less than 1.9%. Also, the source can provide the output peak power of 44.8 m W at the frequency of 502.2 GHz in the case of low beam voltage of 4.7 kV.
In order to clarify the effect of rare earth Gd on the microstructure evolution and deformation behavior of 7075 aluminum alloy during hot compression,uniaxial compression tests of Al-Zn-Mg-Cu-0.5%Gd were conducted at...
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In order to clarify the effect of rare earth Gd on the microstructure evolution and deformation behavior of 7075 aluminum alloy during hot compression,uniaxial compression tests of Al-Zn-Mg-Cu-0.5%Gd were conducted at strain rates of 0.001,0.01,0.1,and 1 s^(-1)with the temperatures ranging from 350 to 450℃.The microstructural evolution during deformation was characterized using optical microscopy and electron backscatter diffraction(EBSD)*** experimental results indicate that the addition of the rare earth element Gd significantly increases the peak flow stress and thermal activation energy of the *** to the pinning effect of rare earth phases,dislocation movement is hindered,leading to an increased level of work hardening in the ***,the dynamic recrystallization of the alloy is *** a high Z(Zener-Hollomon parameter)values,recrystallization occurs in the form of DDRX(Discontinuous Dynamic Recrystallization),making it easier to nucleate at grain *** the Z value decreases gradually,the recrystallization mechanism transitions from discontinuous dynamic recrystallization(DDRX)to continuous dynamic recrystallization(CDRX).At a low Z values with the strain rate of 0.001 s^(-1),the inhibitory effect of rare earths weakens,resulting in a comparable recrystallization ratio between Al-Zn-Mg-Cu-Gd alloy and 7075 aluminum ***,the average grain size of the aluminum alloy with Gd addition is only half that of 7075 *** addition of Gd provides Orowan and substructure strengthening for the alloy,which greatly improves the work-hardening of the alloy compared with 7075 aluminum alloy and improves the strength of the alloy.
The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this ***,a comprehensive nonlinear mathematical model that encompasses both mat...
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The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this ***,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is *** to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched *** from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output ***,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory *** mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is ***,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact *** analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop ***,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is ***,the algorithm’s efficacy is validated through comparative experiments.
The exponential growth of IoT devices has led to the proposal of edge computing for data processing. The decentralized nature of edge computing servers and IoT devices makes blockchain ideal for connecting IoT users a...
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