Transformer-based models have facilitated significant advances in object detection.However,their extensive computational consumption and suboptimal detection of dense small objects curtail their applicability in unman...Transformer-based models have facilitated significant advances in object detection.However,their extensive computational consumption and suboptimal detection of dense small objects curtail their applicability in unmanned aerial vehicle(UAV)imagery.Addressing these limitations,we propose a hybrid transformer-based detector,H-DETR,and enhance it for dense small objects,leading to an accurate and efficient model.Firstly,we introduce a hybrid transformer encoder,which integrates a convolutional neural network-based cross-scale fusion module with the original encoder to handle multi-scale feature sequences more efficiently.Furthermore,we propose two novel strategies to enhance detection performance without incurring additional inference computation.Query filter is designed to cope with the dense clustering inherent in drone-captured images by counteracting similar queries with a training-aware non-maximum suppression.Adversarial denoising learning is a novel enhancement method inspired by adversarial learning,which improves the detection of numerous small targets by counteracting the effects of artificial spatial and semantic noise.Extensive experiments on the VisDrone and UAVDT datasets substantiate the effectiveness of our approach,achieving a significant improvement in accuracy with a reduction in computational complexity.Our method achieves 31.9%and 21.1%AP on the VisDrone and UAVDT datasets,respectively,and has a faster inference speed,making it a competitive model in UAV image object detection.展开更多
A considerable efficiency gap exists between large-area perovskite solar modules and small-area perovskite solar cells.The control of forming uniform and large-area film and perovskite crystallization is still the mai...A considerable efficiency gap exists between large-area perovskite solar modules and small-area perovskite solar cells.The control of forming uniform and large-area film and perovskite crystallization is still the main obstacle restricting the efficiency of PSMs.In this work,we adopted a solid-liquid two-step film formation technique,which involved the evaporation of a lead iodide film and blade coating of an organic ammonium halide solution to prepare perovskite films.This method possesses the advantages of integrating vapor deposition and solution methods,which could apply to substrates with different roughness and avoid using toxic solvents to achieve a more uniform,large-area perovskite film.Furthermore,modification of the NiO_(x)/perovskite buried interface and introduction of Urea additives were utilized to reduce interface recombination and regulate perovskite crystallization.As a result,a large-area perovskite film possessing larger grains,fewer pinholes,and reduced defects could be achieved.The inverted PSM with an active area of 61.56 cm^(2)(10×10 cm^(2)substrate)achieved a champion power conversion efficiency of 20.56%and significantly improved stability.This method suggests an innovative approach to resolving the uniformity issue associated with large-area film fabrication.展开更多
Integrated water and fertilizer management is important for promoting sustainable development of facility agriculture,and biochar plays an important role in guaranteeing food production,as well as alleviating water sh...Integrated water and fertilizer management is important for promoting sustainable development of facility agriculture,and biochar plays an important role in guaranteeing food production,as well as alleviating water shortages and the overuse of fertilizers.The field experiment had twelve treatments and a control(CK)trial including two irrigation amounts(I1,100%ETm;I2,60%ETm;where ETm is the maximum evapotranspiration),two nitrogen applications(N1,360 kg ha^(−1);N2,120 kg ha^(−1))and three biochar application levels(B1,60 t ha^(−1);B_(2),30 t ha^(−1)and B3,0 t ha^(−1)).A multi-objective synergistic irrigation-nitrogen-biochar application system for improving tomato yield,quality,water and nitrogen use efficiency,and greenhouse emissions was developed by integrating the techniques of experimentation and optimization.First,a coupled irrigation-nitrogen-biochar plot experiment was arranged.Then,tomato yield and fruit quality parameters were determined experimentally to establish the response relationships between irrigation-nitrogen-biochar dosage and yield,comprehensive quality of tomatoes(TCQ),irrigation water use efficiency(IWUE),partial factor productivity of nitrogen(PFPN),and net greenhouse gas emissions(NGE).Finally,a multi-objective dynamic optimization regulation model of irrigation-nitrogen-biochar resource allocation at different growth stages of tomato was constructed which was solved by the fuzzy programming method.The results showed that the application of irrigation and nitrogen to biochar promoted increase in yield,IWUE and PFPN,while it had an inhibitory effect on NGE.In addition,the optimal allocation amounts of water and fertilizer were different under different scenarios.The yield of the S1 scenario increased by 8.31%compared to the B_(1)I_(1)N_(2) treatment;TCQ of the S2 scenario increased by 5.14%compared to the B_(2)I_(2)N_(1) treatment;IWUE of the S3 scenario increased by 10.01%compared to the B1I2N2 treatment;PFPN of the S4 scenario increased by 9.35%compared to the B_(1)I_(1)N_(2) treatment;and NGE of the S5 scenario decreased by 11.23%compared to the B_(2)I1N1 treatment.The optimization model showed that the coordination of multiple objectives considering yield,TCQ,IWUE,PFPN,and NGE increased on average from 4.44 to 69.02%compared to each treatment when the irrigation-nitrogen-biochar dosage was 205.18 mm,186 kg ha^(−1)and 43.31 t ha^(−1),respectively.This study provides a guiding basis for the sustainable management of water and fertilizer in greenhouse tomato production under drip irrigation fertilization conditions.展开更多
The deformation control of surrounding rock in gobside roadway with thick and hard roof poses a significant challenge to the safety and efficiency of coal mining.To address this issue,a novel approach combining direct...The deformation control of surrounding rock in gobside roadway with thick and hard roof poses a significant challenge to the safety and efficiency of coal mining.To address this issue,a novel approach combining directional and non-directional blasting techniques,known as combined blasting,was proposed.This study focuses on the experimental investigation of the proposed method in the 122108 working face in Caojiatan Coal Mine as the engineering background.The initial phase of the study involves physical model experiments to reveal the underlying mechanisms of combined blasting for protecting gob-side roadway with thick and hard roof.The results demonstrate that this approach effectively accelerates the collapse of thick and hard roofs,enhances the fragmentation and expansion coefficient of gangue,facilitates the filling of the goaf with gangue,and provides support to the overlying strata,thus reducing the subsidence of the overlying strata above the goaf.Additionally,the method involves cutting the main roof into shorter beams to decrease the stress and disrupt stress transmission pathways.Subsequent numerical simulations were conducted to corroborate the findings of the physical model experiments,thus validating the accuracy of the experimental results.Furthermore,field engineering experiments were performed,affirming the efficacy of the combined blasting method in mitigating the deformation of surrounding rock and achieving the desired protection of the gob-side roadway.展开更多
Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinfor...Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinforce-ment learning(DRL)theory and an improved Multi-Agent Deep Deterministic Policy Gradient(MADDPG-D2)algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA.The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm,and considers the introduction of a double noise mechanism to increase the action exploration space in the early stage of the algorithm,and the introduction of a double experience pool to improve the data utilization rate;at the same time,in order to accelerate the training speed and efficiency of the agents,and to solve the cold-start problem of the training,the a priori knowledge technology is applied to the training of the algorithm.Finally,the MADDPG-D2 algorithm is compared and analyzed based on the digital battlefield of ground and air confrontation.The experimental results show that the agents trained by the MADDPG-D2 algorithm have higher win rates and average rewards,can utilize the resources more reasonably,and better solve the problem of the traditional single agent algorithms facing the difficulty of solving the problem in the high-dimensional decision space.The MADDPG-D2 algorithm based on multi-agent architecture proposed in this paper has certain superiority and rationality in DTA.展开更多
Excessive carbon emissions have resulted in the greenhouse effect, causing considerable global climate change. Marine carbon storage has emerged as a crucial approach to addressing climate change. The Qiantang Sag(QTS...Excessive carbon emissions have resulted in the greenhouse effect, causing considerable global climate change. Marine carbon storage has emerged as a crucial approach to addressing climate change. The Qiantang Sag(QTS) in the East China Sea Shelf Basin, characterized by its extensive area, thick sedimentary strata, and optimal depth, presents distinct geological advantages for carbon dioxide(CO_(2)) storage. Focusing on the lower section of the Shimentan Formation in the Upper Cretaceous of the QTS, this study integrates seismic interpretation and drilling data with core and thin-section analysis. We reveal the vertical variation characteristics of the strata by providing a detailed stratigraphic description. We use petrophysical data to reveal the development characteristics of high-quality carbon-storage layers and favorable reservoircaprock combinations, thereby evaluating the geological conditions for CO_(2) storage in various stratigraphic sections. We identify Layer B of the lower Shimentan Formation as the most advantageous stratum for marine CO_(2) storage. Furthermore, we analyze the carbon emission trends in the adjacent Yangtze River Delta region. Considering the characteristics of the source and sink areas, we suggest a strong correlation between the carbon emission sources of the Yangtze River Delta and the CO_(2) storage area of the QTS, making the latter a priority area for conducting experiments on marine CO_(2) storage.展开更多
The Pacific oyster Crassostrea gigas,one of the most exploited molluscs in the world,has suffered from massive mortality in recent decades,and the occurrence mechanisms have not been well characterized.In this study,t...The Pacific oyster Crassostrea gigas,one of the most exploited molluscs in the world,has suffered from massive mortality in recent decades,and the occurrence mechanisms have not been well characterized.In this study,to reveal the relationship of associated microbiota to the fitness of oysters,temporal dynamics of microbiota in the gill,hemolymph,and hepatopancreas of C.gigas during April 2018-January 2019 were investigated by 16 S rRNA gene sequencing.The microbiota in C.gigas exhibited tissue heterogeneity,of which Spirochaetaceae was dominant in the gill and hemolymph while Mycoplasmataceae enriched in the hepatopancreas.Co-occurrence network demonstrated that the gill microbiota exhibited higher inter-taxon connectivity while the hemolymph microbiota had more modules.The richness(Chao 1 index)and diversity(Shannon index)of microbial community in each tissue showed no significant seasonal variations,except for the hepatopancreas having a higher richness in the autumn.Similarly,beta diversity analysis indicated a relatively stable microbiota in each tissue during the sampling period,showing relative abundance of the dominant taxa exhibiting temporal dynamics.Results indicate that the microbial community in C.gigas showed a tissue-specific stability with temporal dynamics in the composition,which might be essential for the tissue functioning and environmental adaption in oysters.This work provides a baseline microbiota in C.gigas and is helpful for the understanding of host-microbiota interaction in oysters.展开更多
Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeh...Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeholders.This study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China.Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change.The major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change decisions.Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)model.Simultaneously,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion.An agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use conversion.This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services.The results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.展开更多
As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is be...As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.展开更多
The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly...The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly focus on objectives,treating decision variables as a total variable to solve the problem without consideringthe critical role of decision variables in objective optimization.As seen,a variety of decision variable groupingalgorithms have been proposed.However,these algorithms are relatively broad for the changes of most decisionvariables in the evolution process and are time-consuming in the process of finding the Pareto frontier.To solvethese problems,a multi-objective optimization algorithm for grouping decision variables based on extreme pointPareto frontier(MOEA-DV/EPF)is proposed.This algorithm adopts a preprocessing rule to solve the Paretooptimal solution set of extreme points generated by simultaneous evolution in various target directions,obtainsthe basic Pareto front surface to determine the convergence effect,and analyzes the convergence and distributioneffects of decision variables.In the later stages of algorithm optimization,different mutation strategies are adoptedaccording to the nature of the decision variables to speed up the rate of evolution to obtain excellent individuals,thusenhancing the performance of the algorithm.Evaluation validation of the test functions shows that this algorithmcan solve the multi-objective optimization problem more efficiently.展开更多
Nowadays,with the rapid development of industrial Internet technology,on the one hand,advanced industrial control systems(ICS)have improved industrial production efficiency.However,there are more and more cyber-attack...Nowadays,with the rapid development of industrial Internet technology,on the one hand,advanced industrial control systems(ICS)have improved industrial production efficiency.However,there are more and more cyber-attacks targeting industrial control systems.To ensure the security of industrial networks,intrusion detection systems have been widely used in industrial control systems,and deep neural networks have always been an effective method for identifying cyber attacks.Current intrusion detection methods still suffer from low accuracy and a high false alarm rate.Therefore,it is important to build a more efficient intrusion detection model.This paper proposes a hybrid deep learning intrusion detection method based on convolutional neural networks and bidirectional long short-term memory neural networks(CNN-BiLSTM).To address the issue of imbalanced data within the dataset and improve the model’s detection capabilities,the Synthetic Minority Over-sampling Technique-Edited Nearest Neighbors(SMOTE-ENN)algorithm is applied in the preprocessing phase.This algorithm is employed to generate synthetic instances for the minority class,simultaneously mitigating the impact of noise in the majority class.This approach aims to create a more equitable distribution of classes,thereby enhancing the model’s ability to effectively identify patterns in both minority and majority classes.In the experimental phase,the detection performance of the method is verified using two data sets.Experimental results show that the accuracy rate on the CICIDS-2017 data set reaches 97.7%.On the natural gas pipeline dataset collected by Lan Turnipseed from Mississippi State University in the United States,the accuracy rate also reaches 85.5%.展开更多
Optical telescopes are an important tool for acquiring optical information about distant objects,and resolution is an important indicator that measures the ability to observe object details.However,due to the effects ...Optical telescopes are an important tool for acquiring optical information about distant objects,and resolution is an important indicator that measures the ability to observe object details.However,due to the effects of system aberration,atmospheric seeing,and other factors,the observed image of ground-based telescopes is often degraded,resulting in reduced resolution.This paper proposes an optical-neural network joint optimization method to improve the resolution of the observed image by co-optimizing the point-spread function(PSF)of the telescopic system and the image super-resolution(SR)network.To improve the speed of image reconstruction,we designed a generative adversarial net(LCR-GAN)with light parameters,which is much faster than the latest unsupervised networks.To reconstruct the PSF trained by the network in the optical path,a phase mask is introduced.It improves the image reconstruction effect of LCR-GAN by reconstructing the PSF that best matches the network.The results of simulation and verification experiments show that compared with the pure deep learning method,the SR image reconstructed by this method is rich in detail and it is easier to distinguish stars or stripes.展开更多
In order to deal with the special spatio-temporal environmental changes encountered in the process of open-cast mining,taking Huolinhe No.1 Open-cast Mine as the research object,this paper studied its typical problems...In order to deal with the special spatio-temporal environmental changes encountered in the process of open-cast mining,taking Huolinhe No.1 Open-cast Mine as the research object,this paper studied its typical problems in river reconstruction and cultural relics protection.The study focused on eight key core aspects,including the design optimization of the spatial layout of the mining area,the accurate estimation of the mineral resources reserves,the scientific theoretical demonstration of the mining scale,the fine analysis and calculation of the stripping ratio,the comprehensive consideration of the transport distance and efficiency,the accurate judgment of the best time for the implementation of the transformation,the analysis and evaluation of the slope stability,and the overall planning of the production system.The results show that the extracted problem-solving strategies and scheme system for special mining conditions can not only provide specific and practical guidance for Huolinhe No.1 Open-cast Mine,but also serve as a valuable reference and practical reference for other open-cast mine enterprises facing similar challenges.展开更多
This review summarizes the current state of knowledge regarding the role of endothelial dysfunction in the pathogenesis of early and delayed intestinal radiation toxicity and discusses various endothelial-oriented int...This review summarizes the current state of knowledge regarding the role of endothelial dysfunction in the pathogenesis of early and delayed intestinal radiation toxicity and discusses various endothelial-oriented interventions aimed at reducing the risk of radiation enteropathy. Studies published in the biomedical literature during the past four decades and cited in PubMed, as well as clinical and laboratory data from our own research program are reviewed. The risk of injury to normal tissues limits the cancer cure rates that can be achieved with radiation therapy. During treatment of abdominal and pelvic tumors, the intestine is frequently a major close-limiting factor. Microvascular injury is a prominent feature of both early （inflammatory）, as well as delayed （fibroproliferative） radiation injuries in the intestine and in many other normal tissues. Evidence from our and other laboratories suggests that endothelial dysfunction, notably a deficiency of endothelial thrombomodulin, plays a key role in the pathogenesis of these radiation responses. Deficient levels of thrombomodulin cause loss of vascular thromboresistance, excessive activation of cellular thrombin receptors by thrombin, and insufficient activation of protein C, a plasma protein with anticoagulant, anti-inflammatory, and cytoprotective properties. These changes are presumed to be critically involved in many aspects of early intestinal radiation toxicity and may sustain the fibroproliferative processes that lead to delayed intestinal dysfunction, fibrosis, and clinical complications. In conclusion, injury of vascular endothelium is important in the pathogenesis of the intestinal radiation response. Endothelial-oriented interventions are appealing strategies to prevent or treat normal tissue toxicity associated with radiation treatment of cancer.展开更多
Phase change materials(PCMs)are expected to achieve dual-mode thermal management for heating and cooling Li-ion batteries(LIBs)according to real-time thermal conditions,guaranteeing the reliable operation of LIBs in b...Phase change materials(PCMs)are expected to achieve dual-mode thermal management for heating and cooling Li-ion batteries(LIBs)according to real-time thermal conditions,guaranteeing the reliable operation of LIBs in both cold and hot environments.Herein,we report a liquid metal(LM)modified polyethylene glycol/LM/boron nitride PCM,capable of dual-mode thermal managing the LIBs through photothermal effect and passive thermal conduction.Its geometrical conformation and thermal pathways fabricated through ice-template strategy are conformable to the LIB’s structure and heat-conduction characteristic.Typically,soft and deformable LMs are modified on the boron nitride surface,serving as thermal bridges to reduce the contact thermal resistance among adjacent fillers to realize high thermal conductivity of 8.8 and 7.6 W m^(−1) K^(−1) in the vertical and in-plane directions,respectively.In addition,LM with excellent photothermal performance provides the PCM with efficient battery heating capability if employing a controllable lighting system.As a proof-of-concept,this PCM is manifested to heat battery to an appropriate temperature range in a cold environment and lower the working temperature of the LIBs by more than 10℃ at high charging/discharging rate,opening opportunities for LIBs with durable working performance and evitable risk of thermal runaway.展开更多
Lithium-sulfur batteries(LSBs) are regarded as a competitive next-generation energy storage device.However, their practical performance is seriously restricted due to the undesired polysulfides shuttling.Herein, a mul...Lithium-sulfur batteries(LSBs) are regarded as a competitive next-generation energy storage device.However, their practical performance is seriously restricted due to the undesired polysulfides shuttling.Herein, a multifunctional interlayer composed of paper-derived carbon(PC) scaffold, Fe3O4 nanoparticles,graphene, and graphite sheets is designed for applications in LSBs. The porous PC skeleton formed by the interweaving long-fibers not only facilitates fast transfer of Li ions and electrons but also provides a physical barrier for the polysulfide shuttling. The secondary Fe3O4@graphene component can reduce the polarization, boost the attachment of polysulfides, and promote the charging-discharging kinetics. The outer graphitic sheets layers benefit the interfacial electrochemistry and the utilization of S-containing species.The efficient obstruction of polysulfides diffusion is further witnessed via in situ ultraviolet-visible characterization and first-principles simulations. When 73% sulfur/commercial acetylene black is used as the cathode, the cell exhibits excellent capacity retention with high capacities at 0.5 C for 1000 cycles and even up to 10 C for 500 cycles, an ultrahigh rate capability up to 10 C(478 m Ah g-1), and a high arealsulfur loading of 8.05 mg cm-2. The strategy paves the way for developing multifunctional composites for LSBs with superior performance.展开更多
Functional polymer composites(FPCs)have attracted increasing attention in recent decades due to their great potential in delivering a wide range of functionalities.These functionalities are largely determined by funct...Functional polymer composites(FPCs)have attracted increasing attention in recent decades due to their great potential in delivering a wide range of functionalities.These functionalities are largely determined by functional fillers and their network morphology in polymer matrix.In recent years,a large number of studies on morphology control and interfacial modification have been reported,where numerous preparation methods and exciting performance of FPCs have been reported.Despite the fact that these FPCs have many similarities because they are all consisting of functional inorganic fillers and polymer matrices,review on the overall progress of FPCs is still missing,and especially the overall processing strategy for these composites is urgently needed.Herein,a"Toolbox"for the processing of FPCs is proposed to summarize and analyze the overall processing strategies and corresponding morphology evolution for FPCs.From this perspective,the morphological control methods already utilized for various FPCs are systematically reviewed,so that guidelines or even predictions on the processing strategies of various FPCs as well as multi-functional polymer composites could be given.This review should be able to provide interesting insights for the field of FPCs and boost future intelligent design of various FPCs.展开更多
Coral materials can replace concrete aggregates and achieve material self sufficiency for reducing the construction costs of island projects.This paper studies the effects of different mineral admixtures on the proper...Coral materials can replace concrete aggregates and achieve material self sufficiency for reducing the construction costs of island projects.This paper studies the effects of different mineral admixtures on the properties of coral aggregate concrete(CAC).The chloride concentration of CAC after different erosion times is measured using the potentiometric method,and the porosity of the CAC is ca lculated using thermogravimetric and drying methods.The chloride concentration of the CAC presents a two-phases dis tribution.The peak chloride concentration fol-lowed a power function,increasing with the erosion time.The chloride diffusion coefficient of CAC is 7.9%-37.5%larger than that of ordinary aggregate concrete,and the addition of 15% fly ash and 5%silica fume can significantly reduce the chloride diffusion coefficient,with a maximum reduction of 45.0%.The porosity obtained via the thermogravimetric and drying methods is well correlated.The porosity has a strong negative correlation with the compressive strength and a strong positive correlation with the chloride diffusion coefficient.展开更多
A key scientific challenge relating to the threat of invasive plants on agriculture at the region level is to understand their adaptation and evolution in functional traits.Leaf functional traits,related to growth and...A key scientific challenge relating to the threat of invasive plants on agriculture at the region level is to understand their adaptation and evolution in functional traits.Leaf functional traits,related to growth and resource utilization,might lead to adaptation of invasive plants to the geographical barriers(region or elevation).In the field experiment,we discussed the effects of region and elevation on leaf functional traits on invasive plant Erigeron annuus in farmland habitats in China.We compared leaf size,coefficient of variation(CV)of leaf traits,and fluctuating asymmetry(FA)of E.annuus from three regions(east vs.center vs.west)and two leaf types(vegetative vs.reproductive leaf),and from nine elevations(980-2100 m)in the west region of China.Our results indicated region and leaf type influenced leaf functional traits,and leaf size was significantly higher and CV of leaf traits and FA in reproductive leaves were significantly lower in the east region than in the west and center regions.Elevation and leaf type affected leaf functional traits,and leaf size was significantly higher and CV of leaf traits in reproductive leaves were significantly lower in moderate elevation.E.annuus has higher leaf size and developmental stability(lower CV and FA)in the eastern region due to the longer adaptation period.Therefore,leaf functional traits play an important role in the adaptation of different longitudes and elevations.It can also facilitate the understanding of the invasiveness and adaptation of leaf traits of invasive plants in the agricultural ecosystem during their spread process in China.展开更多
Dear Colleagues,This second special edition of the Asian Journal of Urology reviews a number of other important aspects of functional and reconstructive urology.As mentioned in the last special edition,there is a sign...Dear Colleagues,This second special edition of the Asian Journal of Urology reviews a number of other important aspects of functional and reconstructive urology.As mentioned in the last special edition,there is a significant ageing of the population in most countries but also a still limited understanding of the structure,innervation and functional pathophysiology seen as an underlying etiological factor in the development of lower urinary tract dysfunction.The article by Lori A.Birder and colleagues[1]emphasises a number of the aspects of pathophysiology seen in the ageing bladder,with reference to existing experimental research in this field.Clearly,work such as this gives us considerable insight into how we can develop new techniques for the future.展开更多
基金This research was funded by the Natural Science Foundation of Hebei Province(F2021506004).
文摘Transformer-based models have facilitated significant advances in object detection.However,their extensive computational consumption and suboptimal detection of dense small objects curtail their applicability in unmanned aerial vehicle(UAV)imagery.Addressing these limitations,we propose a hybrid transformer-based detector,H-DETR,and enhance it for dense small objects,leading to an accurate and efficient model.Firstly,we introduce a hybrid transformer encoder,which integrates a convolutional neural network-based cross-scale fusion module with the original encoder to handle multi-scale feature sequences more efficiently.Furthermore,we propose two novel strategies to enhance detection performance without incurring additional inference computation.Query filter is designed to cope with the dense clustering inherent in drone-captured images by counteracting similar queries with a training-aware non-maximum suppression.Adversarial denoising learning is a novel enhancement method inspired by adversarial learning,which improves the detection of numerous small targets by counteracting the effects of artificial spatial and semantic noise.Extensive experiments on the VisDrone and UAVDT datasets substantiate the effectiveness of our approach,achieving a significant improvement in accuracy with a reduction in computational complexity.Our method achieves 31.9%and 21.1%AP on the VisDrone and UAVDT datasets,respectively,and has a faster inference speed,making it a competitive model in UAV image object detection.
基金the financial support from Shanxi Province Science and Technology Department(20201101012,202101060301016)the support from the APRC Grant of the City University of Hong Kong(9380086)+5 种基金the TCFS Grant(GHP/018/20SZ)MRP Grant(MRP/040/21X)from the Innovation and Technology Commission of Hong Kongthe Green Tech Fund(202020164)from the Environment and Ecology Bureau of Hong Kongthe GRF grants(11307621,11316422)from the Research Grants Council of Hong KongGuangdong Major Project of Basic and Applied Basic Research(2019B030302007)Guangdong-Hong Kong-Macao Joint Laboratory of Optoelectronic and Magnetic Functional Materials(2019B121205002).
文摘A considerable efficiency gap exists between large-area perovskite solar modules and small-area perovskite solar cells.The control of forming uniform and large-area film and perovskite crystallization is still the main obstacle restricting the efficiency of PSMs.In this work,we adopted a solid-liquid two-step film formation technique,which involved the evaporation of a lead iodide film and blade coating of an organic ammonium halide solution to prepare perovskite films.This method possesses the advantages of integrating vapor deposition and solution methods,which could apply to substrates with different roughness and avoid using toxic solvents to achieve a more uniform,large-area perovskite film.Furthermore,modification of the NiO_(x)/perovskite buried interface and introduction of Urea additives were utilized to reduce interface recombination and regulate perovskite crystallization.As a result,a large-area perovskite film possessing larger grains,fewer pinholes,and reduced defects could be achieved.The inverted PSM with an active area of 61.56 cm^(2)(10×10 cm^(2)substrate)achieved a champion power conversion efficiency of 20.56%and significantly improved stability.This method suggests an innovative approach to resolving the uniformity issue associated with large-area film fabrication.
基金supported by the National Natural Science Foundation of China(52222902 and 52079029)。
文摘Integrated water and fertilizer management is important for promoting sustainable development of facility agriculture,and biochar plays an important role in guaranteeing food production,as well as alleviating water shortages and the overuse of fertilizers.The field experiment had twelve treatments and a control(CK)trial including two irrigation amounts(I1,100%ETm;I2,60%ETm;where ETm is the maximum evapotranspiration),two nitrogen applications(N1,360 kg ha^(−1);N2,120 kg ha^(−1))and three biochar application levels(B1,60 t ha^(−1);B_(2),30 t ha^(−1)and B3,0 t ha^(−1)).A multi-objective synergistic irrigation-nitrogen-biochar application system for improving tomato yield,quality,water and nitrogen use efficiency,and greenhouse emissions was developed by integrating the techniques of experimentation and optimization.First,a coupled irrigation-nitrogen-biochar plot experiment was arranged.Then,tomato yield and fruit quality parameters were determined experimentally to establish the response relationships between irrigation-nitrogen-biochar dosage and yield,comprehensive quality of tomatoes(TCQ),irrigation water use efficiency(IWUE),partial factor productivity of nitrogen(PFPN),and net greenhouse gas emissions(NGE).Finally,a multi-objective dynamic optimization regulation model of irrigation-nitrogen-biochar resource allocation at different growth stages of tomato was constructed which was solved by the fuzzy programming method.The results showed that the application of irrigation and nitrogen to biochar promoted increase in yield,IWUE and PFPN,while it had an inhibitory effect on NGE.In addition,the optimal allocation amounts of water and fertilizer were different under different scenarios.The yield of the S1 scenario increased by 8.31%compared to the B_(1)I_(1)N_(2) treatment;TCQ of the S2 scenario increased by 5.14%compared to the B_(2)I_(2)N_(1) treatment;IWUE of the S3 scenario increased by 10.01%compared to the B1I2N2 treatment;PFPN of the S4 scenario increased by 9.35%compared to the B_(1)I_(1)N_(2) treatment;and NGE of the S5 scenario decreased by 11.23%compared to the B_(2)I1N1 treatment.The optimization model showed that the coordination of multiple objectives considering yield,TCQ,IWUE,PFPN,and NGE increased on average from 4.44 to 69.02%compared to each treatment when the irrigation-nitrogen-biochar dosage was 205.18 mm,186 kg ha^(−1)and 43.31 t ha^(−1),respectively.This study provides a guiding basis for the sustainable management of water and fertilizer in greenhouse tomato production under drip irrigation fertilization conditions.
基金funding support from the National Natural Science Foundation of China(Grant Nos.52074298 and 52204164)Fundamental Research Funds for the Central Universities(Grant No.2022XJSB03).
文摘The deformation control of surrounding rock in gobside roadway with thick and hard roof poses a significant challenge to the safety and efficiency of coal mining.To address this issue,a novel approach combining directional and non-directional blasting techniques,known as combined blasting,was proposed.This study focuses on the experimental investigation of the proposed method in the 122108 working face in Caojiatan Coal Mine as the engineering background.The initial phase of the study involves physical model experiments to reveal the underlying mechanisms of combined blasting for protecting gob-side roadway with thick and hard roof.The results demonstrate that this approach effectively accelerates the collapse of thick and hard roofs,enhances the fragmentation and expansion coefficient of gangue,facilitates the filling of the goaf with gangue,and provides support to the overlying strata,thus reducing the subsidence of the overlying strata above the goaf.Additionally,the method involves cutting the main roof into shorter beams to decrease the stress and disrupt stress transmission pathways.Subsequent numerical simulations were conducted to corroborate the findings of the physical model experiments,thus validating the accuracy of the experimental results.Furthermore,field engineering experiments were performed,affirming the efficacy of the combined blasting method in mitigating the deformation of surrounding rock and achieving the desired protection of the gob-side roadway.
基金This research was funded by the Project of the National Natural Science Foundation of China,Grant Number 62106283.
文摘Aiming at the problems of low solution accuracy and high decision pressure when facing large-scale dynamic task allocation(DTA)and high-dimensional decision space with single agent,this paper combines the deep reinforce-ment learning(DRL)theory and an improved Multi-Agent Deep Deterministic Policy Gradient(MADDPG-D2)algorithm with a dual experience replay pool and a dual noise based on multi-agent architecture is proposed to improve the efficiency of DTA.The algorithm is based on the traditional Multi-Agent Deep Deterministic Policy Gradient(MADDPG)algorithm,and considers the introduction of a double noise mechanism to increase the action exploration space in the early stage of the algorithm,and the introduction of a double experience pool to improve the data utilization rate;at the same time,in order to accelerate the training speed and efficiency of the agents,and to solve the cold-start problem of the training,the a priori knowledge technology is applied to the training of the algorithm.Finally,the MADDPG-D2 algorithm is compared and analyzed based on the digital battlefield of ground and air confrontation.The experimental results show that the agents trained by the MADDPG-D2 algorithm have higher win rates and average rewards,can utilize the resources more reasonably,and better solve the problem of the traditional single agent algorithms facing the difficulty of solving the problem in the high-dimensional decision space.The MADDPG-D2 algorithm based on multi-agent architecture proposed in this paper has certain superiority and rationality in DTA.
基金Key Laboratory of Deep-time Geography and Environment Reconstruction and Applications of Ministry of Natural ResourcesChengdu University of Technology:DGERA20231110。
文摘Excessive carbon emissions have resulted in the greenhouse effect, causing considerable global climate change. Marine carbon storage has emerged as a crucial approach to addressing climate change. The Qiantang Sag(QTS) in the East China Sea Shelf Basin, characterized by its extensive area, thick sedimentary strata, and optimal depth, presents distinct geological advantages for carbon dioxide(CO_(2)) storage. Focusing on the lower section of the Shimentan Formation in the Upper Cretaceous of the QTS, this study integrates seismic interpretation and drilling data with core and thin-section analysis. We reveal the vertical variation characteristics of the strata by providing a detailed stratigraphic description. We use petrophysical data to reveal the development characteristics of high-quality carbon-storage layers and favorable reservoircaprock combinations, thereby evaluating the geological conditions for CO_(2) storage in various stratigraphic sections. We identify Layer B of the lower Shimentan Formation as the most advantageous stratum for marine CO_(2) storage. Furthermore, we analyze the carbon emission trends in the adjacent Yangtze River Delta region. Considering the characteristics of the source and sink areas, we suggest a strong correlation between the carbon emission sources of the Yangtze River Delta and the CO_(2) storage area of the QTS, making the latter a priority area for conducting experiments on marine CO_(2) storage.
基金Supported by the National Natural Science Foundation of China(No.41961124009)the Earmarked Fund for China Agriculture Research System(No.CARS-49)+1 种基金the fund for Outstanding Talents and Innovative Team of Agricultural Scientific Research from MARA,the Innovation Team of Aquaculture Environment Safety from Liaoning Province(No.LT202009)the Dalian High Level Talent Innovation Support Program(No.2022RG14)。
文摘The Pacific oyster Crassostrea gigas,one of the most exploited molluscs in the world,has suffered from massive mortality in recent decades,and the occurrence mechanisms have not been well characterized.In this study,to reveal the relationship of associated microbiota to the fitness of oysters,temporal dynamics of microbiota in the gill,hemolymph,and hepatopancreas of C.gigas during April 2018-January 2019 were investigated by 16 S rRNA gene sequencing.The microbiota in C.gigas exhibited tissue heterogeneity,of which Spirochaetaceae was dominant in the gill and hemolymph while Mycoplasmataceae enriched in the hepatopancreas.Co-occurrence network demonstrated that the gill microbiota exhibited higher inter-taxon connectivity while the hemolymph microbiota had more modules.The richness(Chao 1 index)and diversity(Shannon index)of microbial community in each tissue showed no significant seasonal variations,except for the hepatopancreas having a higher richness in the autumn.Similarly,beta diversity analysis indicated a relatively stable microbiota in each tissue during the sampling period,showing relative abundance of the dominant taxa exhibiting temporal dynamics.Results indicate that the microbial community in C.gigas showed a tissue-specific stability with temporal dynamics in the composition,which might be essential for the tissue functioning and environmental adaption in oysters.This work provides a baseline microbiota in C.gigas and is helpful for the understanding of host-microbiota interaction in oysters.
基金supported by the Program for Guangdong Introducing Innovative and Entrepreneurial Teams(2021ZT090543)the National Natural Science Foundation of China(U20A20117)the Key-Area Research and Development Program of Guangdong Province(2020B1111380003).
文摘Land use/land cover represents the interactive and comprehensive influences between human activities and natural conditions,leading to potential conflicts among natural and human-related issues as well as among stakeholders.This study introduced economic standards for farmers.A hybrid approach(CA-ABM)of cellular automaton(CA)and an agent-based model(ABM)was developed to effectively deal with social and land-use synergic issues to examine human–environment interactions and projections of land-use conversions for a humid basin in south China.Natural attributes and socioeconomic data were used to analyze land use/land cover and its drivers of change.The major modules of the CA-ABM are initialization,migration,assets,land suitability,and land-use change decisions.Empirical estimates of the factors influencing the urban land-use conversion probability were captured using parameters based on a spatial logistic regression(SLR)model.Simultaneously,multicriteria evaluation(MCE)and Markov models were introduced to obtain empirical estimates of the factors affecting the probability of ecological land conversion.An agent-based CA-SLR-MCE-Markov(ABCSMM)land-use conversion model was proposed to explore the impacts of policies on land-use conversion.This model can reproduce observed land-use patterns and provide links for forest transition and urban expansion to land-use decisions and ecosystem services.The results demonstrated land-use simulations under multi-policy scenarios,revealing the usefulness of the model for normative research on land-use management.
基金Scientific Research Project of Liaoning Province Education Department,Code:LJKQZ20222457&LJKMZ20220781Liaoning Province Nature Fund Project,Code:No.2022-MS-291.
文摘As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.
基金the Liaoning Province Nature Fundation Project(2022-MS-291)the National Programme for Foreign Expert Projects(G2022006008L)+2 种基金the Basic Research Projects of Liaoning Provincial Department of Education(LJKMZ20220781,LJKMZ20220783,LJKQZ20222457)King Saud University funded this study through theResearcher Support Program Number(RSPD2023R704)King Saud University,Riyadh,Saudi Arabia.
文摘The existing algorithms for solving multi-objective optimization problems fall into three main categories:Decomposition-based,dominance-based,and indicator-based.Traditional multi-objective optimization problemsmainly focus on objectives,treating decision variables as a total variable to solve the problem without consideringthe critical role of decision variables in objective optimization.As seen,a variety of decision variable groupingalgorithms have been proposed.However,these algorithms are relatively broad for the changes of most decisionvariables in the evolution process and are time-consuming in the process of finding the Pareto frontier.To solvethese problems,a multi-objective optimization algorithm for grouping decision variables based on extreme pointPareto frontier(MOEA-DV/EPF)is proposed.This algorithm adopts a preprocessing rule to solve the Paretooptimal solution set of extreme points generated by simultaneous evolution in various target directions,obtainsthe basic Pareto front surface to determine the convergence effect,and analyzes the convergence and distributioneffects of decision variables.In the later stages of algorithm optimization,different mutation strategies are adoptedaccording to the nature of the decision variables to speed up the rate of evolution to obtain excellent individuals,thusenhancing the performance of the algorithm.Evaluation validation of the test functions shows that this algorithmcan solve the multi-objective optimization problem more efficiently.
基金support from the Liaoning Province Nature Fund Project(No.2022-MS-291)the Scientific Research Project of Liaoning Province Education Department(LJKMZ20220781,LJKMZ20220783,LJKQZ20222457,JYTMS20231488).
文摘Nowadays,with the rapid development of industrial Internet technology,on the one hand,advanced industrial control systems(ICS)have improved industrial production efficiency.However,there are more and more cyber-attacks targeting industrial control systems.To ensure the security of industrial networks,intrusion detection systems have been widely used in industrial control systems,and deep neural networks have always been an effective method for identifying cyber attacks.Current intrusion detection methods still suffer from low accuracy and a high false alarm rate.Therefore,it is important to build a more efficient intrusion detection model.This paper proposes a hybrid deep learning intrusion detection method based on convolutional neural networks and bidirectional long short-term memory neural networks(CNN-BiLSTM).To address the issue of imbalanced data within the dataset and improve the model’s detection capabilities,the Synthetic Minority Over-sampling Technique-Edited Nearest Neighbors(SMOTE-ENN)algorithm is applied in the preprocessing phase.This algorithm is employed to generate synthetic instances for the minority class,simultaneously mitigating the impact of noise in the majority class.This approach aims to create a more equitable distribution of classes,thereby enhancing the model’s ability to effectively identify patterns in both minority and majority classes.In the experimental phase,the detection performance of the method is verified using two data sets.Experimental results show that the accuracy rate on the CICIDS-2017 data set reaches 97.7%.On the natural gas pipeline dataset collected by Lan Turnipseed from Mississippi State University in the United States,the accuracy rate also reaches 85.5%.
基金Funding is provided by the National Natural Science Foundation of China(NSFC,Grant Nos.62375027 and 62127813)Natural Science Foundation of Chongqing Municipality(CSTB2023NSCQ-MSX0504)+1 种基金Natural Science Foundation of Jilin Provincial(YDZJ202201ZYTS411)Jilin Provincial Education Department Fund of China(JJKH20240920KJ)。
文摘Optical telescopes are an important tool for acquiring optical information about distant objects,and resolution is an important indicator that measures the ability to observe object details.However,due to the effects of system aberration,atmospheric seeing,and other factors,the observed image of ground-based telescopes is often degraded,resulting in reduced resolution.This paper proposes an optical-neural network joint optimization method to improve the resolution of the observed image by co-optimizing the point-spread function(PSF)of the telescopic system and the image super-resolution(SR)network.To improve the speed of image reconstruction,we designed a generative adversarial net(LCR-GAN)with light parameters,which is much faster than the latest unsupervised networks.To reconstruct the PSF trained by the network in the optical path,a phase mask is introduced.It improves the image reconstruction effect of LCR-GAN by reconstructing the PSF that best matches the network.The results of simulation and verification experiments show that compared with the pure deep learning method,the SR image reconstructed by this method is rich in detail and it is easier to distinguish stars or stripes.
文摘In order to deal with the special spatio-temporal environmental changes encountered in the process of open-cast mining,taking Huolinhe No.1 Open-cast Mine as the research object,this paper studied its typical problems in river reconstruction and cultural relics protection.The study focused on eight key core aspects,including the design optimization of the spatial layout of the mining area,the accurate estimation of the mineral resources reserves,the scientific theoretical demonstration of the mining scale,the fine analysis and calculation of the stripping ratio,the comprehensive consideration of the transport distance and efficiency,the accurate judgment of the best time for the implementation of the transformation,the analysis and evaluation of the slope stability,and the overall planning of the production system.The results show that the extracted problem-solving strategies and scheme system for special mining conditions can not only provide specific and practical guidance for Huolinhe No.1 Open-cast Mine,but also serve as a valuable reference and practical reference for other open-cast mine enterprises facing similar challenges.
基金National Institutes of Health, Grant CA83719US Department of Veterans Affairs
文摘This review summarizes the current state of knowledge regarding the role of endothelial dysfunction in the pathogenesis of early and delayed intestinal radiation toxicity and discusses various endothelial-oriented interventions aimed at reducing the risk of radiation enteropathy. Studies published in the biomedical literature during the past four decades and cited in PubMed, as well as clinical and laboratory data from our own research program are reviewed. The risk of injury to normal tissues limits the cancer cure rates that can be achieved with radiation therapy. During treatment of abdominal and pelvic tumors, the intestine is frequently a major close-limiting factor. Microvascular injury is a prominent feature of both early （inflammatory）, as well as delayed （fibroproliferative） radiation injuries in the intestine and in many other normal tissues. Evidence from our and other laboratories suggests that endothelial dysfunction, notably a deficiency of endothelial thrombomodulin, plays a key role in the pathogenesis of these radiation responses. Deficient levels of thrombomodulin cause loss of vascular thromboresistance, excessive activation of cellular thrombin receptors by thrombin, and insufficient activation of protein C, a plasma protein with anticoagulant, anti-inflammatory, and cytoprotective properties. These changes are presumed to be critically involved in many aspects of early intestinal radiation toxicity and may sustain the fibroproliferative processes that lead to delayed intestinal dysfunction, fibrosis, and clinical complications. In conclusion, injury of vascular endothelium is important in the pathogenesis of the intestinal radiation response. Endothelial-oriented interventions are appealing strategies to prevent or treat normal tissue toxicity associated with radiation treatment of cancer.
基金This work was financially supported by the National Natural Science Foundation of China(No.52103091)the Natural Science Foundation of Jiangsu Province(No.BK20200501)the State Key Laboratory of Polymer Materials Engineering(No.sklpme2022-3-15).
文摘Phase change materials(PCMs)are expected to achieve dual-mode thermal management for heating and cooling Li-ion batteries(LIBs)according to real-time thermal conditions,guaranteeing the reliable operation of LIBs in both cold and hot environments.Herein,we report a liquid metal(LM)modified polyethylene glycol/LM/boron nitride PCM,capable of dual-mode thermal managing the LIBs through photothermal effect and passive thermal conduction.Its geometrical conformation and thermal pathways fabricated through ice-template strategy are conformable to the LIB’s structure and heat-conduction characteristic.Typically,soft and deformable LMs are modified on the boron nitride surface,serving as thermal bridges to reduce the contact thermal resistance among adjacent fillers to realize high thermal conductivity of 8.8 and 7.6 W m^(−1) K^(−1) in the vertical and in-plane directions,respectively.In addition,LM with excellent photothermal performance provides the PCM with efficient battery heating capability if employing a controllable lighting system.As a proof-of-concept,this PCM is manifested to heat battery to an appropriate temperature range in a cold environment and lower the working temperature of the LIBs by more than 10℃ at high charging/discharging rate,opening opportunities for LIBs with durable working performance and evitable risk of thermal runaway.
基金the financial supports provided by the National Natural Science Foundation of China (Nos. 21971145, 21601108)the Taishan Scholar Project Foundation of Shandong Province (ts20190908)+1 种基金the Natural Science Foundation of Shandong Province (ZR2019MB024)Young Scholars Program of Shandong University (2017WLJH15)。
文摘Lithium-sulfur batteries(LSBs) are regarded as a competitive next-generation energy storage device.However, their practical performance is seriously restricted due to the undesired polysulfides shuttling.Herein, a multifunctional interlayer composed of paper-derived carbon(PC) scaffold, Fe3O4 nanoparticles,graphene, and graphite sheets is designed for applications in LSBs. The porous PC skeleton formed by the interweaving long-fibers not only facilitates fast transfer of Li ions and electrons but also provides a physical barrier for the polysulfide shuttling. The secondary Fe3O4@graphene component can reduce the polarization, boost the attachment of polysulfides, and promote the charging-discharging kinetics. The outer graphitic sheets layers benefit the interfacial electrochemistry and the utilization of S-containing species.The efficient obstruction of polysulfides diffusion is further witnessed via in situ ultraviolet-visible characterization and first-principles simulations. When 73% sulfur/commercial acetylene black is used as the cathode, the cell exhibits excellent capacity retention with high capacities at 0.5 C for 1000 cycles and even up to 10 C for 500 cycles, an ultrahigh rate capability up to 10 C(478 m Ah g-1), and a high arealsulfur loading of 8.05 mg cm-2. The strategy paves the way for developing multifunctional composites for LSBs with superior performance.
基金National Natural Science Foundation of China(51922071,51773139).
文摘Functional polymer composites(FPCs)have attracted increasing attention in recent decades due to their great potential in delivering a wide range of functionalities.These functionalities are largely determined by functional fillers and their network morphology in polymer matrix.In recent years,a large number of studies on morphology control and interfacial modification have been reported,where numerous preparation methods and exciting performance of FPCs have been reported.Despite the fact that these FPCs have many similarities because they are all consisting of functional inorganic fillers and polymer matrices,review on the overall progress of FPCs is still missing,and especially the overall processing strategy for these composites is urgently needed.Herein,a"Toolbox"for the processing of FPCs is proposed to summarize and analyze the overall processing strategies and corresponding morphology evolution for FPCs.From this perspective,the morphological control methods already utilized for various FPCs are systematically reviewed,so that guidelines or even predictions on the processing strategies of various FPCs as well as multi-functional polymer composites could be given.This review should be able to provide interesting insights for the field of FPCs and boost future intelligent design of various FPCs.
基金This study was supported by the National Natural Science Foundation of China(No.51590914).
文摘Coral materials can replace concrete aggregates and achieve material self sufficiency for reducing the construction costs of island projects.This paper studies the effects of different mineral admixtures on the properties of coral aggregate concrete(CAC).The chloride concentration of CAC after different erosion times is measured using the potentiometric method,and the porosity of the CAC is ca lculated using thermogravimetric and drying methods.The chloride concentration of the CAC presents a two-phases dis tribution.The peak chloride concentration fol-lowed a power function,increasing with the erosion time.The chloride diffusion coefficient of CAC is 7.9%-37.5%larger than that of ordinary aggregate concrete,and the addition of 15% fly ash and 5%silica fume can significantly reduce the chloride diffusion coefficient,with a maximum reduction of 45.0%.The porosity obtained via the thermogravimetric and drying methods is well correlated.The porosity has a strong negative correlation with the compressive strength and a strong positive correlation with the chloride diffusion coefficient.
基金This study was supported by the National Natural Science Foundation of China(Nos.31770449,31270465)Fundamental Research Funds for the Central Universities(2662020YLPY016,2662016PY064).
文摘A key scientific challenge relating to the threat of invasive plants on agriculture at the region level is to understand their adaptation and evolution in functional traits.Leaf functional traits,related to growth and resource utilization,might lead to adaptation of invasive plants to the geographical barriers(region or elevation).In the field experiment,we discussed the effects of region and elevation on leaf functional traits on invasive plant Erigeron annuus in farmland habitats in China.We compared leaf size,coefficient of variation(CV)of leaf traits,and fluctuating asymmetry(FA)of E.annuus from three regions(east vs.center vs.west)and two leaf types(vegetative vs.reproductive leaf),and from nine elevations(980-2100 m)in the west region of China.Our results indicated region and leaf type influenced leaf functional traits,and leaf size was significantly higher and CV of leaf traits and FA in reproductive leaves were significantly lower in the east region than in the west and center regions.Elevation and leaf type affected leaf functional traits,and leaf size was significantly higher and CV of leaf traits in reproductive leaves were significantly lower in moderate elevation.E.annuus has higher leaf size and developmental stability(lower CV and FA)in the eastern region due to the longer adaptation period.Therefore,leaf functional traits play an important role in the adaptation of different longitudes and elevations.It can also facilitate the understanding of the invasiveness and adaptation of leaf traits of invasive plants in the agricultural ecosystem during their spread process in China.
文摘Dear Colleagues,This second special edition of the Asian Journal of Urology reviews a number of other important aspects of functional and reconstructive urology.As mentioned in the last special edition,there is a significant ageing of the population in most countries but also a still limited understanding of the structure,innervation and functional pathophysiology seen as an underlying etiological factor in the development of lower urinary tract dysfunction.The article by Lori A.Birder and colleagues[1]emphasises a number of the aspects of pathophysiology seen in the ageing bladder,with reference to existing experimental research in this field.Clearly,work such as this gives us considerable insight into how we can develop new techniques for the future.
