Indium-tin-zinc oxide (ITZO) covered with a silicon oxide layer can be made conductive when subjected to an oxygen plasma treatment. The resulting resistivity is sensitive to the thickness of the cover oxide, the plas...
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Multi-hazard susceptibility prediction is an important component of disasters risk management *** effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their ***,with the rap...
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Multi-hazard susceptibility prediction is an important component of disasters risk management *** effective multi-hazard risk mitigation strategy includes assessing individual hazards as well as their ***,with the rapid development of artificial intelligence technology,multi-hazard susceptibility prediction techniques based on machine learning has encountered a huge *** order to effectively solve this problem,this study proposes a multi-hazard susceptibility mapping framework using the classical deep learning algorithm of Convolutional Neural Networks(CNN).First,we use historical flash flood,debris flow and landslide locations based on Google Earth images,extensive field surveys,topography,hydrology,and environmental data sets to train and validate the proposed CNN ***,the proposed CNN method is assessed in comparison to conventional logistic regression and k-nearest neighbor methods using several objective criteria,i.e.,coefficient of determination,overall accuracy,mean absolute error and the root mean square *** results show that the CNN method outperforms the conventional machine learning algorithms in predicting probability of flash floods,debris flows and ***,the susceptibility maps of the three hazards based on CNN are combined to create a multi-hazard susceptibility *** can be observed from the map that 62.43%of the study area are prone to hazards,while 37.57%of the study area are *** hazard-prone areas,16.14%,4.94%and 30.66%of the study area are susceptible to flash floods,debris flows and landslides,*** terms of concurrent hazards,0.28%,7.11%and 3.13%of the study area are susceptible to the joint occurrence of flash floods and debris flow,debris flow and landslides,and flash floods and landslides,respectively,whereas,0.18%of the study area is subject to all the three *** results of this study can benefit engineers,disaster managers and local government offici
Learning and inferring underlying motion patterns of captured 2D scenes and then re-creating dynamic evolution consistent with the real-world natural phenomena have high appeal for graphics and *** bridge the technica...
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Learning and inferring underlying motion patterns of captured 2D scenes and then re-creating dynamic evolution consistent with the real-world natural phenomena have high appeal for graphics and *** bridge the technical gap between virtual and real environments,we focus on the inverse modeling and reconstruction of visually consistent and property-verifiable oceans,taking advantage of deep learning and differentiable physics to learn geometry and constitute waves in a self-supervised ***,we infer hierarchical geometry using two networks,which are optimized via the differentiable *** extract wave components from the sequence of inferred geometry through a network equipped with a differentiable ocean ***,ocean dynamics can be evolved using the reconstructed wave *** extensive experiments,we verify that our new method yields satisfactory results for both geometry reconstruction and wave ***,the new framework has the inverse modeling potential to facilitate a host of graphics applications,such as the rapid production of physically accurate scene animation and editing guided by real ocean scenes.
Backward stimulated Brillouin scattering(SBS)is widely exploited for various applications in optics and *** typically features a narrow gain bandwidth of a few tens of megahertz in fluoride *** we report a hundredfold...
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Backward stimulated Brillouin scattering(SBS)is widely exploited for various applications in optics and *** typically features a narrow gain bandwidth of a few tens of megahertz in fluoride *** we report a hundredfold increase of SBS bandwidth in whispering-gallery mode *** crystalline orientation results in a large variation of the acoustic phase velocity upon propagation along the periphery,from which a broad Brillouin gain is *** 2.5 GHz wide Brillouin gain profile is theoretically found and experimentally *** phenomena with Brillouin shift frequencies ranging from 11.73 to 14.47 GHz in ultrahigh Q Z-cut magnesium fluoride cavities pumped at the telecommunication wavelength are ***,the Brillouin-Kerr comb in this device is *** 400 comb lines spanning across a spectral window of 120 nm are *** finding paves a new way for tailoring and harnessing the Brillouin gain in crystals.
Metasurfaces are one of the most promising devices to break through the limitations of bulky optical *** offering a new method of light manipulation based on the light-matter interaction in subwavelength nanostructure...
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Metasurfaces are one of the most promising devices to break through the limitations of bulky optical *** offering a new method of light manipulation based on the light-matter interaction in subwavelength nanostructures,metasurfaces enable the efficient manipulation of the amplitude,phase,polarization,and frequency of light and derive a series of possibilities for important ***,one key challenge for the realization of applications for meta-devices is how to fabricate large-scale,uniform nanostructures with high *** this review,we review the state-of-the-art nanofabrication techniques compatible with the manufacture of *** lithography,masked lithography,and other nanofabrication techniques are highlighted in *** also delve into the constraints and limitations of the current fabrication methods while providing some insights on solutions to overcome these challenges for advanced nanophotonic applications.
To solve the data island problem,federated learning(FL)provides a solution paradigm where each client sends the model parameters but not the data to a server for model ***-to-peer(P2P)federated learning further improv...
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To solve the data island problem,federated learning(FL)provides a solution paradigm where each client sends the model parameters but not the data to a server for model ***-to-peer(P2P)federated learning further improves the robustness of the system,in which there is no server and each client communicates directly with the *** secure aggregation,secure multi-party computing(SMPC)protocols have been utilized in peer-to-peer ***,the ideal SMPC protocols could fail when some clients drop *** this paper,we propose a robust peer-to-peer learning(RP2PL)algorithm via SMPC to resist clients dropping *** improve the segmentbased SMPC protocol by adding a check and designing the generation method of random seg*** RP2PL,each client aggregates their models by the improved robust secure multi-part computation protocol when finishes the local *** results demonstrate that the RP2PL paradigm can mitigate clients dropping out with no significant degradation in performance.
Understanding the integrated transport behavior of oil in shale nanopores is critical to efficient shale oil development. In this paper, based on the time-dependent Poiseuille flow momentum equation, we present a nove...
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Understanding the integrated transport behavior of oil in shale nanopores is critical to efficient shale oil development. In this paper, based on the time-dependent Poiseuille flow momentum equation, we present a novel transient model to describe oil transport in unsteady and steady states. The model incorporates the effect of the critical shift density, apparent viscosity, slip length, and alkane property, as well as pore tortuosity and surface roughness. We evaluated our model through a comparison with other models, experiments, and molecular dynamics simulations. The results show that the development rates of the volume flows of C_(6)–C_(12) alkane confined in inorganic nanopores and C_(12) alkane confined in organic nanopores were faster than that of the corresponding bulk alkane. In addition, the critical drift density positively promoted the volume flow development rate in the unsteady state and negatively inhibited the mass flow rate in the steady state. This effect was clearest in pores with a smaller radius and lower-energy wall and in alkane with shorter chain lengths. Furthermore, both the nanoconfinement effect and pore structure determined whether the volume flow enhancement rate was greater than or less than 1. The rate increased or decreased with time and was controlled mainly by the nanoconfinement effect. Moreover, as the wall energy increased, the flow inhibition effect increased;as the carbon number of alkane increased, the flow promotion effect increased. The results indicate that the proposed model can accurately describe oil transport in shale nanopores.
A high-efficiency (97%) fast polarization converter (100 kHz) is achieved using Ferroelectric Liquid Crystal (FLC). Innovatively, by cascading FLC cells, no diffraction and residual light loss are achieved. The flicke...
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The rapid increase in the parameter counts of Large Language Models (LLMs), reaching billions or even trillions, presents significant challenges for their practical deployment, particularly in resource-constrained env...
Quantum computing is a promising paradigm for efficiently solving large and high-complexity problems. However, ensuring privacy within this quantum computing necessitates innovative approaches. Existing research has i...
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