Fine debris is an important component of natural debris *** studies focused primarily on the clay minerals found in the fines,and non-clay minerals were often *** effects of mineralogy of fines on debris-mass slurryin...
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Fine debris is an important component of natural debris *** studies focused primarily on the clay minerals found in the fines,and non-clay minerals were often *** effects of mineralogy of fines on debris-mass slurrying and flow behaviors of the resultant slurries are examined *** fines(≤0.04 mm)in the<5 mm fraction of the Dongyuege Creek debris-flow deposit is replaced with five other mineral powders with the same maximum particle *** types of separate and sequential experiments related to debris slurrying and slurry behaviors are carried out with the prepared clastic *** obtained slurrying index ranging from 0.08 to 0.18 shows that non-clay minerals also can function as the fine fractions of debris-flow materials,so long as the requirement of grain size distribution is ***,non-clay minerals making up fines of debris flows can increase the upper solid concentration limits of slurrying(with a maximum of 0.692)and peak values of relative excess water pressure(measured maximum mean peak value is 0.99),leading to higher momentum and higher competence,and thereby more destructive *** sediments with platy non-clay mineral-dominated fines have potential for mobilizing into small-to medium-size debris flows with a relatively small *** minerals in the fines may indeed enhance the liquefaction potential of debris masses by expanding the difference between upper and lower solid concentration limits of slurrying(0.413 and 0.238,respectively,for pure kaolinite),but they significantly suppress the momentum,competence,and destructive power of potential debris flows by lowering upper solid concentration limit of slurrying of debris *** catchments rich in non-clay minerals,notably those releasing dolomite into loose sediments,may be more prone to threatening and destructive debris *** basin producing clay minerals should be more susceptible to lowmagnitude/high-frequency debris flows
In recent decades, Cellular Networks (CN) have been used broadly in communication technologies. The most critical challenge in the CN was congestion control due to the distributed mobile environment. Some approaches, ...
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Predicting and controlling crowd dynamics in emergencies is one of the main objectives of simulated emergency exercises. However, during emergency exercises, there is often a lack of sense of danger by the actors invo...
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The increasing dependence on smartphones with advanced sensors has highlighted the imperative of precise transportation mode classification, pivotal for domains like health monitoring and urban planning. This research...
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The increasing dependence on smartphones with advanced sensors has highlighted the imperative of precise transportation mode classification, pivotal for domains like health monitoring and urban planning. This research is motivated by the pressing demand to enhance transportation mode classification, leveraging the potential of smartphone sensors, notably the accelerometer, magnetometer, and gyroscope. In response to this challenge, we present a novel automated classification model rooted in deep reinforcement learning. Our model stands out for its innovative approach of harnessing enhanced features through artificial neural networks (ANNs) and visualizing the classification task as a structured series of decision-making events. Our model adopts an improved differential evolution (DE) algorithm for initializing weights, coupled with a specialized agent-environment relationship. Every correct classification earns the agent a reward, with additional emphasis on the accurate categorization of less frequent modes through a distinct reward strategy. The Upper Confidence Bound (UCB) technique is used for action selection, promoting deep-seated knowledge, and minimizing reliance on chance. A notable innovation in our work is the introduction of a cluster-centric mutation operation within the DE algorithm. This operation strategically identifies optimal clusters in the current DE population and forges potential solutions using a pioneering update mechanism. When assessed on the extensive HTC dataset, which includes 8311 hours of data gathered from 224 participants over two years. Noteworthy results spotlight an accuracy of 0.88±0.03 and an F-measure of 0.87±0.02, underscoring the efficacy of our approach for large-scale transportation mode classification tasks. This work introduces an innovative strategy in the realm of transportation mode classification, emphasizing both precision and reliability, addressing the pressing need for enhanced classification mechanisms in an eve
Finding materials with specific properties is a hot topic in materials *** materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high *** the developmen...
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Finding materials with specific properties is a hot topic in materials *** materials design relies on empirical and trial-and-error methods,requiring extensive experiments and time,resulting in high *** the development of physics,statistics,computerscience,and other fields,machine learning offers opportunities for systematically discovering new *** through machine learning-based inverse design,machine learning algorithms analyze the mapping relationships between materials and their properties to find materials with desired *** paper first outlines the basic concepts of materials inverse design and the challenges faced by machine learning-based approaches to materials inverse ***,three main inverse design methods—exploration-based,model-based,and optimization-based—are analyzed in the context of different application ***,the applications of inverse design methods in alloys,optical materials,and acoustic materials are elaborated on,and the prospects for materials inverse design are *** authors hope to accelerate the discovery of new materials and provide new possibilities for advancing materials science and innovative design methods.
The agriculture industry is currently dealing with serious issues with rice plants as a result of illnesses that decrease the quantity and output of the harvest. Numerous fungi and bacteria diseases harm plants that a...
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We theoretically investigate coherent scattering of single photons and quantum entanglement of two giant atoms with azimuthal angle differences in a waveguide *** the real-space Hamiltonian,analytical expressions are ...
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We theoretically investigate coherent scattering of single photons and quantum entanglement of two giant atoms with azimuthal angle differences in a waveguide *** the real-space Hamiltonian,analytical expressions are derived for the transport spectra scattered by these two giant atoms with four azimuthal ***-like resonance can be exhibited in the scattering spectra by adjusting the azimuthal angle *** concurrence of the entangled state for two atoms can be implemented in a wide angle-difference range,and the entanglement of the atomic states can be switched on/off by modulating the additional azimuthal angle differences from the giant *** suggests a novel handle to effectively control the single-photon scattering and quantum entanglement.
In this study, a series of polycrystalline Pr2-xGdxNiO4 (PGNO) ceramics doped with Gd were synthesized using the sol-gel technique. The study analyzed the crystal structure, microstructure, valence states, elemental d...
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In low-density steel,κ-carbides primarily precipitate in the form of nanoscale particles within austenite ***,their precipitation within ferrite matrix grains has not been comprehensively explored,and the second-phas...
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In low-density steel,κ-carbides primarily precipitate in the form of nanoscale particles within austenite ***,their precipitation within ferrite matrix grains has not been comprehensively explored,and the second-phase evolution mechanism during aging remains *** this study,the crystallographic characteristics and morphological evolution ofκ-carbides in Fe-28Mn-10Al-0.8C(wt%)low-density steel at different aging temperatures and times and the impacts of these changes on the steels’microhardness and properties were comprehensively *** different heat treatment conditions,intragranularκ-carbides exhibited various morpho-logical and crystallographic characteristics,such as acicular,spherical,and short rod-like *** the initial stage of aging,acicularκ-carbides primarily precipitated,accompanied by a few spherical carbides.κ-Carbides grew and coarsened with aging time,the spherical carbides were considerably reduced,and rod-like carbides *** hardness testing demonstrated that the material’s hardness was affected by the volume fraction,morphology,and size ofκ-*** aging at higher temperatures led to an increase in carbide size and volume fraction,resulting in a gradual rise in *** deformation,the primary mechanisms for strengthening were dislocation strengthening and second-phase *** on these findings,potential strategies for improving material strength are proposed.
On the premise of ensuring the structural integrity of reinforcement, optimizing the microstructure of interfaces can be an effective method to improve the comprehensive performance of composites. In this study, carbo...
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