INTRODUCTION The manufacturing industry has evolved from traditional forging and cutting to three-dimensional(3D)printing,a revolutionary technology that expands human imagination by creating everything of complex sha...
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INTRODUCTION The manufacturing industry has evolved from traditional forging and cutting to three-dimensional(3D)printing,a revolutionary technology that expands human imagination by creating everything of complex shapes and intricate structures,making it a cornerstone of smart manufacturing.1 However,conventional fabrications may encounter bottlenecks that seriously restrict their printing across different inks,ambient,and *** existing 3D printing methods to produce target functional components on diverse working media,therefore,requires significant *** highly adaptable 3D printing inks,liquid metals(LMs)open large spaces to address such challenges due to their versatile capabilities,such as fluidities,conductivities,easy solid-liquid transitions,and *** continuous efforts are being increasingly made in LM printing in different media,2 there is still no generalized methodology or concept proposed to unite all LM 3D printing techniques,inks,and media *** achieve this intriguing target,here we present a unified 3D printing concept,termed pan-media liquid metal 3D printing,to manufacture customized end-user devices as ***-media 3D printing means that it is able to administrate printing with any ink and any working ambient,from gases and liquids to soft matters,bio-tissues,and rigid media,transcending the boundaries of traditional printing ***,with intentionally introduced physical or chemical processing between LM inks and ambient,pan-media LM 3D printing could achieve a much wider variety of 3D object and targeted functions over existing *** synthesizing the pan-media theory of LM 3D printing,we prospect a pan-media manufacturing center equipped with functional ink storage,media library,printing head system,and control units,all integrated to fully address the desired printing tasks.
Few-shot semantic segmentation has considerable potential for low-data scenarios, especially for medical images that require expert-level dense annotations. Existing few-shot medical image segmentation methods strive ...
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The massive multiple-input and multiple-output (MIMO) system based on channel state information (CSI) is the core technology of next-generation communication. As the complexity of the CSI matrix gradually increases, C...
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Low-light images are usually affected by problems such as low illumination, noise, and color distortion, resulting in unsatisfactory image enhancement. Low-light image enhancement aims to improve the quality and visib...
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Phenylacetic acid(PAA)is a primary raw material for illegal Methamphetamine(MATM)synthesis under the strong precursor chemicals supervisions of safrole and ***,trace detection of PAA at ultra-low concentration is a st...
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Phenylacetic acid(PAA)is a primary raw material for illegal Methamphetamine(MATM)synthesis under the strong precursor chemicals supervisions of safrole and ***,trace detection of PAA at ultra-low concentration is a strategic technique and an urgent issue in the field of drug *** this paper,trace determination of PAA at sub-nmol-L-1 concentration level is achieved by hydrogen bond adsorption and electrochemical catalysis through the prepared aminated SiO_(2)nanoparticles(SiO_(2)-NH_(2) NPs)and MoS_(2) nanosheets(NSs)modified glassy carbon electrode(GCE).The prepared MoS_(2) NS s/SiO_(2)-NH_(2) NPs modified electrode represents a detecting limit of 0.0989 nmol·L^(-1)and an obvious increasing linear range before the concentration increasement up to 60 nmol·L^(-1)in square wave voltammetry(SWV)responses of *** SWV response of the modified electrode to PAA in the concentration range within 100 nmol·L^(-1)is higher than phenol,acetic acid(HOAc)and benzoic Acid(BEN).This electrochemical method for trace detection of PAA in aqueous solution with desired performance provides a feasible scheme for the detection of other drugs and aromatic precursor chemicals.
In recent years, significant progress has been made in image dehazing, but most dehazing convolutional neural networks only learn from hazy images to the corresponding feature maps of clean images, ignoring the detail...
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Few-shot learning based methods can address the reliance on large-scale labeled samples in current breast tumor segmentation. However, previous methods typically rely on a few support samples to extract abstract, coar...
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Massive multiple-input multiple-output (MIMO) system is one of the wireless technologies with great research significance based on channel state information (CSI). As the complexity of the CSI matrix increases, CSI fe...
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The influence maximization(IM)problem aims to find a set of seed nodes that maximizes the spread of their influence in a social *** positive influence maximization(PIM)problem is an extension of the IM problem,which c...
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The influence maximization(IM)problem aims to find a set of seed nodes that maximizes the spread of their influence in a social *** positive influence maximization(PIM)problem is an extension of the IM problem,which consider the polar relation of nodes in signed social networks so that the positive influence of seeds can be the most widely *** solve the PIM problem,this paper proposes the polar and decay related independent cascade(IC-PD)model to simulate the influence propagation of nodes and the decay of information during the influence propagation in signed social *** overcome the low efficiency of the greedy based algorithm,this paper defines the polar reverse reachable(PRR)set and devises a signed reverse influence sampling(SRIS)*** algorithm utilizes the ICPD model as well as the PRR set to select *** are two phases in *** is the sampling phase,which utilizes the IC-PD model to generate the PRR set and a binary search algorithm to calculate the number of needed PRR *** other is the node selection phase,which uses a greedy coverage algorithm to select optimal ***,Experiments on three real-world polar social network datasets demonstrate that SRIS outperforms the baseline algorithms in *** on the Slashdot dataset,SRIS achieves 24.7% higher performance than the best-performing compared algorithm under the weighted cascade model when the seed set size is 25.
Purpose:Community detection is a key factor in analyzing the structural features of complex ***,traditional dynamic community detection methods often fail to effectively solve the problems of deep network information ...
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Purpose:Community detection is a key factor in analyzing the structural features of complex ***,traditional dynamic community detection methods often fail to effectively solve the problems of deep network information loss and computational complexity in hyperbolic *** address this challenge,a hyperbolic space-based dynamic graph neural network community detection model(HSDCDM)is ***/methodology/approach:HSDCDM first projects the node features into the hyperbolic space and then utilizes the hyperbolic graph convolution module on the Poincare and Lorentz models to realize feature fusion and information *** addition,the parallel optimized temporal memory module ensures fast and accurate capture of time domain information over extended ***,the community clustering module divides the community structure by combining the node characteristics of the space domain and the time *** evaluate the performance of HSDCDM,experiments are conducted on both artificial and real ***:Experimental results on complex networks demonstrate that HSDCDM significantly enhances the quality of community detection in hierarchical *** shows an average improvement of 7.29%in NMI and a 9.07%increase in ARI across datasets compared to traditional *** complex networks with nonEuclidean geometric structures,the HSDCDM model incorporating hyperbolic geometry can better handle the discontinuity of the metric space,provides a more compact embedding that preserves the data structure,and offers advantages over methods based on Euclidean geometry ***/value:This model aggregates the potential information of nodes in space through manifoldpreserving distribution mapping and hyperbolic graph topology ***,it optimizes the Simple Recurrent Unit(SRU)on the hyperbolic space Lorentz model to effectively extract time series data in hyperbolic space,thereby enhancing computing efficiency by eliminating t
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