This article introduces AAK24, a Next-to-Leading Order (NLO) QCD analysis of polarized data from both polarized Deep Inelastic Scattering (DIS) and Semi-Inclusive Deep Inelastic Scattering (SIDIS) experiments on the n...
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Properties of stochastic systems are defined by the noise type and deterministic forces acting on the system. In out-of-equilibrium setups, e.g., for motions under action of Lévy noises, the existence of the stat...
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Multimodal platforms combining electrical neural recording and stimulation,optogenetics,optical imaging,and magnetic resonance(MRI)imaging are emerging as a promising platform to enhance the depth of characterization ...
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Multimodal platforms combining electrical neural recording and stimulation,optogenetics,optical imaging,and magnetic resonance(MRI)imaging are emerging as a promising platform to enhance the depth of characterization in neuroscientific *** conductive,optically transparent,and MRI-compatible electrodes can optimally combine all *** as a suitable electrode candidate material can be grown via chemical vapor deposition(CVD)processes and sandwiched between transparent biocompatible ***,due to the high graphene growth temperature(≥900℃)and the presence of polymers,fabrication is commonly based on a manual transfer process of pre-grown graphene sheets,which causes reliability *** this paper,we present CVD-based multilayer graphene electrodes fabricated using a wafer-scale transfer-free process for use in optically transparent and MRI-compatible neural *** fabricated electrodes feature very low impedances which are comparable to those of noble metal electrodes of the same size and *** also exhibit the highest charge storage capacity(CSC)reported to date among all previously fabricated CVD graphene *** graphene electrodes did not reveal any photo-induced artifact during 10-Hz light pulse ***,we show here,for the first time,that CVD graphene electrodes do not cause any image artifact in a 3T MRI *** results demonstrate that multilayer graphene electrodes are excellent candidates for the next generation of neural interfaces and can substitute the standard conventional metal *** fabricated graphene electrodes enable multimodal neural recording,electrical and optogenetic stimulation,while allowing for optical imaging,as well as,artifact-free MRI studies.
K-Nearest Neighbors is a widely used algorithm due to its simplicity and efficacity. However, KNN suffers from many drawbacks, such as it does not work well with datasets with a high number of features. Also, not all ...
K-Nearest Neighbors is a widely used algorithm due to its simplicity and efficacity. However, KNN suffers from many drawbacks, such as it does not work well with datasets with a high number of features. Also, not all the features contribute to the classification process. To resolve these issues, we present an improved KNN algorithm which uses KNN as a base learner in an ensemble method and correlation for selecting the features subsets. The experiment results show that the proposed algorithm performed better than other machine learning algorithms.
In this paper, we propose novel methods to address the challenges of intelligent robotic arm operations in complex environments. Our approach includes a deep learning method for 6D object pose estimation and a deep re...
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In this paper, we propose novel methods to address the challenges of intelligent robotic arm operations in complex environments. Our approach includes a deep learning method for 6D object pose estimation and a deep reinforcement learning method for controlling complex tasks. For 6D object pose estimation, we introduce the Dense Fusion combined with Deep Fusion Transformer model (DFDFTr). This method integrates Dense Fusion and Deep Fusion Transformer, applies re-parameterization techniques such as Reparameterized Convolution and Batch Normalization Fusion, and incorporates specialized neural networks for each stage of the model. Experimental results on the LineMOD and Occlusion LineMOD datasets demonstrate that our method outperforms one-stage approaches like DenseFusion and MPF6D in accuracy and achieves results comparable to advanced two-stage methods such as PVN3D and DTr. Leveraging re-parameterization, our method maintains competitive inference speed with significantly fewer parameters than PVN3D and MPF6D, PoseCNN+ICP without sacrificing accuracy. Additionally, it efficiently processes multiple objects, handling 8 objects in 0.1 s compared to 0.07 s for a single object. For continuous task control, we propose a deep reinforcement learning approach using Realistic Actor-Critic combined with Decoupled Actor-Critic (RAC-DAC), integrated with techniques such as Relay Hindsight Experience Replay (RHER), Multi-step Hindsight Experience Replay (MHER), Curiosity-Driven Prioritization (CDP), and Projected Conflicting Gradients (PCGrad). Experimental results show that RAC-DAC-RHER achieves significantly higher success rates than DDPG-RHER and TD3-RHER, particularly in challenging tasks such as object grasping. It also ensures efficient learning and high accuracy. Furthermore, by refining hyperparameters and integrating MHER, CDP, PCGrad, MLP, and the Clipping Mechanism, we enhanced learning performance, mitigated instabilities, and enabled higher learning rates in spars
The overall translation quality reached by current machine translation (MT) systems for high-resourced language pairs is remarkably good. Standard methods of evaluation are not suitable nor intended to uncover the man...
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Theoretical analysis of the electronic structure of the high-entropy-type superconductor (ScZrNb)1−x(RhPd)x, x ∈ (0.35,0.45) is presented. The studied material is a partially ordered CsCl-type structure, with two sub...
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We revisit the theory of timelike and null geodesics in the (extended) Kerr spacetime. This work is a sequel to a recent paper by Cieślik, Hackmann, and Mach, who applied the so-called Biermann–Weierstrass formula to...
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Metaheuristics are universal optimization algorithms which should be used for solving difficult problems, unsolvable by classic approaches. In this paper we aim at constructing novel socio-cognitive metaheuristic base...
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We report on the chemical structure and spin Hall magnetoresistance (SMR) in epitaxial αFe2O3(hematite)(0001)/Pt(111) bilayers with hematite thicknesses of 6 nm and 15 nm grown by molecular beam epitaxy on a MgO(111)...
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