Leelillelund3272

With the rapid development of wearable artificial intelligence devices, there is an increasing demand for flexible oxide neuromorphic transistors with the solid electrolytes. To achieve high-performance flexible synaptic transistors, the solid electrolytes should exhibit good mechanical bending characteristics and high ion conductivity. However, the polymer-based electrolytes with good mechanical bending characteristics show poor ion conductivity (10-6-10-7S cm-1), which limits the performance of flexible synaptic transistors. Thus, it is urgent to improve the ion conductivity of the polymer-based electrolytes. In the work, a new strategy of electrospun Li0.33La0.557TiO3nanofibers-enhanced ion transport pathway is proposed to simultaneously improve the mechanical bending and ion conductivity of polyethylene oxide/polyvinylpyrrolidone-based solid electrolytes. The flexible InZnO synaptic transistors with Li0.33La0.557TiO3nanofibers-based solid electrolytes successfully simulated excitatory post-synaptic current, paired-pulse-facilitation, dynamic time filter, nonlinear summation, two-terminal input dynamic integration and logic function. This work is a useful attempt to develop high-performance synaptic transistors.We have calculated kinetic inductanceLkof a thin superconductor/ferromagnet/normal metal strip in an in-plane Fulde-Ferrell (FF) state. We consider range of parameters when FF state appears at temperatureTFF less then Tc(Tcis a transition temperature to superconducting state) when the paramagnetic response of FN layers overcomes the diamagnetic response of S layer. We show thatLkdiverges atT=TFFwhich is consequence of the second order phase transition to FF state, similar to divergency ofLkatT=Tc. Kinetic inductance also diverges at finite magnetic field atT less then TFFwhich is consequence of magnetic field driven second order transition to/from FF state. Due to presence in the FF state finite supervelocity, at low current there are two states (metastable and ground) which have differentLk. Metastable state is unstable above some critical current which is much smaller than depairing current, above which the ground state becomes unstable. It results in strong dependence ofLkon current not only at large currents (near depairing current) but at low currents too. We argue that found properties could be useful in various applications which exploit temperature, current and magnetic field dependence of the kinetic inductance.In the conventional DFT + U approach, the mean field solution of the Hubbard Hamiltonian associated with thedorf(iσ) electrons of a transition metal atom is used to define the DFT + U potential acting on theiσ-electrons. In this work, we go beyond that mean field solution by analyzing the correlation energy and potential for a multi-level atom described by a Kanamori Hamiltonian connected to different channels representing the environment. As a first step, we analyze the many-body solution of our model, using a local-orbital density functional formalism that takes as independent variables the orbital occupancies,niσ, of the atomic orbitals; accordingly, we present the corresponding density functional solution describing the correlation energy and potential as a function ofniσ. Then, we use this analysis to introduce a DFT + U potential extending previous proposals to materials with arbitrarily high correlation. In particular, we find that this potential mainly screens the conventional mean field potential contribution, and also yields new terms associated with the number of atomic electrons. Our results show that the atomic correlation effects enhance the role played by the intra-atomic exchange interaction and favor the formation of magnetic solutions.Healthcare professionals have been increasingly viewing medical images and videos in their routine clinical practice, and this in a wide variety of environments. Both the perception and interpretation of medical visual information, across all branches of practice or medical specialties (e.g. diagnostic, therapeutic, or surgical medicine), career stages, and practice settings (e.g. emergency care), appear to be critical for patient care. However, medical images and videos are not self-explanatory and, therefore, need to be interpreted by humans, i.e. medical experts. In addition, various types of degradations and artifacts may appear during image acquisition or processing, and consequently affect medical imaging data. Such distortions tend to impact viewers' quality of experience, as well as their clinical practice. It is accordingly essential to better understand how medical experts perceive the quality of visual content. Thankfully, progress has been made in the recent literature towards such understanding. In this article, we present an up-to-date state-of the-art of relatively recent (i.e. not older than ten years old) existing studies on the subjective quality assessment of medical images and videos, as well as research works using task-based approaches. Furthermore, we discuss the merits and drawbacks of the methodologies used, and we provide recommendations about experimental designs and statistical processes to evaluate the perception of medical images and videos for future studies, which could then be used to optimise the visual experience of image readers in real clinical practice. Finally, we tackle the issue of the lack of available annotated medical image and video quality databases, which appear to be indispensable for the development of new dedicated objective metrics.Objective.The common marmoset has been increasingly used in neural interfacing studies due to its smaller size, easier handling, and faster breeding compared to Old World non-human primate (NHP) species. While assessment of cortical anatomy in marmosets has shown strikingly similar layout to macaques, comprehensive assessment of electrophysiological properties underlying forelimb reaching movements in this bridge species does not exist. The objective of this study is to characterize electrophysiological properties of signals recorded from the marmoset primary motor cortex (M1) during a reach task and compare with larger NHP models such that this smaller NHP model can be used in behavioral neural interfacing studies.Approach and main results.Neuronal firing rates and local field potentials (LFPs) were chronically recorded from M1 in three adult, male marmosets. Firing rates, mu + beta and high gamma frequency bands of LFPs were evaluated for modulation with respect to movement. Firing rate and regularity of neurons of the marmoset M1 were similar to that reported in macaques with a subset of neurons showing selectivity to movement direction. Movement phases (rest vs move) was classified from both neural spiking and LFPs. Microelectrode arrays provide the ability to sample small regions of the motor cortex to drive brain-machine interfaces (BMIs). see more The results demonstrate that marmosets are a robust bridge species for behavioral neuroscience studies with motor cortical electrophysiological signals recorded from microelectrode arrays that are similar to Old World NHPs.Significance. As marmosets represent an interesting step between rodent and macaque models, successful demonstration that neuron modulation in marmoset motor cortex is analogous to reports in macaques illustrates the utility of marmosets as a viable species for BMI studies.Metallic implants can heavily attenuate x-rays in computed tomography (CT) scans, leading to severe artifacts in reconstructed images, which significantly jeopardize image quality and negatively impact subsequent diagnoses and treatment planning. With the rapid development of deep learning in the field of medical imaging, several network models have been proposed for metal artifact reduction (MAR) in CT. Despite the encouraging results achieved by these methods, there is still much room to further improve performance. In this paper, a novel dual-domain adaptive-scaling non-local network (DAN-Net) is proposed for MAR. We correct the corrupted sinogram using adaptive scaling first to preserve more tissue and bone details. Then, an end-to-end dual-domain network is adopted to successively process the sinogram and its corresponding reconstructed image is generated by the analytical reconstruction layer. In addition, to better suppress the existing artifacts and restrain the potential secondary artifacts caused by inaccurate results of the sinogram-domain network, a novel residual sinogram learning strategy and non-local module are leveraged in the proposed network model. Experiments demonstrate the performance of the proposed DAN-Net is competitive with several state-of-the-art MAR methods in both qualitative and quantitative aspects.Octopus suckers that possess the ability to actively control adhesion through muscle actuation have inspired artificial adhesives for safe manipulation of thin and delicate objects. However, the design of adhesives with fast adhesion switching speed to transport cargoes in confined spaces remains an open challenge. Here, we present an untethered magnetic adhesive pad combining the functionality of fast adhesion switching and remotely controlled locomotion. The adhesive pad can be activated from low-adhesion state to high-adhesion state by near infrared laser within 30 s, allowing to fulfill a high-throughput task of retrieving and releasing objects. Moreover, under the guidance of external magnetic field, the proposed pad is demonstrated to transport thin and fragile electronic components across a tortuous path, thus indicating its potential for dexterous delivery in complex working environments.Group VA metal halide-based perovskites have emerged as intensively explored Pb-free perovskites, owing to their excellent environmental stability and low-toxicity. However, the relatively low carrier mobility and high photocarrier recombination rates restrict their applications in photodetectors. One promising approach to achieve higher performance is to integrate these Pb-free perovskites with 2D materials to form heterostructures. Here, we report on the high sensitivity photodetectors based on MoS2/Cs3Bi2I9and graphene/Cs3Bi2I9heterostructures for multispectral regions. The heterostructures combine the high carrier mobility of 2D materials with superior light-harvesting properties of perovskites, as well as the effective built-in electric filed at the junction area, leading to efficient photocarrier separation and extraction. The specific detectivity of MoS2/Cs3Bi2I9device reaches 1.15 × 1013Jones for the detection of ultraviolet (UV) light of 325 nm, which is four orders of magnitude higher than UV detectors built on GaN. As a result of the efficient dark current suppression, the specific detectivity of graphene/Cs3Bi2I9photodetector can be promoted to 5.24 × 1011Jones, 1.33 × 1011Jones, and 1.12 × 1011Jones for the detection of 325 nm, 447 nm, and 532 nm light, respectively.Herein, 3D honeycomb hierarchical porous network scaffold carbon is synthesized by a unique PVP-SiO2-boiling method with the boiling bubbles as soft template and SiO2nanospheres as hard template. Then MnO2nanosheets intimately grow on the carbon matrix and are further decomposed to Mn3O4nanocrystalline with size of 7-9 nm. The obtained Mn3O4nanocrystalline@3D honeycomb hierarchical porous network scaffold carbon has abundant mesopores and large specific surface area (92 m2g-1). When used as a cathode material for zinc-ion batteries, the synthesized composites exhibit high reversible capacity (546.2 mAh g-1at 0.5 A g-1), remarkable cycling stability (discharge capacity of 97.8 mAh g-1at 3 A g-1after 600 cycles) and superior rate capability (15.7 mAh g-1at 10 A g-1). The kinetics analyses indicate zinc storage mechanism includes diffusion process and capacitive process of Zn2+and H+ions, and the capacitive storage is dominant. The outstanding zinc storage performance benefits from the structural advantages. The unique carbon matrix improves electronic conductivity of Mn3O4, facilitates penetration of electrolyte, and well supports Mn3O4nanocrystalline.