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Spin transfer nano-oscillators (STNOs) are nanoscale devices which are promising candidates for on-chip microwave signal sources. For application purposes, they are expected to be nano-sized, to have broad working frequency, narrow spectral linewidth, high output power and low power consumption. In this paper, we demonstrate by micromagnetic simulation that magnetic skyrmions, topologically stable nanoscale magnetization configurations, can be excited into oscillation by a spin-polarized current. Thus, we propose a new kind of STNO using magnetic skyrmions. It is found that the working frequency of this oscillator can range from nearly 0 Hz to gigahertz. The linewidth can be smaller than 1 MHz. Furthermore, this device can work at a current density magnitude as small as 108 A m−2, and it is also expected to improve the output power. Our studies may contribute to the development of skyrmion-based microwave generators.

Biomedical images have complex tissue structures, and there are great differences between images of the same part of different individuals. Although deep learning methods have made some progress in automatic segmentation of biomedical images, the segmentation accuracy is relatively low for biomedical images with significant changes in segmentation targets, and there are also problems of missegmentation and missed segmentation. To address these challenges, we proposed a biomedical image segmentation method based on dense atrous convolution. First, we added a dense atrous convolution module (DAC) between the encoding and decoding paths of the U-Net network. This module was based on the inception structure and atrous convolution design, which can effectively capture multi-scale features of images. Second, we introduced a dense residual pooling module to detect multi-scale features in images by connecting residual pooling blocks of different sizes. Finally, in the decoding part of the network, we adopted an attention mechanism to suppress background interference by enhancing the weight of the target area. These modules work together to improve the accuracy and robustness of biomedical image segmentation. The experimental results showed that compared to mainstream segmentation networks, our segmentation model exhibited stronger segmentation ability when processing biomedical images with multiple-shaped targets. At the same time, this model can significantly reduce the phenomenon of missed segmentation and missegmentation, improve segmentation accuracy, and make the segmentation results closer to the real situation.

We study spin wave excitation modes of kπ skyrmion (k = 1, 2, 3) in a magnetic nanodot under an external magnetic field along the z direction using micromagnetic simulations based on the Landau-Lifshitz-Gilbert equation. We find that a transition of kπ skyrmion to other skyrmion-like structures appears under some critical external fields, the corresponding spin wave excitations are simulated for each state under magnetic field. For skyrmion, the frequencies of excitation modes increases and then decreases with the low frequency mode splitting at a critical magnetic field. In addition to the well-known two in-plane rotation modes and an out-of-plane breathing mode of skyrmion, more excitation modes are found with a higher k (k = 2, 3). The excitation modes vary as a function of magnetic field, and the excitation frequencies for different modes exhibit a rapid or slight change depending on the field-induced change of magnetization profile. Our study indicates the rich spin wave excitations for kπ skyrmion and opens up the possibility for theoretical or experimental investigation of magnonics application.

Outcome-guided behavior requires knowledge about the identity of future rewards. Previous work across species has shown that the dopaminergic midbrain responds to violations in expected reward identity and that the lateral orbitofrontal cortex (OFC) represents reward identity expectations. Here we used network-targeted transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) during a trans-reinforcer reversal learning task to test the hypothesis that outcome expectations in the lateral OFC contribute to the computation of identity prediction errors (iPE) in the midbrain. Network-targeted TMS aiming at lateral OFC reduced the global connectedness of the lateral OFC and impaired reward identity learning in the first block of trials. Critically, TMS disrupted neural representations of expected reward identity in the OFC and modulated iPE responses in the midbrain. These results support the idea that iPE signals in the dopaminergic midbrain are computed based on outcome expectations represented in the lateral OFC. Behaviour requires knowledge of cues and outcomes. Here the authors use neuromodulation of lateral orbitofrontal cortex and neuroimaging of error-related midbrain activity to reveal the neurocomputational mechanisms underlying reward identity learning.

Magnetic skyrmion-based spin transfer nano-oscillators (STNOs) have been proposed as microwave signal generators and attracted enormous interest recently. However, the oscillation frequency of skyrmion-based STNOs is about 2 GHz, which is not so high for practical applications. In this paper, we create an annular groove in the surface of the free layer and put skyrmions in the annular groove. Due to the potential of the groove, skyrmions are confined to moving in the groove when driven by the spin-polarized currents. Through micromagnetic simulations, it is found that the frequency tunability of the STNO with the presence of the annular groove reaches to 15.63 GHz, which is more than 6 times higher than the case without the presence of the annular groove because of three reasons: the oscillation radius of skyrmions can be adjusted by the groove, the potential of the groove is larger than that of the edge and the groove can limit the diameter of skyrmions so that a larger number of skyrmions can be placed in the groove. Our results present the understanding of dynamic of skyrmions in an annular groove, which provides alternative possibilities for the design of skyrmion-based STNOs.

This paper studies the stationary incompressible Navier-Stokes equations with mixed boundary conditions using a velocity-pressure finite element formulation. We first establish a variational framework and prove existence of solutions under suitable regularity assumptions, followed by a Galerkin discretization with error estimates. Three iterative algorithms (the Stokes, Newton, and Oseen schemes) are then analyzed, with stability conditions and error bounds derived for each. Numerical experiments confirm the theoretical results: all methods achieve second-order convergence for velocity and pressure. Among the three schemes, the Newton iteration is the most efficient in terms of computational time, while the Oseen iteration exhibits the strongest robustness with respect to decreasing viscosity coefficients.

Iron-nickel (Fe-Ni) alloy nanoribbons were reported for the first time by deoxidizing NiFe 2 O 4 nanoribbons, which were synthesized through a handy route of electrospinning followed by air-annealing at 450 °C, in hydrogen (H 2 ) at different temperatures. It was demonstrated that the phase configurations, microstructures and magnetic properties of the as-deoxidized samples closely depended upon the deoxidization temperature. The spinel NiFe 2 O 4 ferrite of the precursor nanoribbons were firstly deoxidized into the body-centered cubic (bcc) Fe-Ni alloy and then transformed into the face-centered cubic (fcc) Fe-Ni alloy of the deoxidized samples with the temperature increasing. When the deoxidization temperature was in the range of 300 ~ 500 °C, although each sample possessed its respective morphology feature, all of them completely reserved the ribbon-like structures. When it was further increased to 600 °C, the nanoribbons were evolved completely into the fcc Fe-Ni alloy nanochains. Additionally, all samples exhibited typical ferromagnetism. The saturation magnetization ( M s ) firstly increased, then decreased, and finally increased with increasing the deoxidization temperature, while the coercivity ( H c ) decreased monotonously firstly and then basically stayed unchanged. The largest M s (~145.7 emu·g −1 ) and the moderate H c (~132 Oe) were obtained for the Fe-Ni alloy nanoribbons with a mixed configuration of bcc and fcc phases.

While tourism eco-efficiency has been analyzed actively within tourism research, there is an extant dearth of research on the spatial network structure of provincial-scale tourism eco-efficiency. The Super-SBM was used to evaluate the tourism eco-efficiency of 30 provinces (excluding Tibet, Hong Kong, Macao and Taiwan). Then, social network analysis was employed to examine the evolution characteristics regarding the spatial network structure of tourism eco-efficiency. The main results are shown as follows. Firstly, tourism eco-efficiency of more than two thirds’ provinces witnessed an increasing trend. Secondly, the spatial network structure of tourism eco-efficiency was still loose and unstable during the sample period. Thirdly, there existed the multidimensional nested and fused spatial factions and condensed subsets in the spatial network structure of tourism eco-efficiency. However, there was still a lack of low-carbon tourism cooperation among second or third sub-groups. These conclusions can provide references for policymakers who expect to reduce carbon emissions from the tourism industry and to achieve sustainable tourism development.

This study demonstrates the controllable switching of skyrmion helicity using spin-orbit torque, enhanced by thermal effects. Electric current pulses applied to a [Pt/Co] 3 /Ru/[Co/Pt] 3 multilayer stripe drive skyrmions in a direction opposite to the current flow. Continuous pulsing results in an unexpected reversal of skyrmion motion. Micromagnetic simulations reveal that skyrmions in the upper and lower ferromagnetic layers exhibit distinct helicities, forming a hybrid synthetic skyrmion. The helicity switch of this hybrid structure accounts for the motion reversal. This study introduces innovative helicity control methods, advancing spintronic device applications, including data storage and quantum computing based on skyrmion helicity. The authors realize s helicity switching of hybrid skyrmions in [Pt/Co] 3 /Ru/[Co/Pt] 3 multilayers using spin-orbit torque and thermal effects, enabling motion reversal. This method advances skyrmion-based spintronic devices for data storage and quantum computing.

Nitrogen (N) fertilization has a considerable effect on food production and carbon cycling in agro-ecosystems. However, the impacts of N fertilization rates on the temperature sensitivity of soil respiration (Q10) were controversial. Five N rates (N0, N45, N90, N135, and N180) were applied to a continuous winter wheat (Triticum aestivum L.) crop on the semi-arid Loess Plateau, and the in situ soil respiration was monitored during five consecutive years from 2008 to 2013. During the growing season, the mean soil respiration rates increased with increasing N fertilization rates, peaking at 1.53 μmol m-2s-1 in the N135 treatment. A similar dynamic pattern was observed during the non-growing season, yet on average with 7.3% greater soil respiration rates than the growing season. In general for all the N fertilization treatments, the mean Q10 value during the non-growing season was significantly greater than that during the growing season. As N fertilization rates increased, the Q10 values did not change significantly in the growing season but significantly decreased in the non-growing season. Overall, N fertilization markedly influenced soil respirations and Q10 values, in particular posing distinct effects on the Q10 values between the growing and non-growing seasons.