Three dimensional spider-web-like superconducting filamentary paths in KxFe2−ySe2K_xFe_{2-y}Se_2 single crystals

Since the discovery of high temperature superconductivity in F-doped LaFeAsO, many new iron based superconductors with different structures have been fabricated2. The observation of superconductivity at about 32 K in KxFe2-ySe2 with the iso-structure of the FeAs-based 122 superconductors was a surprise and immediately stimulated the interests because the band structure calculation8 predicted the absence of the hole pocket which was supposed to be necessary for the theoretical picture of S+- pairing. Soon later, it was found that the material may separate into the insulating antiferromagnetic K2Fe4Se5 phase and the superconducting phase. It remains unresolved that how these two phases coexist and what is the parent phase for superconductivity. In this study we use different quenching processes to produce the target samples with distinct microstructures, and apply multiple measuring techniques to reveal a close relationship between the microstructures and the global appearance of superconductivity. In addition, we clearly illustrate three dimensional spider-web-like superconducting filamentary paths, and for the first time propose that the superconducting phase may originate from a state with one vacancy in every eight Fe-sites with the root8*root10 parallelogram structure.Comment: 22 pages, 7 figure

Optimization of shift schedule for hybrid electric vehicle with automated manual transmission

Currently, most hybrid electric vehicles (HEVs) equipped with automated mechanical transmission (AMT) are implemented with the conventional two-parameter gear shift schedule based on engineering experience. However, this approach cannot take full advantage of hybrid drives. In other words, the powertrain of an HEV is not able to work at the best fuel-economy points during the whole driving profile. To solve this problem, an optimization method of gear shift schedule for HEVs is proposed based on Dynamic Programming (DP) and a corresponding solving algorithm is also put forward. A gear shift schedule that can be employed in real-vehicle is extracted from the obtained optimal gear shift points by DP approach and is optimized based on analysis of the engineering experience in a typical Chinese urban driving cycle. Compared with the conventional two-parameter gear shift schedule in both simulation and real vehicle experiments, the extracted gear shift schedule is proved to clearly improve the fuel economy of the HEV

Dynamic motion of polar skyrmions in oxide heterostructures

Polar skyrmions have been widely investigated in oxide heterostructure recently, due to their exotic properties and intriguing physical insights. Meanwhile, so far, the external field-driven motion of the polar skyrmion, akin to the magnetic counterpart, has yet to be discovered. Here, using phase-field simulations, we demonstrate the dynamic motion of the polar skyrmions with integrated external thermal, electrical, and mechanical stimuli. The external heating reduces the spontaneous polarization hence the skyrmion motion barrier, while the skyrmions shrink under the electric field, which could weaken the lattice pinning and interactions between the skyrmions. The mechanical force transforms the skyrmions into c-domain in the vicinity of the indenter center under the electric field, providing the space and driving force needed for the skyrmions to move. This study confirmed that the skyrmions are quasi-particles that can move collectively, while also providing concrete guidance for the further design of polar skyrmion-based electronic devices.Comment: 17 pages, 4 figure

New Dynamic Stability Rig for Tri-sonic Wind-tunnel

AbstractThe present-day unconventional and high-lifting aerospace configuration design has greatly increased the demand for accurate prediction and expanded measure dynamic stability derivatives envelopes of conventional aerospace vehicles. With these issues in mind, china academy of aerospace aerodynamics (CAAA) designed and built a forced oscillation test rig in the sub-, tran- and supersonic wind tunnel that provides new capabilities for aerodynamic researchers to accurately measure the dynamic derivatives and investigate the asymmetric coupling effects of high-lifting aerospace configuration vehicles

GlyphControl: Glyph Conditional Control for Visual Text Generation

Recently, there has been a growing interest in developing diffusion-based text-to-image generative models capable of generating coherent and well-formed visual text. In this paper, we propose a novel and efficient approach called GlyphControl to address this task. Unlike existing methods that rely on character-aware text encoders like ByT5 and require retraining of text-to-image models, our approach leverages additional glyph conditional information to enhance the performance of the off-the-shelf Stable-Diffusion model in generating accurate visual text. By incorporating glyph instructions, users can customize the content, location, and size of the generated text according to their specific requirements. To facilitate further research in visual text generation, we construct a training benchmark dataset called LAION-Glyph. We evaluate the effectiveness of our approach by measuring OCR-based metrics and CLIP scores of the generated visual text. Our empirical evaluations demonstrate that GlyphControl outperforms the recent DeepFloyd IF approach in terms of OCR accuracy and CLIP scores, highlighting the efficacy of our method.Comment: Technical report. The codes will be released at https://github.com/AIGText/GlyphControl-releas

Mask-Attention-Free Transformer for 3D Instance Segmentation

Recently, transformer-based methods have dominated 3D instance segmentation, where mask attention is commonly involved. Specifically, object queries are guided by the initial instance masks in the first cross-attention, and then iteratively refine themselves in a similar manner. However, we observe that the mask-attention pipeline usually leads to slow convergence due to low-recall initial instance masks. Therefore, we abandon the mask attention design and resort to an auxiliary center regression task instead. Through center regression, we effectively overcome the low-recall issue and perform cross-attention by imposing positional prior. To reach this goal, we develop a series of position-aware designs. First, we learn a spatial distribution of 3D locations as the initial position queries. They spread over the 3D space densely, and thus can easily capture the objects in a scene with a high recall. Moreover, we present relative position encoding for the cross-attention and iterative refinement for more accurate position queries. Experiments show that our approach converges 4x faster than existing work, sets a new state of the art on ScanNetv2 3D instance segmentation benchmark, and also demonstrates superior performance across various datasets. Code and models are available at https://github.com/dvlab-research/Mask-Attention-Free-Transformer.Comment: Accepted to ICCV 2023. Code and models are available at https://github.com/dvlab-research/Mask-Attention-Free-Transforme