Insights from ARPES for an undoped, four-layered, two-gap high-T_c superconductor

An undoped cuprate with apical fluorine and inner (i) and outer (o) CuO2-layers is a 60 K superconductor whose Fermi surface (FS) has large n- and p-doped sheets with the SC gap on the n-sheet twice that on the p -sheet (Y. Chen et al.). The Fermi surface is not reproduced by the LDA, but the screening must be substantially reduced due to electronic correlations, and oxygen in the o-layers must be allowed to dimple outwards. This charges the i-layers by 0.01|e|, causes an 0.4 eV Madelung-potential difference between the i and o -layers, quenches the i-o hopping, and localizes the n-sheets onto the i-layers, thus protecting their d-wave pairs from being broken by scattering on impurities in the BaF layers. The correlation-reduced screening strengthens the coupling to z-axis phonons.Comment: 4 pages, 3 figure

Study of Direct Compression Heat Pump Energy-saving Technology

AbstractAnalyzed the feasibility and necessity of the application of heat pump distillation in the gas separation unit. Through the comparison of the results of different heat exchanger, this paper verified the advantages of the heat exchanger with aluminum porous surface tube. Calculated the power consumption of the compressor by Aspen Plus steady-state process simulation, then the value of COP of the heat pump is obtained, and analyzed the economy of the heat pump distillation, the result shows that utilities and operating cost could be decreased by using heat pump distillation in gas separation unit, and the energy utilization efficiency economic benefits and energy-saving effects could be enhanced

4-(4-Bromo­phen­yl)-5-oxo-1,2,3,4,5,6,7,8-octa­hydro­quinazoline-2-thione

The title compound, C14H13BrN2OS, was synthesized from the multicomponent reaction between thio­urea, 4-bromo­benzaldehyde and cyclo­hexane-1,3-dione. The crystal packing is stabilized by inter­molecular N—H⋯O, N—H⋯S, C—H⋯O and C—H⋯S hydrogen bonds. Br⋯O inter­actions [3.183 (3) Å] are also observed in the crystal structure

Research on the key technologies of web parts library in product configuration system

AbstractIn order to build a web-based parts library for the product configuration system, the data description norm, web browsing and application methods are researched. An ontology based data description norm is used to build the web parts library, with the help of product family and the article characteristic table. A plug-in file of Autovue is adapted for web-based browsing and interaction of geometric models of parts. The schema of Application Services Provider is used to realize the application of web parts library in the product configuration system. Empirical results show that the methods are feasible. And the library has been shown to illustrate the concept. The ontology based data description norm can solve the standardization problem. The plug-in file can show the online 3D demo of parts. And the application of ASP can help more companies to use the web parts library. These technologies help to build and use the library

3,3,6,6,9,9-Hexamethyl-2,3,4,5,6,7,8,9-octa­hydro-1H-xanthene-1,8-dione

The title compound, C19H26O3, was synthesized directly from the condensation of 5,5-dimethyl­cyclo­hexane-1,3-dione with malononitrile catalysed by palladium chloride: there are two molecules in the asymmetric unit

MataDoc: Margin and Text Aware Document Dewarping for Arbitrary Boundary

Document dewarping from a distorted camera-captured image is of great value for OCR and document understanding. The document boundary plays an important role which is more evident than the inner region in document dewarping. Current learning-based methods mainly focus on complete boundary cases, leading to poor document correction performance of documents with incomplete boundaries. In contrast to these methods, this paper proposes MataDoc, the first method focusing on arbitrary boundary document dewarping with margin and text aware regularizations. Specifically, we design the margin regularization by explicitly considering background consistency to enhance boundary perception. Moreover, we introduce word position consistency to keep text lines straight in rectified document images. To produce a comprehensive evaluation of MataDoc, we propose a novel benchmark ArbDoc, mainly consisting of document images with arbitrary boundaries in four typical scenarios. Extensive experiments confirm the superiority of MataDoc with consideration for the incomplete boundary on ArbDoc and also demonstrate the effectiveness of the proposed method on DocUNet, DIR300, and WarpDoc datasets.Comment: 12 page

MoWE: Mixture of Weather Experts for Multiple Adverse Weather Removal

Currently, most adverse weather removal tasks are handled independently, such as deraining, desnowing, and dehazing. However, in autonomous driving scenarios, the type, intensity, and mixing degree of the weather are unknown, so the separated task setting cannot deal with these complex conditions well. Besides, the vision applications in autonomous driving often aim at high-level tasks, but existing weather removal methods neglect the connection between performance on perceptual tasks and signal fidelity. To this end, in upstream task, we propose a novel \textbf{Mixture of Weather Experts(MoWE)} Transformer framework to handle complex weather removal in a perception-aware fashion. We design a \textbf{Weather-aware Router} to make the experts targeted more relevant to weather types while without the need for weather type labels during inference. To handle diverse weather conditions, we propose \textbf{Multi-scale Experts} to fuse information among neighbor tokens. In downstream task, we propose a \textbf{Label-free Perception-aware Metric} to measure whether the outputs of image processing models are suitable for high level perception tasks without the demand for semantic labels. We collect a syntactic dataset \textbf{MAW-Sim} towards autonomous driving scenarios to benchmark the multiple weather removal performance of existing methods. Our MoWE achieves SOTA performance in upstream task on the proposed dataset and two public datasets, i.e. All-Weather and Rain/Fog-Cityscapes, and also have better perceptual results in downstream segmentation task compared to other methods. Our codes and datasets will be released after acceptance