Electron correlation in solids via density embedding theory

Density matrix embedding theory (Phys. Rev. Lett. 109, 186404 (2012)) and density embedding theory ((Phys. Rev. B 89, 035140 (2014)) have recently been introduced for model lattice Hamiltonians and molecular systems. In the present work, the formalism is extended to the ab initio description of infinite systems. An appropriate definition of the impurity Hamiltonian for such systems is presented and demonstrated in cases of 1, 2 and 3 dimensions, using coupled cluster theory as the impurity solver. Additionally, we discuss the challenges related to disentanglement of fragment and bath states. The current approach yields results comparable to coupled cluster calculations of infinite systems even when using a single unit cell as the fragment. The theory is formulated in the basis of Wannier functions but it does not require separate localization of unoccupied bands. The embedding scheme presented here is a promising way of employing highly accurate electronic structure methods for extended systems at a fraction of their original computational cost

Study of Risk Evaluation for Complex Projects under BIM and IPD Collaborative Pattern Based on Neighborhood Rough Sets

Faced with the existing problems in the construction industry, project managers have been aware that traditional project delivery patterns cannot satisfy the current building industry\u27s pursuit of high-quality economic benefits or cope with the increasing volume and complexity of modern buildings. Therefore, whole-process comprehensive management has become a new development trend for engineering projects, the traditional project delivery pattern should be changed, and early-stage communication, cooperation, and information sharing among project participants should be strengthened. As for the BIM and IPD collaborative pattern, the emphasis is laid on collaboration among project members, and the core idea lies in benefit and risk sharing and full consideration of human resources, commercial structure and engineering system of projects. The advent of IPD pattern has well solved problematic issues encountered in engineering projects, where risk problem has attracted the highest attention. Risk factors of IPD projects were reduced and screened out based on attribute reduction theory of rough sets, and primary risk factors influencing smooth implementation of IPD projects were obtained

Ultra-Sensitive Piezo-Resistive Sensors Constructed with Reduced Graphene Oxide/Polyolefin Elastomer (RGO/POE) Nanofiber Aerogels.

Flexible wearable pressure sensors have received extensive attention in recent years because of the promising application potentials in health management, humanoid robots, and human machine interfaces. Among the many sensory performances, the high sensitivity is an essential requirement for the practical use of flexible sensors. Therefore, numerous research studies are devoted to improving the sensitivity of the flexible pressure sensors. The fiber assemblies are recognized as an ideal substrate for a highly sensitive piezoresistive sensor because its three-dimensional porous structure can be easily compressed and can provide high interconnection possibilities of the conductive component. Moreover, it is expected to achieve high sensitivity by raising the porosity of the fiber assemblies. In this paper, the three-dimensional reduced graphene oxide/polyolefin elastomer (RGO/POE) nanofiber composite aerogels were prepared by chemical reducing the graphene oxide (GO)/POE nanofiber composite aerogels, which were obtained by freeze drying the mixture of the GO aqueous solution and the POE nanofiber suspension. It was found that the volumetric shrinkage of thermoplastic POE nanofibers during the reduction process enhanced the compression mechanical strength of the composite aerogel, while decreasing its sensitivity. Therefore, the composite aerogels with varying POE nanofiber usage were prepared to balance the sensitivity and working pressure range. The results indicated that the composite aerogel with POE nanofiber/RGO proportion of 3:3 was the optimal sample, which exhibits high sensitivity (ca. 223 kPa-1) and working pressure ranging from 0 to 17.7 kPa. In addition, the composite aerogel showed strong stability when it is either compressed with different frequencies or reversibly compressed and released 5000 times

An Anatomy-aware Framework for Automatic Segmentation of Parotid Tumor from Multimodal MRI

Magnetic Resonance Imaging (MRI) plays an important role in diagnosing the parotid tumor, where accurate segmentation of tumors is highly desired for determining appropriate treatment plans and avoiding unnecessary surgery. However, the task remains nontrivial and challenging due to ambiguous boundaries and various sizes of the tumor, as well as the presence of a large number of anatomical structures around the parotid gland that are similar to the tumor. To overcome these problems, we propose a novel anatomy-aware framework for automatic segmentation of parotid tumors from multimodal MRI. First, a Transformer-based multimodal fusion network PT-Net is proposed in this paper. The encoder of PT-Net extracts and fuses contextual information from three modalities of MRI from coarse to fine, to obtain cross-modality and multi-scale tumor information. The decoder stacks the feature maps of different modalities and calibrates the multimodal information using the channel attention mechanism. Second, considering that the segmentation model is prone to be disturbed by similar anatomical structures and make wrong predictions, we design anatomy-aware loss. By calculating the distance between the activation regions of the prediction segmentation and the ground truth, our loss function forces the model to distinguish similar anatomical structures with the tumor and make correct predictions. Extensive experiments with MRI scans of the parotid tumor showed that our PT-Net achieved higher segmentation accuracy than existing networks. The anatomy-aware loss outperformed state-of-the-art loss functions for parotid tumor segmentation. Our framework can potentially improve the quality of preoperative diagnosis and surgery planning of parotid tumors.Comment: under revie

Marine Ecological Disasters and Their Physical Controlling Mechanisms in Jiangsu Coastal Area

The studies in this chapter are focused on marine ecological disasters in Jiangsu coastal area. Three kinds of algal blooms occurred in this region, namely, red tide associated with Dinoflagellate, green tide associated with Ulvaprolifera and golden tide associated with Sargassum. Numerical model results demonstrated that red tides in Haizhou Bay originated locally, because most of Dinoflagellates near Zhoushan Islands would be transported northeastward by the Changjiang diluted water, and even the lucky ones that entered the south of Jiangsu coastal area would die in the Subei Shoal due to high turbidity there. Due to the Changjiang diluted water and the prevailing southerly wind, Ulvaprolifera could not drift southward, either. Seawater with high turbidity in the Subei Shoal limited sunlight penetration into deep water column, and further inhibited the growth of Ulvaprolifera suspending in the water column. In this chapter, we use drift bottles and satellite-tracked Argos drifters to provide solid direct dynamic evidence that Ulvaprolifera could drift from the Subei Shoal to Qingdao coastal area and even further north. The sand ridges limited the traveling path of Ulvaprolifera in the Subei Shoal, and wind-driven currents and other baroclinic processes helped Ulvaprolifera travel farther to the north