Quantum and Classical Communication Complexity of Permutation-Invariant Functions

This paper gives a nearly tight characterization of the quantum communication complexity of the permutation-invariant Boolean functions. With such a characterization, we show that the quantum and randomized communication complexity of the permutation-invariant Boolean functions are quadratically equivalent (up to a logarithmic factor). Our results extend a recent line of research regarding query complexity \cite{AA14, Cha19, BCG+20} to communication complexity, showing symmetry prevents exponential quantum speedups. Furthermore, we show the Log-rank Conjecture holds for any non-trivial total permutation-invariant Boolean function. Moreover, we establish a relationship between the quantum/classical communication complexity and the approximate rank of permutation-invariant Boolean functions. This implies the correctness of the Log-approximate-rank Conjecture for permutation-invariant Boolean functions in both randomized and quantum settings (up to a logarithmic factor).Comment: accepted in STACS 202

Segment Anything Model-guided Collaborative Learning Network for Scribble-supervised Polyp Segmentation

Polyp segmentation plays a vital role in accurately locating polyps at an early stage, which holds significant clinical importance for the prevention of colorectal cancer. Various polyp segmentation methods have been developed using fully-supervised deep learning techniques. However, pixel-wise annotation for polyp images by physicians during the diagnosis is both time-consuming and expensive. Moreover, visual foundation models such as the Segment Anything Model (SAM) have shown remarkable performance. Nevertheless, directly applying SAM to medical segmentation may not produce satisfactory results due to the inherent absence of medical knowledge. In this paper, we propose a novel SAM-guided Collaborative Learning Network (SAM-CLNet) for scribble-supervised polyp segmentation, enabling a collaborative learning process between our segmentation network and SAM to boost the model performance. Specifically, we first propose a Cross-level Enhancement and Aggregation Network (CEA-Net) for weakly-supervised polyp segmentation. Within CEA-Net, we propose a Cross-level Enhancement Module (CEM) that integrates the adjacent features to enhance the representation capabilities of different resolution features. Additionally, a Feature Aggregation Module (FAM) is employed to capture richer features across multiple levels. Moreover, we present a box-augmentation strategy that combines the segmentation maps generated by CEA-Net with scribble annotations to create more precise prompts. These prompts are then fed into SAM, generating segmentation SAM-guided masks, which can provide additional supervision to train CEA-Net effectively. Furthermore, we present an Image-level Filtering Mechanism to filter out unreliable SAM-guided masks. Extensive experimental results show that our SAM-CLNet outperforms state-of-the-art weakly-supervised segmentation methods.Comment: 10 pages, 7 figure

Construction and Characterization of a Chimeric Virus (BIV/HIV-1) Carrying the Bovine Immunodeficiency Virus \u3ci\u3egag\u3c/i\u3e-\u3ci\u3epol\u3c/i\u3e Gene: Research Letters

HIV-1HXB2 5′LTR region, most of BIVR29 gag-pol segment and HIV-1HXB2 pol IN-3′LTR region were respectively amplified. A chimeric clone, designated as pHBIV3753, was constructed by cloning three fragments sequentially into pUC18. MT4 cells were transfected with pHBIV3753. The replication and expressions of the chimeric virus (HBIV3753) were monitored by RT activity and IFA. The results firstly demonstrated that it is possible to generate a new type of the BIV/HIV-1 chimeric virus containing BIV gag-pol gene

SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma

Radiation therapy is a primary and effective NasoPharyngeal Carcinoma (NPC) treatment strategy. The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis. Previously, the delineation of GTVs and OARs was performed by experienced radiation oncologists. Recently, deep learning has achieved promising results in many medical image segmentation tasks. However, for NPC OARs and GTVs segmentation, few public datasets are available for model development and evaluation. To alleviate this problem, the SegRap2023 challenge was organized in conjunction with MICCAI2023 and presented a large-scale benchmark for OAR and GTV segmentation with 400 Computed Tomography (CT) scans from 200 NPC patients, each with a pair of pre-aligned non-contrast and contrast-enhanced CT scans. The challenge's goal was to segment 45 OARs and 2 GTVs from the paired CT scans. In this paper, we detail the challenge and analyze the solutions of all participants. The average Dice similarity coefficient scores for all submissions ranged from 76.68\% to 86.70\%, and 70.42\% to 73.44\% for OARs and GTVs, respectively. We conclude that the segmentation of large-size OARs is well-addressed, and more efforts are needed for GTVs and small-size or thin-structure OARs. The benchmark will remain publicly available here: https://segrap2023.grand-challenge.orgComment: A challenge report of SegRap2023 (organized in conjunction with MICCAI2023

Does Chinese-style margin trading promote the high-quality development of listed companies?

Using the margin trading reform of China's stock market as a quasinatural experiment, this paper explores whether margin trading promotes the high-quality development of listed companies. The results show that total factor productivity (TFP) significantly decreases after listed companies are included in the underlying stocks of margin trading. In addition, the negative impacts are stronger for listed companies with higher financial leverage, lower cash asset holdings, lower shareholdings of financial institution investors, and less attention from securities analysts. Further research shows that the negative impacts of margin trading on TFP are closely related to the deterioration of the information environment and the tightening of financing constraints. When listed companies are included in the underlying stocks of margin trading, they use a lower proportion of their net profit for internal financing (and a higher proportion of their net profit for cash dividends) and significantly reduce external equity financing. The results of this study show that the margin trading reform in China's stock market may inhibit the high-quality development of listed companies to a certain extent

Graph Neural Diffusion Networks for Semi-supervised Learning

Graph Convolutional Networks (GCN) is a pioneering model for graph-based semi-supervised learning. However, GCN does not perform well on sparsely-labeled graphs. Its two-layer version cannot effectively propagate the label information to the whole graph structure (i.e., the under-smoothing problem) while its deep version over-smoothens and is hard to train (i.e., the over-smoothing problem). To solve these two issues, we propose a new graph neural network called GND-Nets (for Graph Neural Diffusion Networks) that exploits the local and global neighborhood information of a vertex in a single layer. Exploiting the shallow network mitigates the over-smoothing problem while exploiting the local and global neighborhood information mitigates the under-smoothing problem. The utilization of the local and global neighborhood information of a vertex is achieved by a new graph diffusion method called neural diffusions, which integrate neural networks into the conventional linear and nonlinear graph diffusions. The adoption of neural networks makes neural diffusions adaptable to different datasets. Extensive experiments on various sparsely-labeled graphs verify the effectiveness and efficiency of GND-Nets compared to state-of-the-art approaches.Comment: 7 page

Coastal Wetlands Play an Important Role in the Ecological Security Pattern of the Coastal Zone

The construction of an ecological security pattern can effectively overcome the contradiction between regional human exploitation and ecological protection in the coastal zone. Taking the Xiangshan Bay (XSB) basin as an example, this study identified ecological source areas from three aspects, namely ecosystem services’ importance, ecological sensitivity, and landscape connectivity, and then constructed ecological resistance surfaces, identified ecological corridors, and constructed an ecological security pattern. The results show that the natural reserves in the XSB basin were all located in the identified primary ecological source areas, thus indicating the feasibility and reliability of the “importance–connectivity–sensitivity” ecological source identification mechanism in this study. The ecological corridor in the coastal wetland area accounts for about 40% of the total corridor length, which is the link connecting other ecological sources, revealing the important role of coastal wetlands in the coastal ecosystem. Through the ecological security pattern of the XSB basin and field investigation, we put forward suggestions such as clearing Spartina alterniflora, restoring salt marsh wetland vegetation, and strengthening follow-up monitoring for the restoration of coastal wetlands. This study is expected to provide reference and guidance for the improvement of coastal zone ecological protection and restoration

Coastal Wetlands Play an Important Role in the Ecological Security Pattern of the Coastal Zone

The construction of an ecological security pattern can effectively overcome the contradiction between regional human exploitation and ecological protection in the coastal zone. Taking the Xiangshan Bay (XSB) basin as an example, this study identified ecological source areas from three aspects, namely ecosystem services’ importance, ecological sensitivity, and landscape connectivity, and then constructed ecological resistance surfaces, identified ecological corridors, and constructed an ecological security pattern. The results show that the natural reserves in the XSB basin were all located in the identified primary ecological source areas, thus indicating the feasibility and reliability of the “importance–connectivity–sensitivity” ecological source identification mechanism in this study. The ecological corridor in the coastal wetland area accounts for about 40% of the total corridor length, which is the link connecting other ecological sources, revealing the important role of coastal wetlands in the coastal ecosystem. Through the ecological security pattern of the XSB basin and field investigation, we put forward suggestions such as clearing Spartina alterniflora, restoring salt marsh wetland vegetation, and strengthening follow-up monitoring for the restoration of coastal wetlands. This study is expected to provide reference and guidance for the improvement of coastal zone ecological protection and restoration