An original model for multi-target learning of logical rules for knowledge graph reasoning

Large-scale knowledge graphs provide structured representations of human knowledge. However, as it is impossible to collect all knowledge, knowledge graphs are usually incomplete. Reasoning based on existing facts paves a way to discover missing facts. In this paper, we study the problem of learning logical rules for reasoning on knowledge graphs for completing missing factual triplets. Learning logical rules equips a model with strong interpretability as well as the ability to generalize to similar tasks. We propose a model able to fully use training data which also considers multi-target scenarios. In addition, considering the deficiency in evaluating the performance of models and the quality of mined rules, we further propose two novel indicators to help with the problem. Experimental results empirically demonstrate that our model outperforms state-of-the-art methods on five benchmark datasets. The results also prove the effectiveness of the indicators

Weight-dependent Gates for Differentiable Neural Network Pruning

In this paper, we propose a simple and effective network pruning framework, which introduces novel weight-dependent gates to prune filter adaptively. We argue that the pruning decision should depend on the convolutional weights, in other words, it should be a learnable function of filter weights. We thus construct the weight-dependent gates (W-Gates) to learn the information from filter weights and obtain binary filter gates to prune or keep the filters automatically. To prune the network under hardware constraint, we train a Latency Predict Net (LPNet) to estimate the hardware latency of candidate pruned networks. Based on the proposed LPNet, we can optimize W-Gates and the pruning ratio of each layer under latency constraint. The whole framework is differentiable and can be optimized by gradient-based method to achieve a compact network with better trade-off between accuracy and efficiency. We have demonstrated the effectiveness of our method on Resnet34, Resnet50 and MobileNet V2, achieving up to 1.33/1.28/1.1 higher Top-1 accuracy with lower hardware latency on ImageNet. Compared with state-of-the-art pruning methods, our method achieves superior performance.Comment: ECCV worksho

Effectiveness and safety of vedolizumab for ulcerative colitis: a single-center retrospective real-world study in China

Introduction: The effectiveness and safety of vedolizumab (VDZ) against ulcerative colitis (UC) have been validated in several randomized controlled trials and real-world studies in Western countries. However, there are few studies on VDZ in Asia, and the follow-up period for these studies is generally short. Therefore, this study evaluates the long-term effectiveness and safety of VDZ in Chinese patients with UC.Methods: This retrospective study included patients with moderate to severe UC treated with VDZ between September 2019 and April 2022 at Sir Run Run Shaw Hospital, College of Medicine Zhejiang University. Clinical response and remission were assessed using the patient reported outcomes and the partial Mayo Score, and mucosal remission and healing were assessed using the Mayo Endoscopy Score. The primary endpoint was defined as clinical remission at week 14, and secondary endpoints included clinical response and steroid-free clinical remission at week 14, clinical response, clinical remission, and steroid-free clinical remission at week 52, and mucosal remission and healing at weeks 14 ± 8 and 52 ± 8.Results: Overall, 64 patients with moderate to severe UC were enrolled. The clinical response, clinical remission, and steroid-free clinical remission rates at week 14 were 73.4% (47/64), 65.6% (42/64), and 54.7% (35/64), respectively. Mucosal remission and healing rates at week 14 ± 8 were 64.7% (22/34) and 38.2% (13/34), respectively. A total of 48 patients were treated with VDZ for 52 weeks. Based on intention-to-treat analysis, the clinical response, clinical remission, and steroid-free clinical remission rates at week 52 were 68.8% (44/64), 64.1% (41/64), and 64.1% (41/64), respectively. Mucosal remission and healing rates at week 52 ± 8 were 70.6% (12/17) and 35.3% (6/17), respectively. During the follow-up period, the most common adverse event was skin rash (6/64). No cases of acute infusion reactions, delayed allergic reactions, new hepatitis B infections, active tuberculosis, or malignant tumors were reported.Conclusion: In this single-center retrospective real-world study, the effectiveness of long-term use of VDZ for Chinese patients with UC was similar to the outcomes previously reported in other geographical regions and populations; no new safety signals were found compared with other registered studies

Effectiveness of the Endplate Reduction Technique Combined With Bone Grafting for the Treatment of Thoracolumbar Fractures by Using Posterior Short-Segment Fixation

Objective This study aimed to examine the effect of the endplate reduction (EPR) technique combined with bone grafting for treating thoracolumbar burst fractures using posterior short-segmental fixation. Methods Patients with thoracolumbar fractures admitted between January 2018 and October 2021 were retrospectively analyzed, and those meeting the criteria were assigned to the EPR group and the intermediate screws (IS) group. The vertebral wedge angle (VWA), Cobb angle (CA), anterior vertebral body height (AVBH), middle vertebral body height (MVBH), upper endplate line (UEPL), upper intervertebral angle (UIVA), and upper intervertebral disc height (UIDH) indices were examined and compared preoperatively, first day postoperatively, as well as at 12 months postoperatively. Results The result indicated that the EPR group achieved better MVBH reduction (p<0.001), UEPL reduction (p<0.001), vertebral body fracture healing (p=0.006), as well as implant breakage (p=0.04) than the IS group; VWA (p<0.001), CA (p=0.005), AVBH (p<0.001), MVBH (p<0.001), UEPL (p<0.001), and UIDH (p<0.001) were lost after reduction less than those in the IS group. There was no significant difference in operative time (p=0.315) and intraoperative bleeding (p=0.274) between the 2 groups. Conclusion The EPR group achieved better results in repositioning and maintaining MVBH and endplate morphology, with less correction loss after the reduction of the VWA, CA, AVBH, and endplate morphology. The EPR group exhibited a better healing pattern after vertebral fracture and disc degeneration was better relieved

Urinary microbiota signatures associated with different types of urinary diversion: a comparative study

BackgroundRadical cystectomy and urinary diversion (UD) are gold standards for non-metastatic muscle-invasive bladder cancer. Orthotopic neobladder (or Studer), ileal conduit (or Bricker) and cutaneous ureterostomy (CU) are mainstream UD types. Little is known about urinary microbiological changes after UD. MethodsIn this study, urine samples were collected from healthy volunteers and patients with bladder cancer who had received aforementioned UD procedures. Microbiomes of samples were analyzed using 16S ribosomal RNA gene sequencing, and microbial diversities, distributions and functions were investigated and compared across groups. ResultsHighest urine microbial richness and diversity were observed in healthy controls, followed by Studer patients, especially those without hydronephrosis or residual urine, α-diversity indices of whom were remarkably higher than those of Bricker and CU groups. Studer UD type was the only independent factor favoring urine microbial diversity. The urine microflora structure of the Studer group was most similar to that of the healthy individuals while that of the CU group was least similar. Studer patients and healthy volunteers shared many similar urine microbial functions, while Bricker and CU groups exhibited opposite characteristics. ConclusionOur study first presented urinary microbial landscapes of UD patients and demonstrated the microbiological advantage of orthotopic neobladder. Microbiota might be a potential tool for optimization of UD management

Slope-based shape cluster method for smart metering load profiles

Cluster analysis is used to study the group of load profiles from smart meters to improve the operability in distribution network. The traditional K-means clustering analysis method employs Euclidean distance as similarity measurement, which is insufficient in reflecting the shape similarities of load profiles. In this work, we propose a novel shape cluster method based on the segmented slope of load profiles. Compared with traditional K-means and two improved algorithms, the proposed method can improve the clustering accuracy and efficiency by capturing the shape features of smart metering load profiles