MPR-Net:Multi-Scale Pattern Reproduction Guided Universality Time Series Interpretable Forecasting

Time series forecasting has received wide interest from existing research due to its broad applications and inherent challenging. The research challenge lies in identifying effective patterns in historical series and applying them to future forecasting. Advanced models based on point-wise connected MLP and Transformer architectures have strong fitting power, but their secondary computational complexity limits practicality. Additionally, those structures inherently disrupt the temporal order, reducing the information utilization and making the forecasting process uninterpretable. To solve these problems, this paper proposes a forecasting model, MPR-Net. It first adaptively decomposes multi-scale historical series patterns using convolution operation, then constructs a pattern extension forecasting method based on the prior knowledge of pattern reproduction, and finally reconstructs future patterns into future series using deconvolution operation. By leveraging the temporal dependencies present in the time series, MPR-Net not only achieves linear time complexity, but also makes the forecasting process interpretable. By carrying out sufficient experiments on more than ten real data sets of both short and long term forecasting tasks, MPR-Net achieves the state of the art forecasting performance, as well as good generalization and robustness performance

Progressive Scene Text Erasing with Self-Supervision

Scene text erasing seeks to erase text contents from scene images and current state-of-the-art text erasing models are trained on large-scale synthetic data. Although data synthetic engines can provide vast amounts of annotated training samples, there are differences between synthetic and real-world data. In this paper, we employ self-supervision for feature representation on unlabeled real-world scene text images. A novel pretext task is designed to keep consistent among text stroke masks of image variants. We design the Progressive Erasing Network in order to remove residual texts. The scene text is erased progressively by leveraging the intermediate generated results which provide the foundation for subsequent higher quality results. Experiments show that our method significantly improves the generalization of the text erasing task and achieves state-of-the-art performance on public benchmarks

Advancing Model Pruning via Bi-level Optimization

The deployment constraints in practical applications necessitate the pruning of large-scale deep learning models, i.e., promoting their weight sparsity. As illustrated by the Lottery Ticket Hypothesis (LTH), pruning also has the potential of improving their generalization ability. At the core of LTH, iterative magnitude pruning (IMP) is the predominant pruning method to successfully find 'winning tickets'. Yet, the computation cost of IMP grows prohibitively as the targeted pruning ratio increases. To reduce the computation overhead, various efficient 'one-shot' pruning methods have been developed, but these schemes are usually unable to find winning tickets as good as IMP. This raises the question of how to close the gap between pruning accuracy and pruning efficiency? To tackle it, we pursue the algorithmic advancement of model pruning. Specifically, we formulate the pruning problem from a fresh and novel viewpoint, bi-level optimization (BLO). We show that the BLO interpretation provides a technically-grounded optimization base for an efficient implementation of the pruning-retraining learning paradigm used in IMP. We also show that the proposed bi-level optimization-oriented pruning method (termed BiP) is a special class of BLO problems with a bi-linear problem structure. By leveraging such bi-linearity, we theoretically show that BiP can be solved as easily as first-order optimization, thus inheriting the computation efficiency. Through extensive experiments on both structured and unstructured pruning with 5 model architectures and 4 data sets, we demonstrate that BiP can find better winning tickets than IMP in most cases, and is computationally as efficient as the one-shot pruning schemes, demonstrating 2-7 times speedup over IMP for the same level of model accuracy and sparsity.Comment: Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022

Genetically predicted causality between gut microbiota, blood metabolites, and intracerebral hemorrhage: a bidirectional Mendelian randomization study

BackgroundRecent research linked changes in the gut microbiota and serum metabolite concentrations to intracerebral hemorrhage (ICH). However, the potential causal relationship remained unclear. Therefore, the current study aims to estimate the effects of genetically predicted causality between gut microbiota, serum metabolites, and ICH.MethodsSummary data from genome-wide association studies (GWAS) of gut microbiota, serum metabolites, and ICH were obtained separately. Gut microbiota GWAS (N = 18,340) were acquired from the MiBioGen study, serum metabolites GWAS (N = 7,824) from the TwinsUK and KORA studies, and GWAS summary-level data for ICH from the FinnGen R9 (ICH, 3,749 cases; 339,914 controls). A two-sample Mendelian randomization (MR) study was conducted to explore the causal effects between gut microbiota, serum metabolites, and ICH. The random-effects inverse variance-weighted (IVW) MR analyses were performed as the primary results, together with a series of sensitivity analyses to assess the robustness of the results. Besides, a reverse MR was conducted to evaluate the possibility of reverse causation. To validate the relevant findings, we further selected data from the UK Biobank for analysis.ResultsMR analysis results revealed a nominal association (p < 0.05) between 17 gut microbial taxa, 31 serum metabolites, and ICH. Among gut microbiota, the higher level of genus Eubacterium xylanophilum (odds ratio (OR): 1.327, 95% confidence interval (CI):1.154–1.526; Bonferroni-corrected p = 7.28 × 10−5) retained a strong causal relationship with a higher risk of ICH after the Bonferroni corrected test. Concurrently, the genus Senegalimassilia (OR: 0.843, 95% CI: 0.778–0.915; Bonferroni-corrected p = 4.10 × 10−5) was associated with lower ICH risk. Moreover, after Bonferroni correction, only two serum metabolites remained out of the initial 31 serum metabolites. One of the serum metabolites, Isovalerate (OR: 7.130, 95% CI: 2.648–19.199; Bonferroni-corrected p = 1.01 × 10−4) showed a very strong causal relationship with a higher risk of ICH, whereas the other metabolite was unidentified and excluded from further analysis. Various sensitivity analyses yielded similar results, with no heterogeneity or directional pleiotropy observed.ConclusionThis two-sample MR study revealed the significant influence of gut microbiota and serum metabolites on the risk of ICH. The specific bacterial taxa and metabolites engaged in ICH development were identified. Further research is required in the future to delve deeper into the mechanisms behind these findings

Comparison of the feasibility and validity of a one-level and a two-level erector spinae plane block combined with general anesthesia for patients undergoing lumbar surgery

BackgroundSpinal surgery causes severe postoperative pain. An erector spinae plane (ESP) block can relieve postoperative pain, but the optimal blocking method has not been defined. The aim of this study is to compare the feasibility of a one-level and a two-level lumbar ESP block and their effect on intraoperative and postoperative analgesia in lumbar spinal surgery.MethodsA total of 83 adult patients who were scheduled for posterior lumbar interbody fusion were randomly divided into two groups. Patients in Group I (n = 42) received an ultrasound-guided bilateral one-level ESP block with 0.3% ropivacaine, while patients in Group II (n = 41) received a bilateral two-level ESP block. Blocking effectiveness was evaluated, including whether a sensory block covered the surgical incision, sensory decrease in anterior thigh, and quadriceps strength decrease. Intraoperative anesthetic dosage, postoperative visual analogue scale scores of pain, opioid consumption, rescue analgesia, and opioid-related side effects were analyzed.ResultsOf the total number, 80 patients completed the clinical trial and were included in the analysis, with 40 in each group. The time to complete the ESP block was significantly longer in Group II than in Group I (16.0 [14.3, 17.0] min vs. 9.0 [8.3, 9.0] min, P = 0.000). The rate of the sensory block covering the surgical incision at 30 min was significantly higher in Group II than in Group I (100% [40/40] vs. 85.0% [34/40], P = 0.026). The rate of the sensory block in the anterior thigh was higher in Group II (43.8% [35/80] vs. 27.5% [22/80], P = 0.032), but the rate of quadriceps strength decrease did not differ significantly between the groups. The mean effect–site remifentanil concentration during intervertebral decompression was lower in Group II than in Group I (2.9 ± 0.3 ng/ml vs. 3.3 ± 0.5 ng/ml, P = 0.007).There were no significant differences between the groups in terms of intraoperative analgesic consumption, postoperative analgesic consumption, and postoperative VAS pain scores at rest and with movement within 24 h. There were no block failures, block-related complications, and postoperative infection.ConclusionsAmong patients undergoing posterior lumbar interbody fusion, the two-level ESP block provided a higher rate of coverage of the surgical incision by the sensory block when compared with the one-level method, without increasing the incidence of procedure-related complications. Clinical Trial Registrationwww.chictr.org.cn, identifier: ChiCTR210004359

Study on Dynamic Evaluation Method of Stability of Slope Controlled by Structural Plane Based on Deformation Characteristics

The study on deformation characteristics of structural plane is the research foundation of structural plane mechanics and hydraulics. In this paper, a calculation method for dynamic evaluation of the stability of slope controlled by structural plane based on deformation characteristics was proposed on the basis of shear reinforcement three-fold line constitutive model, and it was applied to the example of Raytheon landslide in Chongqing-Guizhou high-speed railway. By comparison, the calculated results were in good agreement with the measured displacement results, and the displacement development process of the dangerous rock mass can be well simulated, thus verifying the feasibility and engineering practicality of the method

The Marketing Effects of Recommender Systems in a B2C E-commerce Context: A Review and Future Directions

As a kind of digital marketing technology, recommender systems (RSs) have already been widely applied for online retailers. Empirical studies have proved that RSs can increase the number of items sold, sell more diverse items, increase the user satisfaction and user fidelity and so on. However, our understanding of the marketing effects of RSs is still fragmented. Few comprehensive literature reviews has been published. This paper mainly reviews and synthesizes extant related literature in the last five years on the marketing effects of RSs, specifically focuses on how RSs influence consumers’ decision quality ,product demand and retailer profits in e-commerce market and e-commerce companies. From the angles of consumer behavior and marketing strategies, this study aims to discuss the positive and negative impacts which RSs bring to consumer and its providers, and presents some suggestions and potential directions for future research on RSs

A retrospective study of analgesia efficacy and its side effect in 127 patients undergoing selective neurosurgery

Objective To investigate the analgesia efficacy and the impact of age on it after selective craniectomy, and to study risk factors of analgesia side effects. Methods One hundred and twenty-seven patients undergoing selective craniectomy were enrolled in this study. All patients were administered with fentanyl and ondansetron to produce continuous intravenous postoperative analgesia. Patients were evaluated by Visual Analog Score (VAS), Ramsay score and the impact on their mobility status. Heart rate (HR), mean blood pressure (MBP) and respiratory rate (RR) were recorded at preoperative time, and 24 h and 48 h after operation. We mainly focused on the incidence of postoperative pain and side effects of analgesia (such as nausea and vomiting, urinary retention, pruritus and exhaust time). Results There were statistic differences in MBP and RR among 3 groups (P = 0.000, for all), but all within normal range. Total rate of excellent analgesia was 84.25% (107/127), and there was no statistic difference in VAS among 3 groups (P > 0.05, for all). The VAS (at rest and mobility status) at 48 h was significantly lower than at 24 h after surgery (P = 0.000, for all). Total incidence of postoperative nausea and vomiting (PONV) was 29.13% (37/127), and total incidence of urinary retention was 14.96% (19/127). There was no statistic difference in the incidence of PONV and urinary retention among 3 groups (P > 0.05, for all). The risk factor of PONV was gender (P = 0.022). American Society of Anesthesiologists (ASA) score was related to mental state (rs = 0.202, P = 0.023) and mobility status (rs = 0.221, P = 0.013). Age was related to mental state (rs = 0.945, P = 0.015) and mobility status (rs = 0.940, P = 0.020). ASA score also had a correlation with pruritus (rs = 0.212, P = 0.017). Conclusion Fentanyl combined with ondansetron can produce a good continuous intravenous postoperative analgesia for patients undergoing craniectomy. The risk factor of PONV is gender. Mental state and mobility status are related to ASA score and age. DOI:10.3969/j.issn.1672-6731.2011.04.01