Mixed Norm Equalization with Applications in Television Multipath Cancellation

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Three dimension high definition manometry evaluated postoperative anal canal functions in children with congenital anorectal malformations

BackgroundWe aimed to evaluate the function of the reconstructed anal canal in postoperative anorectal malformations (ARMs) patients through three dimension (3D) high-definition anorectal manometry.MethodsFrom January 2015 to December 2019, 3D manometry was performed as a postoperative functional assessment of patients with ARMs divided into age subgroups based on the time of manometry. Manometric parameters, such as the length of the anorectal high-pressure zone (HPZ-length), the mean resting and squeeze pressure of HPZ (HPZ-rest and HPZ-sqze), recto-anal inhibitory reflex (RAIR), and strength distribution of the anal canal, were collected and compared with age-matched controls. Their functional outcomes were analyzed with SPSS 23.0 software for statistical analysis.Results171 manometric measurements were performed on 142 postoperative patients (3 months∼15 years). The HPZ-rest in all patients was significantly lower than in age-matched controls (p < 0.05). HPZ-sqze was notably decreased in patients older than 4 years, whereas other age groups were comparable to controls (p < 0.05). The proportions of asymmetric strength distribution and negative RAIR were higher in ARMs patients. The type of anorectal malformations and lower HPZ-rest were the impact factors affecting postoperative functional outcomes.ConclusionsThe majority of the ARMs patients had acceptable functional outcomes. 3D manometry can objectively assess the reconstructed anal canal function. The patients with fecal incontinence had a high proportion of extremely low HPZ-rest and HPZ-sqze, negative RAIR, and asymmetric strength distribution. The manometric details will help the clinicians explore the causes of defecation complications and guide further management

Rifaximin Alters Intestinal Microbiota and Prevents Progression of Ankylosing Spondylitis in Mice

Recently, accumulating evidence has suggested that gut microbiota may be involved in the occurrence and development of ankylosing spondylitis (AS). It has been suggested that rifaximin have the ability to modulate the gut bacterial communities, prevent inflammatory response, and modulate gut barrier function. The goal of this work is to evaluate the protective effects of rifaximin in fighting AS and to elucidate the potential underlying mechanism. Rifaximin were administered to the proteoglycan (PG)-induced AS mice for 4 consecutive weeks. The disease severity was measured with the clinical and histological of arthritis and spondylitis. Intestinal histopathological, pro-inflammatory cytokine levels and the intestinal mucosal barrier were evaluated. Then, western blot was performed to explore the toll-like receptor 4 (TLR-4) signal transducer and NF-κB expression. Stool samples were collected to analyze the differences in the gut microbiota via next-generation sequencing of 16S rDNA. We found that rifaximin significantly reduced the severity of AS and resulted in down-regulation of inflammatory factors, such as TNF-α, IL-6, IL-17A, and IL-23. Meanwhile, rifaximin prevented ileum histological alterations, restored intestinal barrier function and inhibited TLR-4/NF-κB signaling pathway activation. Rifaximin also changed the gut microbiota composition with increased Bacteroidetes/Firmicutes phylum ratio, as well as selectively promoting some probiotic populations, including Lactobacillales. Our results suggest that rifaximin suppressed progression of AS and regulated gut microbiota in AS mice. Rifaximin might be useful as a novel treatment for AS

A multicentre single arm phase 2 trial of neoadjuvant pyrotinib and letrozole plus dalpiciclib for triple-positive breast cancer.

peer reviewedCurrent therapies for HER2-positive breast cancer have limited efficacy in patients with triple-positive breast cancer (TPBC). We conduct a multi-center single-arm phase 2 trial to test the efficacy and safety of an oral neoadjuvant therapy with pyrotinib, letrozole and dalpiciclib (a CDK4/6 inhibitor) in patients with treatment-naïve, stage II-III TPBC with a Karnofsky score of ≥70 (NCT04486911). The primary endpoint is the proportion of patients with pathological complete response (pCR) in the breast and axilla. The secondary endpoints include residual cancer burden (RCB)-0 or RCB-I, objective response rate (ORR), breast pCR (bpCR), safety and changes in molecular targets (Ki67) from baseline to surgery. Following 5 cycles of 4-week treatment, the results meet the primary endpoint with a pCR rate of 30.4% (24 of 79; 95% confidence interval (CI), 21.3-41.3). RCB-0/I is 55.7% (95% CI, 44.7-66.1). ORR is 87.4%, (95% CI, 78.1-93.2) and bpCR is 35.4% (95% CI, 25.8-46.5). The mean Ki67 expression reduces from 40.4% at baseline to 17.9% (P < 0.001) at time of surgery. The most frequent grade 3 or 4 adverse events are neutropenia, leukopenia, and diarrhoea. There is no serious adverse event- or treatment-related death. This fully oral, chemotherapy-free, triplet combined therapy has the potential to be an alternative neoadjuvant regimen for patients with TPBC

The Regularization Method for an Obstacle Problem

. We give a relatively complete analysis for the regularization method, which is usually used in solving non-differentiable minimization problems. The model problem considered in the paper is an obstacle problem. In addition to the usual convergence result and a-priori error estimates, we provide a-posteriori error estimates which are highly desired for practical implementation of the regularization method. 1 An obstacle problem The purpose of the paper is to give a relatively complete analysis of the regularization method for solving non-differentiable minimization problems. In addition to the usual convergence analysis and a-priori error estimates, we will also provide a-posteriori error estimates. The model problem to be solved is an obstacle problem considered in [15]. Let\Omega be a Lipschitz domain. Let g 2 H 1=2 (@ \Omega\Gamma be non-negative. Denote the energy functional E(v) = Z \Omega ` 1 2 jrvj 2 + v &apos; dx (1.1) 1 Department of Mathematics, Hong Kong Baptist Col..

Extrapolation of Numerical Solutions for Elliptic Problems on Corner Domains

Introduction The Richardson extrapolation technique is an efficient approach to increase the accuracy of numerical solutions of mathematical problems. The success of the extrapolation technique relies on the existence of asymptotic error expansions. The survey paper [9] summarizes many important results, available up to 1971, on the application of extrapolation in numerical 1 Department of Mathematics, Hong Kong Baptist University, Kowloon, Hong Kong. The work of this author was supported by Research Grants Council of the Hong Kong UPGC. 2 Department of Mathematics, University of Iowa, Iowa City, IA 52242, U.S.A. integration and numerical ODEs. The monograph [11] presents a systematic treatment of the application of the extrapolation technique on the finite difference method for solving ordinary and partial differential equations, as well as on methods for solving singular linear systems and integral equations. The extrapolati

Data-Driven Reinforcement-Learning-Based Automatic Bucket-Filling for Wheel Loaders

Automation of bucket-filling is of crucial significance to the fully automated systems for wheel loaders. Most previous works are based on a physical model, which cannot adapt to the changeable and complicated working environment. Thus, in this paper, a data-driven reinforcement-learning (RL)-based approach is proposed to achieve automatic bucket-filling. An automatic bucket-filling algorithm based on Q-learning is developed to enhance the adaptability of the autonomous scooping system. A nonlinear, non-parametric statistical model is also built to approximate the real working environment using the actual data obtained from tests. The statistical model is used for predicting the state of wheel loaders in the bucket-filling process. Then, the proposed algorithm is trained on the prediction model. Finally, the results of the training confirm that the proposed algorithm has good performance in adaptability, convergence, and fuel consumption in the absence of a physical model. The results also demonstrate the transfer learning capability of the proposed approach. The proposed method can be applied to different machine-pile environments

Effective Incomplete Multi-View Clustering via Low-Rank Graph Tensor Completion

In the past decade, multi-view clustering has received a lot of attention due to the popularity of multi-view data. However, not all samples can be observed from every view due to some unavoidable factors, resulting in the incomplete multi-view clustering (IMC) problem. Up until now, most efforts for the IMC problem have been made on the learning of consensus representations or graphs, while many missing views are ignored, making it impossible to capture the information hidden in the missing view. To overcome this drawback, we first analyzed the low-rank relationship existing inside each graph and among all graphs, and then propose a novel method for the IMC problem via low-rank graph tensor completion. Specifically, we first stack all similarity graphs into a third-order graph tensor and then exploit the low-rank relationship from each mode using the matrix nuclear norm. In this way, the connection hidden between the missing and available instances can be recovered. The consensus representation can be learned from all completed graphs via multi-view spectral clustering. To obtain the optimal multi-view clustering result, incomplete graph recovery and consensus representation learning are integrated into a joint framework for optimization. Extensive experimental results on several incomplete multi-view datasets demonstrate that the proposed method can obtain a better clustering performance in comparison with state-of-the-art incomplete multi-view clustering methods

Joint estimation of head pose and visual focus of attention.

International audienceHead pose is an important indicator of a person's visual focus of attention (VFoA). A traditional way to recognize VFoA is to consider accurate head pose or gaze estimations. However, these estimations usually degrade drastically in middle or low resolution video data. In this paper, a joint estimation of head pose and VFoA is proposed to address this issue; both head pose and VFoA are iteratively refined until convergence. This approach is evaluated in a specific scenario involving children around a table playing together with toys. Datasets are acquired and annotated by psychologists in Peking university. The experimental results demonstrate the usefulness of the join estimation process to recognize visual focus of attention in middle resolution video sequences

Effect of Flume Width on the Hydraulic Properties of Overland Flow from Laboratory Observation

The effect of flume width (b) on overland flow dynamics was investigated in this study. Experiments were conducted with five different flow discharges and five flume widths (0.05–0.30 m, with an interval of 0.05 m). The findings revealed that a narrow flume had a noticeable impact on flow acceleration as the slope length increased. Relative average deviation (RAD) was calculated to evaluate the influence of sidewall effects on flow velocity. The coefficient of variation in the RAD ranged from 1.90% to 3.65%. The RAD has extremely significant differences between different widths when the flow is 0.02–0.08 m2/min. The significant differences in the RAD at different widths decrease as the flow rate increases. The flow regime was evaluated using the ratio of the thickness of the viscous sublayer to the water depth (δ/h), which proved to be a better indicator than the Reynolds number for studying flow regimes in different flume widths. Furthermore, it was observed that the energy variation was smaller in narrow flumes (b = 0.5–0.10 m) compared to wider flumes (b = 0.25–0.30 m). When the flume width ranged from 0.15 to 0.30 m, the specific energy change increased. These results contribute to further understanding of the hydraulic characteristics of overland flow and provide theoretical references for optimizing experimental design