Matching Natural Language Sentences with Hierarchical Sentence Factorization

Semantic matching of natural language sentences or identifying the relationship between two sentences is a core research problem underlying many natural language tasks. Depending on whether training data is available, prior research has proposed both unsupervised distance-based schemes and supervised deep learning schemes for sentence matching. However, previous approaches either omit or fail to fully utilize the ordered, hierarchical, and flexible structures of language objects, as well as the interactions between them. In this paper, we propose Hierarchical Sentence Factorization---a technique to factorize a sentence into a hierarchical representation, with the components at each different scale reordered into a "predicate-argument" form. The proposed sentence factorization technique leads to the invention of: 1) a new unsupervised distance metric which calculates the semantic distance between a pair of text snippets by solving a penalized optimal transport problem while preserving the logical relationship of words in the reordered sentences, and 2) new multi-scale deep learning models for supervised semantic training, based on factorized sentence hierarchies. We apply our techniques to text-pair similarity estimation and text-pair relationship classification tasks, based on multiple datasets such as STSbenchmark, the Microsoft Research paraphrase identification (MSRP) dataset, the SICK dataset, etc. Extensive experiments show that the proposed hierarchical sentence factorization can be used to significantly improve the performance of existing unsupervised distance-based metrics as well as multiple supervised deep learning models based on the convolutional neural network (CNN) and long short-term memory (LSTM).Comment: Accepted by WWW 2018, 10 page

Adaptive absorbing boundary conditions for Schrodinger-type equations: application to nonlinear and multi-dimensional problems

We propose an adaptive approach in picking the wave-number parameter of absorbing boundary conditions for Schr\"{o}dinger-type equations. Based on the Gabor transform which captures local frequency information in the vicinity of artificial boundaries, the parameter is determined by an energy-weighted method and yields a quasi-optimal absorbing boundary conditions. It is shown that this approach can minimize reflected waves even when the wave function is composed of waves with different group velocities. We also extend the split local absorbing boundary (SLAB) method [Z. Xu and H. Han, {\it Phys. Rev. E}, 74(2006), pp. 037704] to problems in multidimensional nonlinear cases by coupling the adaptive approach. Numerical examples of nonlinear Schr\"{o}dinger equations in one- and two dimensions are presented to demonstrate the properties of the discussed absorbing boundary conditions.Comment: 18 pages; 12 figures. A short movie for the 2D NLS equation with absorbing boundary conditions can be downloaded at http://home.ustc.edu.cn/~xuzl/movie.avi. To appear in Journal of Computational Physic

The Ecological Restoration of Heavily Degraded Saline Wetland in the Yellow River Delta

As a result of discontinuous water flow, agriculture, and increasing urban use of fresh water affecting the natural wetlands of the Yellow River Delta, these areas have experienced significant degradation in the past two decades, ultimately diminishing the overall natural wetland land area in the region. This study aimed to address the issue of decreasing fresh water in the Yellow River Delta by studying the effects of three different approaches to restoration on long-term wetland recovery. The results of the study demonstrated that soil salt and available Na contents significantly decreased in response to all three restoration treatments. Impacts of the restoration treatments were more significant in 2009 than in 2010, as shown by the high rate of activity in the reed debris group. The highest phosphatase activity of the experimental period was also observed in the reed debris group. Meanwhile, a marked variation in soil nutrient elements (total carbon (TC), total nitrogen (TN), available phosphorus, and available potassium) was observed in the restoration treatment plots throughout the experimental period. TC and TN contents were generally higher in the restoration treatment groups than in the control group. Moreover, urease and phosphatase activity levels were highly correlated with one another, as well as with soil nutrient elements. In 2009, the yield of the Suaeda salsa plant was highest in the reed debris treatment group and lowest in the ploughing treatment group. The S. salsa plant did show a positive response to all of the different restoration treatments. Taken together, these results suggest that restoration approaches that implement ploughing techniques aided in the restoration of degraded saline wetlands.As a result of discontinuous water flow, agriculture, and increasing urban use of fresh water affecting the natural wetlands of the Yellow River Delta, these areas have experienced significant degradation in the past two decades, ultimately diminishing the overall natural wetland land area in the region. This study aimed to address the issue of decreasing fresh water in the Yellow River Delta by studying the effects of three different approaches to restoration on long-term wetland recovery. The results of the study demonstrated that soil salt and available Na contents significantly decreased in response to all three restoration treatments. Impacts of the restoration treatments were more significant in 2009 than in 2010, as shown by the high rate of activity in the reed debris group. The highest phosphatase activity of the experimental period was also observed in the reed debris group. Meanwhile, a marked variation in soil nutrient elements (total carbon (TC), total nitrogen (TN), available phosphorus, and available potassium) was observed in the restoration treatment plots throughout the experimental period. TC and TN contents were generally higher in the restoration treatment groups than in the control group. Moreover, urease and phosphatase activity levels were highly correlated with one another, as well as with soil nutrient elements. In 2009, the yield of the Suaeda salsa plant was highest in the reed debris treatment group and lowest in the ploughing treatment group. The S. salsa plant did show a positive response to all of the different restoration treatments. Taken together, these results suggest that restoration approaches that implement ploughing techniques aided in the restoration of degraded saline wetlands

Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes

Object detection via inaccurate bounding boxes supervision has boosted a broad interest due to the expensive high-quality annotation data or the occasional inevitability of low annotation quality (\eg tiny objects). The previous works usually utilize multiple instance learning (MIL), which highly depends on category information, to select and refine a low-quality box. Those methods suffer from object drift, group prediction and part domination problems without exploring spatial information. In this paper, we heuristically propose a \textbf{Spatial Self-Distillation based Object Detector (SSD-Det)} to mine spatial information to refine the inaccurate box in a self-distillation fashion. SSD-Det utilizes a Spatial Position Self-Distillation \textbf{(SPSD)} module to exploit spatial information and an interactive structure to combine spatial information and category information, thus constructing a high-quality proposal bag. To further improve the selection procedure, a Spatial Identity Self-Distillation \textbf{(SISD)} module is introduced in SSD-Det to obtain spatial confidence to help select the best proposals. Experiments on MS-COCO and VOC datasets with noisy box annotation verify our method's effectiveness and achieve state-of-the-art performance. The code is available at https://github.com/ucas-vg/PointTinyBenchmark/tree/SSD-Det.Comment: accepted by ICCV 202

Timing of Maximal Weight Reduction Following Bariatric Surgery: A Study in Chinese Patients

Introduction: Bariatric surgery is a well-received treatment for obesity with maximal weight loss at 12–36 months postoperatively. We investigated the effect of early bariatric surgery on weight reduction of Chinese patients in accordance with their preoperation characteristics. Materials and Methods: Altogether, 409 patients with obesity from a prospective cohort in a single bariatric center were enrolled retrospectively and evaluated for up to 4 years. Measurements obtained included surgery type, duration of diabetic condition, besides the usual body mass index data tuple. Weight reduction was expressed as percent total weight loss (%TWL) and percent excess weight loss (%EWL). Results: RYGB or SG were performed laparoscopically without mortality or complications. BMI generally plateaued at 12 months, having decreased at a mean of 8.78 kg/m2. Successful weight loss of \u3e 25% TWL was achieved by 35.16, 49.03, 39.22, 27.74, 20.83% of patients at 6, 12, 24, 36, and 48 months after surgery. Overall, 52.91% of our patients had lost 100% of their excess weight at 12 months, although there was a rather wide range among individuals. Similar variability was revealed in women of child-bearing age. Conclusion: Chinese patients undergoing bariatric surgery tend to achieve maximal weight loss and stabilization between 12 and 24 months postoperatively, instead of at \u3e 2 years. The finding of the shorter stabilization interval has importance to earlier intervention of weight loss related conditions and women\u27s conception planning

Enhancement of the superconductivity and quantum metallic state in the thin film of superconducting Kagome metal KV3_3Sb5_5

Recently V-based Kagome metal attracted intense attention due to the emergence of superconductivity in the low temperature. Here we report the fabrication and physical investigations of the high quality single-crystalline thin films of the Kagome metal KV$_3$Sb$_5$. For the sample with the thickness of about 15 nm, the temperature dependent resistance reveals a Berezinskii-Kosterlitz-Thouless (BKT) type behavior, indicating the presence of two-dimensional superconductivity. Compared with the bulk sample, the onset transition temperature $T^{onset}_{c}$ and the out-of-plane upper critical field $H_{c2}$ are enhanced by 15\% and more than 10 times respectively. Moreover, the zero-resistance state is destroyed by a magnetic field as low as 50 Oe. Meanwhile, the temperature-independent resistance is observed in a wide field region, which is the hallmark of quantum metallic state. Our results provide evidences for the existence of unconventional superconductivity in this material.Comment: 5 pages, 4 figure