A Deep Architecture for Semantic Matching with Multiple Positional Sentence Representations

Matching natural language sentences is central for many applications such as information retrieval and question answering. Existing deep models rely on a single sentence representation or multiple granularity representations for matching. However, such methods cannot well capture the contextualized local information in the matching process. To tackle this problem, we present a new deep architecture to match two sentences with multiple positional sentence representations. Specifically, each positional sentence representation is a sentence representation at this position, generated by a bidirectional long short term memory (Bi-LSTM). The matching score is finally produced by aggregating interactions between these different positional sentence representations, through $k$-Max pooling and a multi-layer perceptron. Our model has several advantages: (1) By using Bi-LSTM, rich context of the whole sentence is leveraged to capture the contextualized local information in each positional sentence representation; (2) By matching with multiple positional sentence representations, it is flexible to aggregate different important contextualized local information in a sentence to support the matching; (3) Experiments on different tasks such as question answering and sentence completion demonstrate the superiority of our model.Comment: Accepted by AAAI-201

Non-seismic geophysical prospecting model of Beiya gold mine in Western Yunnan Province

According to the basic rules and characteristics of the gold-polymetallic deposits of Beiya gold mine area in terms of mineralization and ore controlling, it is concluded that skarn deposit is the main ore deposit type in this area and the geological conditions are analyzed by the statistics of the physical parameters. Then, the tectonic, rocks, stratum, ore geophysical models have been treated by the forward modeling numerical simulation and the results are analyzed comprehensively. Based on the forward modeling results, combined with the relevant physical differences, the principle and exploration method test and research for the comprehensive geophysical exploration technology has been carried out, covering the induced polarization and magnetic prospecting for the ore body as well as the indirect geophysical exploration method by means of plane gravity data, audio-magnetotelluric sounding for rock mass and tectonics, the mineralization mode-physical forward modeling - geophysical exploration mode has been established and good results have been achieved. Therefore, a location forecast method has been put forward for the concealed skarn type Fe-Au deposit which is adaptive to the mineralized geological background of Beiya and other similar areas

Foreword

Extraction of the aorto-femoral vessel trajectory is important to utilize computed tomography angiography (CTA) in an integrated workflow of the image-guided work-up prior to trans-catheter aortic valve replacement (TAVR). The aim of this study was to develop a new, fully-automated technique for the extraction of the entire arterial access route from the femoral artery to the aortic root. An automatic vessel tracking algorithm was first used to find the centerline that connected the femoral accessing points and the aortic root. Subsequently, a deformable 3D-model fitting method was used to delineate the lumen boundary of the vascular trajectory in the whole-body CTA

Learning Contextualized Document Representations for Healthcare Answer Retrieval

We present Contextual Discourse Vectors (CDV), a distributed document representation for efficient answer retrieval from long healthcare documents. Our approach is based on structured query tuples of entities and aspects from free text and medical taxonomies. Our model leverages a dual encoder architecture with hierarchical LSTM layers and multi-task training to encode the position of clinical entities and aspects alongside the document discourse. We use our continuous representations to resolve queries with short latency using approximate nearest neighbor search on sentence level. We apply the CDV model for retrieving coherent answer passages from nine English public health resources from the Web, addressing both patients and medical professionals. Because there is no end-to-end training data available for all application scenarios, we train our model with self-supervised data from Wikipedia. We show that our generalized model significantly outperforms several state-of-the-art baselines for healthcare passage ranking and is able to adapt to heterogeneous domains without additional fine-tuning.Comment: The Web Conference 2020 (WWW '20

In vivo comparison of arterial lumen dimensions assessed by co-registered three-dimensional (3D) quantitative coronary angiography, intravascular ultrasound and optical coherence tomography

This study sought to compare lumen dimensions as assessed by 3D quantitative coronary angiography (QCA) and by intravascular ultrasound (IVUS) or optical coherence tomography (OCT), and to assess the association of the discrepancy with vessel curvature. Coronary lumen dimensions often show discrepancies when assessed by X-ray angiography and by IVUS or OCT. One source of error concerns a possible mismatch in the selection of corresponding regions for the comparison. Therefore, we developed a novel, real-time co-registration approach to guarantee the point-to-point correspondence between the X-ray, IVUS and OCT images. A total of 74 patients with indication for cardiac catheterization were retrospectively included. Lumen morphometry was performed by 3D QCA and IVUS or OCT. For quantitative analysis, a novel, dedicated approach for co-registration and lumen detection was employed allowing for assessment of lumen size at multiple positions along the vessel. Vessel curvature was automatically calculated from the 3D arterial vessel centerline. Comparison of 3D QCA and IVUS was performed in 519 distinct positions in 40 vessels. Correlations were r = 0.761, r = 0.790, and r = 0.799 for short diameter (SD), long diameter (LD), and area, respectively. Lumen sizes were larger by IVUS (P < 0.001): SD, 2.51 ± 0.58 mm versus 2.34 ± 0.56 mm; LD, 3.02 ± 0.62 mm versus 2.63 ± 0.58 mm; Area, 6.29 ± 2.77 mm2versus 5.08 ± 2.34 mm2. Comparison of 3D QCA and OCT was performed in 541 distinct positions in 40 vessels. Correlations were r = 0.880, r = 0.881, and r = 0.897 for SD, LD, and area, respectively. Lumen sizes were larger by OCT (P < 0.001): SD, 2.70 ± 0.65 mm versus 2.57 ± 0.61 mm; LD, 3.11 ± 0.72 mm versus 2.80 ± 0.62 mm; Area 7.01 ± 3.28 mm2versus 5.93 ± 2.66 mm2. The vessel-based discrepancy between 3D QCA and IVUS or OCT long diameters increased with increasing vessel curvature. In conclusion, our comparison of co-registered 3D QCA and invasive imaging data suggests a bias towards larger lume

Monitoring Opportunistic Pathogens in Domestic Wastewater from a Pilot-Scale Anaerobic Biofilm Reactor to Reuse in Agricultural Irrigation

Wastewater reuse for agricultural irrigation in many developing countries is an increasingly common practice. Regular monitoring of indicators can help to identify potential health risks; therefore, there is an urgent need to understand the presence and abundance of opportunistic pathogens in wastewater, as well as plant phyllosphere and rhizosphere. In this study, an anaerobic biofilm reactor (ABR) was developed to treat rural domestic wastewater; the performance of pollutants removal and pathogenic bacteria elimination were investigated. Additionally, we also assessed the physicochemical and microbiological profiles of soil and lettuces after wastewater irrigation. Aeromonas hydrophila, Arcobacter sp., Bacillus cereus, Bacteroides sp., Escherichia coli, Legionella sp., and Mycobacterium sp. were monitored in the irrigation water, as well as in the phyllosphere and rhizosphere of lettuces. Pathogens like B. cereus, Legionella sp. and Mycobacterium sp. were present in treated effluent with relatively high concentrations, and the levels of A. hydrophila, Arcobacter sp., and E. coli were higher in the phyllosphere. The physicochemical properties of soil and lettuce did not vary significantly. These data indicated that treated wastewater irrigation across a short time period may not alter the soil and crop properties, while the pathogens present in the wastewater may transfer to soil and plant, posing risks to human health

Transcriptomic Sequencing Analysis on Key Genes and Pathways Regulating Cadmium (Cd) in Ryegrass (Lolium&nbsp;perenne L.) under Different Cadmium Concentrations

Perennial ryegrass (Lolium&nbsp;perenne L.) is an important forage grass and has the potential to be used in phytoremediation, while little information is available regarding the transcriptome profiling of ryegrass leaves in response to high levels of Cd. To investigate and uncover the physiological responses and gene expression characteristics of perennial ryegrass under Cd stress, a pot experiment was performed to study the transcriptomic profiles of ryegrass with Cd-spiked soils. Transcriptome sequencing and comparative analysis were performed on the Illumina RNA-Seq platform at different concentrations of Cd-treated (0, 50 and 500 mg&middot;kg&minus;1 soil) ryegrass leaves and differentially expressed genes (DEGs) were verified by RT-qPCR. The results show that high concentrations of Cd significantly inhibited the growth of ryegrass, while the lower concentrations (5 and 25 mg&middot;kg&minus;1) showed minor effects. The activity levels of antioxidant enzymes such as superoxide dismutase (SOD), peroxidase (POD), catalase (CAT) and malondialdehyde (MDA) increased in Cd-treated ryegrass leaves. We identified 1103 differentially expressed genes (DEGs) and profiled the molecular regulatory pathways of ryegrass leaves with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis in response to Cd stress. Cd stress significantly increased the membrane part, the metabolic process, the cellular process and catalytic activity. The numbers of unigenes related to signal transduction mechanisms, post-translational modification, replication, recombination and repair significantly increased. KEGG function annotation and enrichment analysis were performed based on DEGs with different treatments, indicating that the MAPK signaling pathway, the mRNA surveillance pathway and RNA transport were regulated significantly. Taken together, this study explores the effect of Cd stress on the growth physiology and gene level of ryegrass, thus highlighting significance of preventing and controlling heavy metal pollution in the future

Insights into the toxicities of UV-328, UV-329, UV-P in HepG2 cells and their roles in AHR-mediated pathway

The widespread high concentrations of benzotriazole ultraviolet stabilizers (BUVSs) in many biotic and abiotic samples have raised urgent concerns of their adverse effects on environmental and human health. In this study, we investigated the toxicity of three typical BUVSs (UV-328, UV-329, UV-P) with HepG2 cells in vitro. Results indicated that the three BUVSs showed weak cytotoxicity in HepG2 cells at concentrations lower than 50 μM. Transcriptional analysis indicated that the toxic effects of the three chemicals followed the order of UV-P > UV-329 > UV-328. UV-P and UV-329 may act as potential environmental diabetogens by significantly enriching several diabetic related items in both GO and KEGG analysis. Moreover, UV-P and UV-329 significantly upregulated the expression of AHR target genes (CYP1A1, CYP1A2, UGT1A1, etc.), and increased the ethoxyresorufin-O-deethylase (EROD) activity and exhibited agonistic activity toward AHR in the XRE-mediated luciferase reporter gene assay. Molecular docking assay also indicated that UV-329 and UV-P had higher binding affinities to AHR-LBD than UV-328. In brief, our findings indicated that UV-P and UV-329 were potential agonist of AHR ligand, and may exert more toxicity than UV-328 in inducing liver toxicity