Implicit Discourse Relation Classification via Multi-Task Neural Networks

Without discourse connectives, classifying implicit discourse relations is a challenging task and a bottleneck for building a practical discourse parser. Previous research usually makes use of one kind of discourse framework such as PDTB or RST to improve the classification performance on discourse relations. Actually, under different discourse annotation frameworks, there exist multiple corpora which have internal connections. To exploit the combination of different discourse corpora, we design related discourse classification tasks specific to a corpus, and propose a novel Convolutional Neural Network embedded multi-task learning system to synthesize these tasks by learning both unique and shared representations for each task. The experimental results on the PDTB implicit discourse relation classification task demonstrate that our model achieves significant gains over baseline systems.Comment: This is the pre-print version of a paper accepted by AAAI-1

Observation of damage initiation for trans-laminar fracture using in situ fast synchrotron x-ray radiography and ex situ x-ray computed tomography

Trans-laminar fracture is an important topic for engineering composites. In this study, trans-laminar fracture initiation in quasi-isotropic carbon/epoxy laminates made of non-crimp fabrics was examined using in situ fast synchrotron X-ray radiography and ex situ X-ray computed tomography. The maximum split lengths were measured by in situ radiography and were compared with the predicted values in a detailed FE model using cohesive elements. Ex situ computed tomography scans were also conducted to confirm that no fibre breakage occurs before the final load drop in the experiments. In situ and ex situ observations are complementary for the understanding of damage initiation

Fully Inkjet-Printed, 2D Materials-Based Field-Effect Transistor for Water Sensing

Despite significant progress in solution-processing of 2D materials, it remains challenging to reliably print high-performance semiconducting channels that can be efficiently modulated in a field-effect transistor (FET). Herein, electrochemically exfoliated MoS2 nanosheets are inkjet-printed into ultrathin semiconducting channels, resulting in high on/off current ratios up to 103. The reported printing strategy is reliable and general for thin film channel fabrication even in the presence of the ubiquitous coffee-ring effect. Statistical modeling analysis on the printed pattern profiles suggests that a spaced parallel printing approach can overcome the coffee-ring effect during inkjet printing, resulting in uniform 2D flake percolation networks. The uniformity of the printed features allows the MoS2 channel to be hundreds of micrometers long, which easily accommodates the typical inkjet printing resolution of tens of micrometers, thereby enabling fully printed FETs. As a proof of concept, FET water sensors are demonstrated using printed MoS2 as the FET channel, and printed graphene as the electrodes and the sensing area. After functionalization of the sensing area, the printed water sensor shows a selective response to Pb2+ in water down to 2 ppb. This work paves the way for additive nanomanufacturing of FET-based sensors and related devices using 2D nanomaterials

Effects of water stress on starch synthesis and accumulation of two rice cultivars at different growth stages

Rice is a water intensive crop and soil water conditions affect rice yield and quality. However, there is limited research on the starch synthesis and accumulation of rice under different soil water conditions at different growth stages. Thus, a pot experiment was conducted to explore the effects of IR72 (indica) and Nanjing (NJ) 9108 (japonica) rice cultivars under flood-irrigated treatment (CK, 0 kPa), light water stress treatment (L, -20 ± 5 kPa), moderate water stress treatment (M, -40 ± 5 kPa) and severe water stress treatment (S, -60 ± 5 kPa) on the starch synthesis and accumulation and rice yield at booting stage (T1), flowering stage (T2) and filling stage (T3), respectively. Under LT treatment, the total soluble sugar and sucrose contents of both cultivars decreased while the amylose and total starch contents increased. Starch synthesis-related enzyme activities and their peak activities at mid-late growth stage increased as well. However, applying MT and ST treatments produced the opposite effects. The 1000-grain weight of both cultivars increased under LT treatment while the seed setting rate increased only under LT3 treatment. Compared with CK, water stress at booting stage decreased grain yield. The principal component analysis (PCA) showed that LT3 got the highest comprehensive score while ST1 got lowest for both cultivars. Furthermore, the comprehensive score of both cultivars under the same water stress treatment followed the trend of T3 > T2 > T1, and NJ 9108 had a better drought-resistant ability than IR72. Compared with CK, the grain yield under LT3 increased by 11.59% for IR72 and 16.01% for NJ 9108, respectively. Overall, these results suggested that light water stress at filling stage could be an effective method to enhance starch synthesis-related enzyme activities, promote starch synthesis and accumulation and increase grain yield

Functional expression and characterization of an archaeal aquaporin. AqpM from methanothermobacter marburgensis.

Researchers have described aquaporin water channels from diverse eubacterial and eukaryotic species but not from the third division of life, Archaea. Methanothermobacter marburgensis is a methanogenic archaeon that thrives under anaerobic conditions at 65 °C. After transfer to hypertonic media,M. marburgensis sustained cytoplasmic shrinkage that could be prevented with HgCl2. We amplified aqpM by PCR from M. marburgensis DNA. Like known aquaporins, the open reading frame of aqpM encodes two tandem repeats each containing three membrane-spanning domains and a pore-forming loop with the signature motif Asn-Pro-Ala (NPA). Unlike other known homologs, the putative Hg2+-sensitive cysteine was found proximal to the first NPA motif in AqpM, rather than the second. Moreover, amino acids distinguishing water-selective homologs from glycerol-transporting homologs were not conserved in AqpM. A fusion protein, 10-His-AqpM, was expressed and purified from Escherichia coli. AqpM reconstituted into proteoliposomes was shown by stopped-flow light scattering assays to have elevated osmotic water permeability (P f = 57 μm·s−1 versus12 μm·s−1 of control liposomes) that was reversibly inhibited with HgCl2. Transient, initial glycerol permeability was also detected. AqpM remained functional after incubations at temperatures above 80 °C and formed SDS-stable tetramers. Our studies of archaeal AqpM demonstrate the ubiquity of aquaporins in nature and provide new insight into protein structure and transport selectivity. To withstand environmental and physiological stresses, organisms must be able to rapidly absorb and release water. Facilitated transport of water across cell membranes must be highly selective to prevent uncontrolled movement of other solutes, protons, and ions. Discovery of the aquaporins provided a molecular explanation to these processes (2). More than 200 aquaporins have now been identified, and their presence has been established in most forms of life (3). No aquaporin from Archaea has yet been characterized, although functional roles for a water channel protein have been predicted in these organisms (4). Two major protein family subsets are presently recognized, water-selective channels (aquaporins) and glycerol-transporting homologs with varying water permeabilities (aquaglyceroporins). The permeation selectivity of new members of the protein family may be predicted by a small number of conserved residues (5, 6). Several prokaryotic aquaporins and aquaglyceroporins are known. The bacterial water channel, AqpZ, was first identified in Escherichia coli (7, 8). Movement of water across the bacterial plasma membrane may be part of the osmoregulatory response by which microorganisms adjust cell turgor (9), although the regulation and physiological role of AqpZ are being reassessed (10). AqpZ is a highly stable tetramer with negligible permeability to glycerol. In contrast, the glycerol permeability of the glycerol facilitator (GlpF) fromE. coli has long been recognized (11). GlpF has relatively limited water permeability (12), and the tetrameric form has reduced stability in some detergents (13). Atomic resolution structures have been solved for GlpF (14) as well as human and bovine AQP11 (15-17). These have elucidated differential specificities and functional mechanisms of the two sequence-related proteins. Archaea and certain other microorganisms are able to withstand exceptional challenges in maintaining water balance as they thrive in extreme environments including saturated salt solutions, extreme pH, and temperatures up to 130 °C (18). We recently recognized the DNA sequence of AqpM, a candidate aquaporin or aquaglyceroporin in the genome of a methanogenic thermophilic archaeon,Methanothermobacter marburgensis 2 (,19). Here we investigate water permeability in living cells and report the purification, functional reconstitution, and characterization of AqpM

Satellite image analysis using crowdsourcing data for collaborative mapping: current and opportunities

Researchers are continually finding new applications of satellite images because of the growing number of high-resolution images with wide spatial coverage. However, the cost of these images is sometimes high, and their temporal resolution is relatively coarse. Crowdsourcing is an increasingly common source of data that takes advantage of local stakeholder knowledge and that provides a higher frequency of data. The complementarity of these two data sources suggests there is great potential for mutually beneficial integration. Unfortunately, there are still important gaps in crowdsourced satellite image analysis by means of crowdsourcing in areas such as land cover classification and emergency management. In this paper, we summarize recent efforts, and discuss the challenges and prospects of satellite image analysis for geospatial applications using crowdsourcing. Crowdsourcing can be used to improve satellite image analysis and satellite images can be used to organize crowdsourced efforts for collaborative mapping

A Comprehensive Risk Assessment Framework for Inland Waterway Transportation of Dangerous Goods

A framework for risk assessment due to inland waterway transportation of dangerous goods is designed based on all possible event types that may be caused by the inland transportation of dangerous goods. The objective of this study is to design a framework for calculating the risks associated with changes in the transportation of dangerous goods along inland waterways. The framework is based on the traditional definition of risk and is designed for sensitive riverside environmental conditions in inland waterways. From the perspective of transportation management, this paper introduced the concept of transportability of dangerous goods and constructed a transportability assessment framework, which consists of a multi-index evaluation system and a single metric model. The result of the assessment is as an auxiliary basis to determine the transportation permit and control intensity of dangerous goods in an inland waterway specific voyage. The methodology is illustrated using a case study of transporting fireworks in the Yangtze River

A Multi-View Fusion Neural Network for Answer Selection

Community question answering aims at choosing the most appropriate answer for a given question, which is important in many NLP applications. Previous neural network-based methods consider several different aspects of information through calculating attentions. These different kinds of attentions are always simply summed up and can be seen as a ``single view", causing severe information loss. To overcome this problem, we propose a Multi-View Fusion Neural Network, where each attention component generates a ``view'' of the QA pair and a fusion RNN integrates the generated views to form a more holistic representation.    In this fusion RNN method, a filter gate  collects  important information of  input and directly adds it to the output, which borrows the idea of residual networks.    Experimental results on the WikiQA and SemEval-2016 CQA datasets demonstrate that our proposed model outperforms the state-of-the-art methods

Multi-state ship traffic flow analysis using data-driven method and visibility graph

Ship traffic flow characteristics play a crucial role in enhancing the effectiveness and efficiency of intelligent maritime traffic management systems. The primary objective of this study is to establish a comprehensive framework for analyzing multi-state traffic flow based on the automatic identification system (AIS). The collected AIS data undergoes preprocessing to calculate traffic flow density, velocity, and intensity. Subsequently, clustering techniques, specifically the K-medoids algorithm and silhouette coefficient analysis, are applied to classify traffic states ranging from least congested to highly congested. The datasets corresponding to each cluster are then utilized to construct visibility graphs, which enable a graphical representation of the traffic flow dynamics. Statistical analysis is conducted to examine the topological characteristics of the network. To illustrate the applicability of the proposed framework, a case study of the Meishan island water areas is conducted, allowing for an in-depth analysis of ship traffic flow characteristics and the identification of distinct traffic flow states. The findings of this study demonstrate the effectiveness of the visibility graph method in analyzing multi-state ship traffic flow. Additionally, the statistical characteristics derived from the developed complex networks adeptly capture the inherent maritime traffic flow characteristics. The insights gained from this study contribute to the advancement of maritime traffic management by providing a deeper understanding of complex traffic flow patterns and delineation