The Current Status of Historical Preservation Law in Regularory Takings Jurisprudence: Has the Lucas Missile Dismantled Preservation Programs?

This paper describes our NIHRIO system for SemEval-2018 Task 3 "Irony detection in English tweets". We propose to use a simple neural network architecture of Multilayer Perceptron with various types of input features including: lexical, syntactic, semantic and polarity features.  Our system achieves very high performance in both subtasks of binary and multi-class irony detection in tweets. In particular, we rank at fifth in terms of the accuracy metric and the F1 metric. Our code is available at: https://github.com/NIHRIO/IronyDetectionInTwitte

A novel ASP flood design for CO₂ contaminated sandstone reservoirs at low salinity and low permeability

ASP flooding relies the ability of surfactant to reduce the oil-water inter facial tension (IFT) and to alter the wettability towards water-wet conditions in order to promote oil mobilization. During this process surfactants must show long term stability under reservoir conditions as well as low adsorption on to the rock surface. Surfactant screening is particularly challenging for low salinity formation brines with low target salinity injection brine since most commercially available surfactants show optimum salinity ranges above 3 wt% total dissolved solid (TDS). A series of propylene oxide (PO) sulfate surfactants, internal olefin sulfonates (IOS), and alkyl benzene sulfonates (ABS) have been used for surfactant screening. Co-solvents were incorporated to improve aqueous stability of the surfactant mixture, reduce equilibration time, and minimize formation of viscous phases. More than 300 phase behavior scans were performed in order to optimize a chemical formulation for optimum salinity within a range of 1.0 to 2.0 wt% TDS. PO surfactant formulations show viscous oil-water microemulsion, and thus does not meet our criteria due to high surfactant retention. Therefore, PO formulations were not selected for coreflood experiments. ABS and IOS surfactant combination shows the optimum salinity in the desired range and Winsor Type III microemulsion which has low interfacial tension with oil and water within the Type III region. In addition, viscous emulsions were not observed over an incubation period of 60 days. This combination of surfactants has the ability to tune the optimum salinity within the range by changing the ratio of two surfactants. A Na2CO3 preflood was introduced before slug injection to neutralize the acidic nature of the core. ABS and IOS were blended at a 7:3 ratio in the surfactant slug based on our findings from our phase behavior study. Co-solvent (Butoxypolyglycol Basic) was added at 1.0 wt% concentration to achieve suitable low IFT conditions and less viscous microemulsions. We have conducted more than 20 corefloods using the above surfactant combination and with our final optimized coreflood yielding 98% oil recovery with 0.6% S [subscript orc].Petroleum and Geosystems Engineerin

Some Characteristics And Allopurinol Release Of Carrageenan/ Allopurinol Films Using Polyethylene Oxide As A Dispersion Aid Agent

This paper presents the effect of carrageenan (CG) on some characteristics and drug release of allopurinol in the presence of polyethylene oxide (PEO) as a dispersion aid agent. The samples were prepared in film shape by solution method, in which, the content of PEO was changed from 1 wt.% to 5 wt.% and the content of allopurinol was fixed at 10 wt.% in comparison with carrageenan weight. FTIR , FESEM, UV-Vis methods were used to evaluate characterizations and morphology of CG/PEO/allopurinol films

A Label Attention Model for ICD Coding from Clinical Text

ICD coding is a process of assigning the International Classification of Disease diagnosis codes to clinical/medical notes documented by health professionals (e.g. clinicians). This process requires significant human resources, and thus is costly and prone to error. To handle the problem, machine learning has been utilized for automatic ICD coding. Previous state-of-the-art models were based on convolutional neural networks, using a single/several fixed window sizes. However, the lengths and interdependence between text fragments related to ICD codes in clinical text vary significantly, leading to the difficulty of deciding what the best window sizes are. In this paper, we propose a new label attention model for automatic ICD coding, which can handle both the various lengths and the interdependence of the ICD code related text fragments. Furthermore, as the majority of ICD codes are not frequently used, leading to the extremely imbalanced data issue, we additionally propose a hierarchical joint learning mechanism extending our label attention model to handle the issue, using the hierarchical relationships among the codes. Our label attention model achieves new state-of-the-art results on three benchmark MIMIC datasets, and the joint learning mechanism helps improve the performances for infrequent codes.Comment: In Proceedings of IJCAI 2020 (Main Track

Sentiment classification on polarity reviews: an empirical study using rating-based features

We present a new feature type named rating-based feature and evaluate the contribution of this feature to the task of document-level sentiment analysis. We achieve state-of-the-art results on two publicly available standard polarity movie datasets: on the dataset consisting of 2000 reviews produced by Pang and Lee (2004) we obtain an accuracy of 91.6% while it is 89.87% evaluated on the dataset of 50000 reviews created by Maas et al. (2011). We also get a performance at 93.24% on our own dataset consisting of 233600 movie reviews, and we aim to share this dataset for further research in sentiment polarity analysis task

VnCoreNLP: A Vietnamese Natural Language Processing Toolkit

We present an easy-to-use and fast toolkit, namely VnCoreNLP---a Java NLP annotation pipeline for Vietnamese. Our VnCoreNLP supports key natural language processing (NLP) tasks including word segmentation, part-of-speech (POS) tagging, named entity recognition (NER) and dependency parsing, and obtains state-of-the-art (SOTA) results for these tasks. We release VnCoreNLP to provide rich linguistic annotations to facilitate research work on Vietnamese NLP. Our VnCoreNLP is open-source and available at: https://github.com/vncorenlp/VnCoreNLPComment: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, NAACL 2018, to appea