scholarly journals Anaphora With Non-nominal Antecedents in Computational Linguistics: a Survey

2018 ◽  
Vol 44 (3) ◽  
pp. 547-612 ◽  
Author(s):  
Varada Kolhatkar ◽  
Adam Roussel ◽  
Stefanie Dipper ◽  
Heike Zinsmeister
Keyword(s):  
Computational Linguistics ◽  
Question Answering ◽  
Future Research ◽  
Good Picture ◽  
Text Understanding ◽  
Theoretical Approaches ◽  
Current State ◽  
Open Questions ◽  
Work Done ◽  
Computational Systems

This article provides an extensive overview of the literature related to the phenomenon of non-nominal-antecedent anaphora (also known as abstract anaphora or discourse deixis), a type of anaphora in which an anaphor like “that” refers to an antecedent (marked in boldface) that is syntactically non-nominal, such as the first sentence in “It’s way too hot here. That’s why I’m moving to Alaska.” Annotating and automatically resolving these cases of anaphora is interesting in its own right because of the complexities involved in identifying non-nominal antecedents, which typically represent abstract objects such as events, facts, and propositions. There is also practical value in the resolution of non-nominal-antecedent anaphora, as this would help computational systems in machine translation, summarization, and question answering, as well as, conceivably, any other task dependent on some measure of text understanding. Most of the existing approaches to anaphora annotation and resolution focus on nominal-antecedent anaphora, classifying many of the cases where the antecedents are syntactically non-nominal as non-anaphoric. There has been some work done on this topic, but it remains scattered and difficult to collect and assess. With this article, we hope to bring together and synthesize work done in disparate contexts up to now in order to identify fundamental problems and draw conclusions from an overarching perspective. Having a good picture of the current state of the art in this field can help researchers direct their efforts to where they are most necessary. Because of the great variety of theoretical approaches that have been brought to bear on the problem, there is an equally diverse array of terminologies that are used to describe it, so we will provide an overview and discussion of these terminologies. We also describe the linguistic properties of non-nominal-antecedent anaphora, examine previous annotation efforts that have addressed this topic, and present the computational approaches that aim at resolving non-nominal-antecedent anaphora automatically. We close with a review of the remaining open questions in this area and some of our recommendations for future research.

scholarly journals Hepatic stellate cells: current state and open questions

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Claus Kordes ◽  
Hans H. Bock ◽  
Doreen Reichert ◽  
Petra May ◽  
Dieter Häussinger
Keyword(s):  
Hepatic Stellate Cells ◽  
Stellate Cells ◽  
Essential Elements ◽  
Future Research ◽  
Heinrich Heine ◽  
Current State ◽  
Open Questions ◽  
Sinusoidal Endothelium ◽  
Cell Niche ◽  
Space Of Disse

Abstract This review article summarizes 20 years of our research on hepatic stellate cells within the framework of two collaborative research centers CRC575 and CRC974 at the Heinrich Heine University. Over this period, stellate cells were identified for the first time as mesenchymal stem cells of the liver, and important functions of these cells in the context of liver regeneration were discovered. Furthermore, it was determined that the space of Disse – bounded by the sinusoidal endothelium and hepatocytes – functions as a stem cell niche for stellate cells. Essential elements of this niche that control the maintenance of hepatic stellate cells have been identified alongside their impairment with age. This article aims to highlight previous studies on stellate cells and critically examine and identify open questions and future research directions.

Second language structural priming: A critical review and directions for future research

2017 ◽  
Vol 34 (4) ◽  
pp. 539-552 ◽  
Author(s):  
Carrie N. Jackson
Keyword(s):  
Second Language ◽  
Future Research ◽  
Structural Priming ◽  
Cognitive Mechanisms ◽  
L2 Acquisition ◽  
Current State ◽  
Current Review ◽  
Open Questions ◽  
Key Issues ◽  
State Of Research

The last 15 years has seen a tremendous growth in research on structural priming among second language (L2) speakers. Structural priming is the phenomenon whereby speakers are more likely to repeat a structure they have recently heard or produced. Research on L2 structural priming speaks to key issues regarding the underlying linguistic and cognitive mechanisms that support L2 acquisition and use, and the extent to which lexical and grammatical information are shared across an L2 speaker’s languages. As the number of researchers investigating L2 priming and its implications for L2 learning continues to grow, it is important to assess the current state of research in this area and establish directions for continued inquiry. The goal of the current review is to provide an overview of recent research on within-language L2 structural priming, with an eye towards the open questions that remain.

Ecological Interactions and Macroevolution: A New Field with Old Roots

2020 ◽  
Vol 51 (1) ◽  
pp. 215-243 ◽  
Author(s):  
David H. Hembry ◽  
Marjorie G. Weber
Keyword(s):  
Species Interactions ◽  
Interspecific Interactions ◽  
Biotic Interactions ◽  
Evolutionary Change ◽  
Future Research ◽  
Ecological Interactions ◽  
Open Questions ◽  
Work Done ◽  
Lineage Diversification

Linking interspecific interactions (e.g., mutualism, competition, predation, parasitism) to macroevolution (evolutionary change on deep timescales) is a key goal in biology. The role of species interactions in shaping macroevolutionary trajectories has been studied for centuries and remains a cutting-edge topic of current research. However, despite its deep historical roots, classic and current approaches to this topic are highly diverse. Here, we combine historical and contemporary perspectives on the study of ecological interactions in macroevolution, synthesizing ideas across eras to build a zoomed-out picture of the big questions at the nexus of ecology and macroevolution. We discuss the trajectory of this important and challenging field, dividing research into work done before the 1970s, research between 1970 and 2005, and work done since 2005. We argue that in response to long-standing questions in paleobiology, evidence accumulated to date has demonstrated that biotic interactions (including mutualism) can influence lineage diversification and trait evolution over macroevolutionary timescales, and we outline major open questions for future research in the field.

Meinungsbildung in der Netzöffentlichkeit

2019 ◽  
Keyword(s):  
Social Media ◽  
Public Communication ◽  
Future Research ◽  
Digital Revolution ◽  
The Public ◽  
Empirical Basis ◽  
Current State ◽  
Open Questions ◽  
State Of Research

This volume offers insights into current research on the reception and effects of the digital revolution in public communication in the field of communication science. The contributions it contains deal with questions about the use of news on Facebook, the articulation of opinions on the public Net and the influencing of opinions on social media (e.g. by influencers). They document the current state of research and knowledge in this field, answer current open questions on an empirical basis and provide suggestions for future research. With contributions by Patrick Weber, Frank Mangold, Miriam Steiner, Melanie Magin, Birgit Stark, Pascal Jürgens, Anna Sophie Kümpel, Larissa Leonhard, Veronika Karnowski, Claudia Wilhelm, Ines Engelmann, Stefan Geiß, German Neubaum, Manuel Cargnino, Davina Berthelé, Priska Breves, Helene Schüler, Benedikt Spangardt, Kerstin Thummes

scholarly journals An Analysis of the Information Architecture of New Zealand Tertiary Library Websites

2021 ◽  
Author(s):  
◽  
Summer Michelle Bledsoe
Keyword(s):  
New Zealand ◽  
Best Practice ◽  
Information Architecture ◽  
Future Research ◽  
Navigation Systems ◽  
Good Picture ◽  
Current State ◽  
Specific Analysis ◽  
Library Websites ◽  
User Friendly

<p>Library websites are becoming more and more important as so much of a library’s content is accessed through its website. It is important that this is usable for the site’s users and that the information contained in the site is findable. In order for this to happen the site must have a good information architecture.  This study was done firstly as a literature analysis to determine what is currently considered to be best practice in information architecture for library websites. This was then formed into a checklist of best practice criteria and was used to analyse a sample of New Zealand’s tertiary library websites to determine what areas that these sites were doing well with their information architecture and what areas may need improvement. The study found that in many areas the sites matched well with the criteria such as having effective site navigation systems and using clear label terms. There were also areas that needed improvement such as the prominence of the library branding and search tools needing to be more user-friendly.  This study provides a good picture of the current state of New Zealand tertiary library sites information architecture that could be used when updating these sites and it also provides a good checklist that can be used in the analysis of other library sites. Future research could extend this project by analysing sites more thoroughly and it could also do a more specific analysis by looking at what a certain library’s users want and need in the information architecture of their library site.</p>

scholarly journals Weakly Supervised Learning for Textbook Question Answering

2021 ◽  
Author(s):  
Jie Ma ◽  
Qi Chai ◽  
Jingyue Huang ◽  
Jun Liu ◽  
Yang You ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Text Comprehension ◽  
Question Answering ◽  
Weakly Supervised Learning ◽  
Effective Learning ◽  
Task Forces ◽  
Text Understanding ◽  
Current State ◽  
Weakly Supervised ◽  
Fine Tune

Textbook Question Answering (TQA) is the task of answering diagram and non-diagram questions given large multi-modal contexts consisting of abundant text and diagrams. Deep text understandings and effective learning of diagram semantics are important for this task due to its specificity. In this paper, we propose a Weakly Supervised learning method for TQA (WSTQ), which regards the incompletely accurate results of essential intermediate procedures for this task as supervision to develop Text Matching (TM) and Relation Detection (RD) tasks and then employs the tasks to motivate itself to learn strong text comprehension and excellent diagram semantics respectively. Specifically, we apply the result of text retrieval to build positive as well as negative text pairs. In order to learn deep text understandings, we first pre-train the text understanding module of WSTQ on TM and then fine-tune it on TQA. We build positive as well as negative relation pairs by checking whether there is any overlap between the items/regions detected from diagrams using object detection. The RD task forces our method to learn the relationships between regions, which are crucial to express the diagram semantics. We train WSTQ on RD and TQA simultaneously, \emph{i.e.}, multitask learning, to obtain effective diagram semantics and then improve the TQA performance. Extensive experiments are carried out on CK12-QA and AI2D to verify the effectiveness of WSTQ. Experimental results show that our method achieves significant accuracy improvements of $5.02\%$ and $4.12\%$ on test splits of the above datasets respectively than the current state-of-the-art baseline. We have released our code on \url{https://github.com/dr-majie/WSTQ}.

scholarly journals Mechanical homeostasis in tissue equivalents: a review

2021 ◽  
Author(s):  
Jonas F. Eichinger ◽  
Lea J. Haeusel ◽  
Daniel Paukner ◽  
Roland C. Aydin ◽  
Jay D. Humphrey ◽  
...  
Keyword(s):  
Multiple Scales ◽  
Experimental Studies ◽  
Biological Tissues ◽  
Future Research ◽  
Collagen Gels ◽  
Tissue Equivalents ◽  
Current State ◽  
Open Questions ◽  
Mechanical Homeostasis ◽  
State Of Research

AbstractThere is substantial evidence that growth and remodeling of load bearing soft biological tissues is to a large extent controlled by mechanical factors. Mechanical homeostasis, which describes the natural tendency of such tissues to establish, maintain, or restore a preferred mechanical state, is thought to be one mechanism by which such control is achieved across multiple scales. Yet, many questions remain regarding what promotes or prevents homeostasis. Tissue equivalents, such as collagen gels seeded with living cells, have become an important tool to address these open questions under well-defined, though limited, conditions. This article briefly reviews the current state of research in this area. It summarizes, categorizes, and compares experimental observations from the literature that focus on the development of tension in tissue equivalents. It focuses primarily on uniaxial and biaxial experimental studies, which are well-suited for quantifying interactions between mechanics and biology. The article concludes with a brief discussion of key questions for future research in this field.

scholarly journals An Analysis of the Information Architecture of New Zealand Tertiary Library Websites

2021 ◽  
Author(s):  
◽  
Summer Michelle Bledsoe
Keyword(s):  
New Zealand ◽  
Best Practice ◽  
Information Architecture ◽  
Future Research ◽  
Navigation Systems ◽  
Good Picture ◽  
Current State ◽  
Specific Analysis ◽  
Library Websites ◽  
User Friendly

<p>Library websites are becoming more and more important as so much of a library’s content is accessed through its website. It is important that this is usable for the site’s users and that the information contained in the site is findable. In order for this to happen the site must have a good information architecture.  This study was done firstly as a literature analysis to determine what is currently considered to be best practice in information architecture for library websites. This was then formed into a checklist of best practice criteria and was used to analyse a sample of New Zealand’s tertiary library websites to determine what areas that these sites were doing well with their information architecture and what areas may need improvement. The study found that in many areas the sites matched well with the criteria such as having effective site navigation systems and using clear label terms. There were also areas that needed improvement such as the prominence of the library branding and search tools needing to be more user-friendly.  This study provides a good picture of the current state of New Zealand tertiary library sites information architecture that could be used when updating these sites and it also provides a good checklist that can be used in the analysis of other library sites. Future research could extend this project by analysing sites more thoroughly and it could also do a more specific analysis by looking at what a certain library’s users want and need in the information architecture of their library site.</p>

High-frequency Oscillations in Epilepsy: What Have We Learned and What Needs to be Addressed

Neurology ◽  
2021 ◽  
pp. 10.1212/WNL.0000000000011465 ◽  
Author(s):  
Zhuying Chen ◽  
Matias I. Maturana ◽  
Anthony N. Burkitt ◽  
Mark J. Cook ◽  
David B. Grayden
Keyword(s):  
High Frequency ◽  
Future Research ◽  
Great Promise ◽  
Clinical Biomarkers ◽  
High Frequency Oscillations ◽  
Visual Identification ◽  
Current State ◽  
Open Questions ◽  
Term Data

For the past two decades, high-frequency oscillations (HFOs) have been enthusiastically studied by the epilepsy community. Emerging evidence shows that HFOs harbour great promise to delineate epileptogenic brain areas and possibly predict the likelihood of seizures. Investigations into HFOs in clinical epilepsy have advanced from small retrospective studies relying on visual identification and correlation analysis to larger prospective assessments using automatic detection and prediction strategies. While most studies have yielded promising results, some have revealed significant obstacles to clinical application of HFOs, thus raising debate about the reliability and practicality of HFOs as clinical biomarkers. In this review, we give an overview of the current state of HFO research and pinpoint the conceptual and methodological issues that have hampered HFO translation. We highlight recent insights gained from long-term data, high-density recordings and multicentre collaborations, and discuss the open questions that need to be addressed in future research.

scholarly journals Weakly Supervised Learning for Textbook Question Answering

2021 ◽  
Author(s):  
Jie Ma ◽  
Qi Chai ◽  
Jingyue Huang ◽  
Jun Liu ◽  
Yang You ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Text Comprehension ◽  
Question Answering ◽  
Weakly Supervised Learning ◽  
Effective Learning ◽  
Task Forces ◽  
Text Understanding ◽  
Current State ◽  
Weakly Supervised ◽  
Fine Tune

Textbook Question Answering (TQA) is the task of answering diagram and non-diagram questions given large multi-modal contexts consisting of abundant text and diagrams. Deep text understandings and effective learning of diagram semantics are important for this task due to its specificity. In this paper, we propose a Weakly Supervised learning method for TQA (WSTQ), which regards the incompletely accurate results of essential intermediate procedures for this task as supervision to develop Text Matching (TM) and Relation Detection (RD) tasks and then employs the tasks to motivate itself to learn strong text comprehension and excellent diagram semantics respectively. Specifically, we apply the result of text retrieval to build positive as well as negative text pairs. In order to learn deep text understandings, we first pre-train the text understanding module of WSTQ on TM and then fine-tune it on TQA. We build positive as well as negative relation pairs by checking whether there is any overlap between the items/regions detected from diagrams using object detection. The RD task forces our method to learn the relationships between regions, which are crucial to express the diagram semantics. We train WSTQ on RD and TQA simultaneously, \emph{i.e.}, multitask learning, to obtain effective diagram semantics and then improve the TQA performance. Extensive experiments are carried out on CK12-QA and AI2D to verify the effectiveness of WSTQ. Experimental results show that our method achieves significant accuracy improvements of $5.02\%$ and $4.12\%$ on test splits of the above datasets respectively than the current state-of-the-art baseline. We have released our code on \url{https://github.com/dr-majie/WSTQ}.

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