Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Natural Language Processing
Title: End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF
Abstract: State-of-the-art sequence labeling systems traditionally require large amounts of task-specific knowledge in the form of hand-crafted features and data pre-processing. In this paper, we introduce a novel neutral network architecture that benefits from both word- and character-level representations automatically, by using combination of bidirectional LSTM, CNN and CRF. Our system is truly end-to-end, requiring no feature engineering or data pre-processing, thus making it applicable to a wide range of sequence labeling tasks. We evaluate our system on two data sets for two sequence labeling tasks --- Penn Treebank WSJ corpus for part-of-speech (POS) tagging and CoNLL 2003 corpus for named entity recognition (NER). We obtain state-of-the-art performance on both the two data --- 97.55\% accuracy for POS tagging and 91.21\% F1 for NER.
Extracted statement — Material: Penn Treebank WSJ corpus for part-of-speech (POS) tagging
Research field: Natural Language Processing
Title: Analyzing the Dynamics of Research by Extracting Key Aspects of Scientific Papers
Abstract: We present a method for characterizing a research work in terms of its focus, domain of application, and techniques used. We show how tracing these aspects over time provides a novel measure of the influence of research communities on each other. We extract these characteristics by matching semantic extraction patterns, learned using bootstrapping, to the dependency trees of sentences in an article’s
Extracted statement — description: present a method for characterizing a research work in terms of its focus, domain of application, and techniques used.
Research field: Natural Language Processing
Title: Concept-based analysis of scientific literature
Abstract: This paper studies the importance of identifying and categorizing scientific concepts as a way to achieve a deeper understanding of the research literature of a scientific community. To reach this goal, we propose an unsupervised bootstrapping algorithm for identifying and categorizing mentions of concepts. We then propose a new clustering algorithm that uses citations' context as a way to cluster the extracted mentions into coherent concepts. Our evaluation of the algorithms against gold standards shows significant improvement over state-of-the-art results. More importantly, we analyze the computational linguistic literature using the proposed algorithms and show four different ways to summarize and understand the research community which are difficult to obtain using existing techniques.
Extracted statement — description: propose an unsupervised bootstrapping algorithm for identifying and categorizing mentions of concepts. We then propose a new clustering algorithm that uses citations' context as a way to cluster the extracted mentions into coherent concepts.
Research field: Natural Language Processing
Title: Coreference Resolution in Biomedical Texts: a Machine Learning Approach
Abstract: Motivation: Coreference resolution, the process of identifying different mentions of an entity, is a very important component in a text-mining system. Compared with the work in news articles, the existing study of coreference resolution in biomedical texts is quite preliminary by only focusing on specific types of anaphors like pronouns or definite noun phrases, using heuristic methods, and running on small data sets. Therefore, there is a need for an in-depth exploration of this task in the biomedical domain. Results: In this article, we presented a learning-based approach to coreference resolution in the biomedical domain. We made three contributions in our study. Firstly, we annotated a large scale coreference corpus, MedCo, which consists of 1,999 medline abstracts in the GENIA data set. Secondly, we proposed a detailed framework for the coreference resolution task, in which we augmented the traditional learning model by incorporating non-anaphors into training. Lastly, we explored various sources of knowledge for coreference resolution, particularly, those that can deal with the complexity of biomedical texts. The evaluation on the MedCo corpus showed promising results. Our coreference resolution system achieved a high precision of 85.2% with a reasonable recall of 65.3%, obtaining an F-measure of 73.9%. The results also suggested that our augmented learning model significantly boosted precision (up to 24.0%) without much loss in recall (less than 5%), and brought a gain of over 8% in F-measure.
Extracted statement — Method: proposed a detailed framework for the coreference resolution task, in which we augmented the traditional learning model by incorporating non-anaphors into training
Research field: Natural Language Processing
Title: Analyzing the Dynamics of Research by Extracting Key Aspects of Scientific Papers
Abstract: We present a method for characterizing a research work in terms of its focus, domain of application, and techniques used. We show how tracing these aspects over time provides a novel measure of the influence of research communities on each other. We extract these characteristics by matching semantic extraction patterns, learned using bootstrapping, to the dependency trees of sentences in an article’s
Extracted statement — description: show how tracing these aspects over time provides a novel measure of the influence of research communities on each other.
Research field: Natural Language Processing
Title: Overview of BioCreAtIvE task 1B: normalized gene lists
Abstract: Abstract Background Our goal in BioCreAtIve has been to assess the state of the art in text mining, with emphasis on applications that reflect real biological applications, e.g., the curation process for model organism databases. This paper summarizes the BioCreAtIvE task 1B, the "Normalized Gene List" task, which was inspired by the gene list supplied for each curated paper in a model organism database. The task was to produce the correct list of unique gene identifiers for the genes and gene products mentioned in sets of abstracts from three model organisms (Yeast, Fly, and Mouse). Results Eight groups fielded systems for three data sets (Yeast, Fly, and Mouse). For Yeast, the top scoring system (out of 15) achieved 0.92 F-measure (harmonic mean of precision and recall); for Mouse and Fly, the task was more difficult, due to larger numbers of genes, more ambiguity in the gene naming conventions (particularly for Fly), and complex gene names (for Mouse). For Fly, the top F-measure was 0.82 out of 11 systems and for Mouse, it was 0.79 out of 16 systems. Conclusion This assessment demonstrates that multiple groups were able to perform a real biological task across a range of organisms. The performance was dependent on the organism, and specifically on the naming conventions associated with each organism. These results hold out promise that the technology can provide partial automation of the curation process in the near future.
Extracted statement — description: The task was to produce the correct list of unique gene identifiers for the genes and gene products mentioned in sets of abstracts from three model organisms (Yeast, Fly, and Mouse).
Research field: Natural Language Processing
Title: SemEval-2020 Task 3: Graded Word Similarity in Context
Abstract: This paper presents the Graded Word Similarity in Context (GWSC) task which asked participants to predict the effects of context on human perception of similarity in English, Croatian, Slovene and Finnish. We received 15 submissions and 11 system description papers. A new dataset (CoSimLex) was created for evaluation in this task: it contains pairs of words, each annotated within two different contexts. Systems beat the baselines by significant margins, but few did well in more than one language or subtask. Almost every system employed a Transformer model, but with many variations in the details: WordNet sense embeddings, translation of contexts, TF-IDF weightings, and the automatic creation of datasets for fine-tuning were all used to good effect.
Extracted statement — description: to predict the effects of context on human perception of similarity in English, Croatian, Slovene and Finnish
Research field: Networking and Internet Architecture
Title: PredictRoute: A Network Path Prediction Toolkit
Abstract: Accurate prediction of network paths between arbitrary hosts on the Internet is of vital importance for network operators, cloud providers, and academic researchers. We present PredictRoute, a system that predicts network paths between hosts on the Internet using historical knowledge of the data and control plane. In addition to feeding on freely available traceroutes and BGP routing tables, PredictRoute optimally explores network paths towards chosen BGP prefixes. PredictRoute's strategy for exploring network paths discovers 4X more autonomous system (AS) hops than other well-known strategies used in practice today. Using a corpus of traceroutes, PredictRoute trains probabilistic models of routing towards prefixes on the Internet to predict network paths and their likelihood. PredictRoute's AS-path predictions differ from the measured path by at most 1 hop, 75% of the time. We expose PredictRoute's path prediction capability via a REST API to facilitate its inclusion in other applications and studies. We additionally demonstrate the utility of PredictRoute in improving real-world applications for circumventing Internet censorship and preserving anonymity online.
Extracted statement — Method: PredictRoute trains probabilistic models of routing towards prefixes on the Internet to predict network paths and their likelihood.
Research field: Pharmacology
Title: EFFECT OF PIOGLITAZONE AND GEMFIBROZIL ADMINISTRATION ON C-REACTIVE PROTEIN LEVELS IN NON-DIABETIC HYPERLIPIDEMIC RATS
Abstract: ABSTRACTOBJECTIVE: To assess and compare anti-inflammatory effect of pioglitazone and gemfibrozil by measuring C-reactive protein (CRP) levels in high fat fed non-diabetic rats.METHODS: A comparative animal study was conducted at the Post Graduate Medical Institute, Lahore, Pakistan in which 27, adult healthy male Sprague Dawley rats were used. The rats were divided into three groups. Hyperlipidemia was induced in all three groups by giving hyperlipidemic diet containing cholesterol 1.5%, coconut oil 8.0% and sodium cholate 1.0%. After four weeks, Group A (control) was given distilled water, Group B was given pioglitazone 10mg/kg body weight and Group C was given gemfibrozil 10mg/kg body weight as single morning dose by oral route for four weeks. CRP was estimated at zero, 4th and 8th week.RESULTS: There was significant increase in the level of CRP after giving high lipid diet from mean±SD of 2.59±0.28mg/L, 2.63±0.32mg/L and 2.67±0.23mg/L at 0 week to 3.55±0.44mg/L, 3.59±0.34mg/L and 3.6±0.32mg/L at 4th week in groups A, B and C respectively.Multiple comparisons by ANOVA revealed significant difference between groups at 8th week only. Post hoc analysis disclosed that CRP level was significantly low in pioglitazone treated group having mean±SD of 2.93±0.33mg/L compared to control group’s 4.42±0.30mg/L and gemfibrozil group’s 4.28±0.39mg/L. The p-value in each case was <0.001, while difference between control and gemfibrozil was not statistically significant.CONCLUSION: Pioglitazone is effective in reducing hyperlipidemia associated inflammation, evidenced by decreased CRP level while gemfibrozil is not effective.KEY WORDS: Pioglitazone (MeSH); Gemfibrozil (MeSH); Hyperlipidemia (MeSH); Anti-inflammatory (MeSH); C-reactive protein (MeSH).
Extracted statement — Material: Pioglitazone (MeSH); Gemfibrozil (MeSH); Hyperlipidemia (MeSH); Anti-inflammatory (MeSH); C-reactive protein (MeSH)
Research field: Planetary Sciences
Title: Mineralogy of the MSL Curiosity landing site in Gale crater as observed by MRO/CRISM
Abstract: Orbital data acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) and High Resolution Imaging Science Experiment instruments on the Mars Reconnaissance Orbiter (MRO) provide a synoptic view of compositional stratigraphy on the floor of Gale crater surrounding the area where the Mars Science Laboratory (MSL) Curiosity landed. Fractured, light‐toned material exhibits a 2.2 µm absorption consistent with enrichment in hydroxylated silica. This material may be distal sediment from the Peace Vallis fan, with cement and fracture fill containing the silica. This unit is overlain by more basaltic material, which has 1 µm and 2 µm absorptions due to pyroxene that are typical of Martian basaltic materials. Both materials are partially obscured by aeolian dust and basaltic sand. Dunes to the southeast exhibit differences in mafic mineral signatures, with barchan dunes enhanced in olivine relative to pyroxene‐containing longitudinal dunes. This compositional difference may be related to aeolian grain sorting.
Extracted statement — Instrument: Compact Reconnaissance Imaging Spectrometer for Mars (CRISM)
Research field: Planetary Sciences
Title: New insights into gully formation on Mars: Constraints from composition as seen by MRO/CRISM
Abstract: Over 100 Martian gully sites were analyzed using orbital data collected by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) and High Resolution Imaging Science Experiment on the Mars Reconnaissance Orbiter (MRO). Most gullies are spectrally indistinct from their surroundings, due to mantling by dust. Where spectral information on gully sediments was obtained, a variety of mineralogies were identified. Their relationship to the source rock suggests that gully‐forming processes transported underlying material downslope. There is no evidence for specific compositions being more likely to be associated with gullies or with the formation of hydrated minerals in situ as a result of recent liquid water activity. Seasonal CO2 and H2O frosts were observed in gullies at middle to high latitudes, consistent with seasonal frost‐driven processes playing important roles in the evolution of gullies. Our results do not clearly indicate a role for long‐lived liquid water in gully formation and evolution.
Extracted statement — Instrument: Compact Reconnaissance Imaging Spectrometer for Mars (CRISM)
Research field: Psychology
Title: Corrective interpersonal experience in psychodrama group therapy: A comprehensive process analysis of significant therapeutic events
Abstract: Abstract This study investigated the process of resolving painful emotional experience during psychodrama group therapy, by examining significant therapeutic events within seven psychodrama enactments. A comprehensive process analysis of four resolved and three not-resolved cases identified five meta-processes which were linked to in-session resolution. One was a readiness to engage in the therapeutic process, which was influenced by client characteristics and the client's experience of the group; and four were therapeutic events: (1) re-experiencing with insight; (2) activating resourcefulness; (3) social atom repair with emotional release; and (4) integration. A corrective interpersonal experience (social atom repair) healed the sense of fragmentation and interpersonal disconnection associated with unresolved emotional pain, and emotional release was therapeutically helpful when located within the enactment of this new role relationship. Protagonists who experienced resolution reported important improvements in interpersonal functioning and sense of self which they attributed to this experience.
Extracted statement — Qualitative findings   : Improvements in interpersonal functioning and sense of self
Research field: Public Administration
Title: How many could have been saved? Effects of social distancing on COVID-19
Abstract: Abstract What is the effect of social distancing policies on the spread of the new coronavirus? Social distancing policies rose to prominence as most capable of containing contagion and saving lives. Our purpose in this paper is to identify the causal effect of social distancing policies on the number of confirmed cases of COVID-19 and on contagion velocity. We align our main argument with the existing scientific consensus: social distancing policies negatively affect the number of cases. To test this hypothesis, we construct a dataset with daily information on 78 affected countries in the world. We compute several relevant measures from publicly available information on the number of cases and deaths to estimate causal effects for short-term and cumulative effects of social distancing policies. We use a time-series cross-sectional matching approach to match countries’ observable histories. Causal effects (ATTs and ATEs) can be extracted via a dif-in-dif estimator. Results show that social distancing policies reduce the aggregated number of cases by 4,832 on average (or 17.5/100 thousand), but only when strict measures are adopted. This effect seems to manifest from the third week onwards.
Extracted statement — Results: Social distancing policies reduce the aggregated number of cases
Research field: Science
Title: Proofs of Retrievability: Theory and Implementation
Abstract: A proof of retrievability (POR) is a compact proof by a file system (prover) to a client (verifier) that a target file F is intact, in the sense that the client can fully recover it. As PORs incur lower communication complexity than transmission of F itself, they are an attractive building block for high-assurance remote storage systems. In this paper, we propose a theoretical framework for the design of PORs. Our framework improves the previously proposed POR constructions of Juels-Kaliski and Shacham-Waters, and also sheds light on the conceptual limitations of previous theoretical models for PORs. It supports a fully Byzantine adversarial model, carrying only the restriction---fundamental to all PORs---that the adversary's error rate be bounded when the client seeks to extract F. We propose a new variant on the Juels-Kaliski protocol and describe a prototype implementation. We demonstrate practical encoding even for files F whose size exceeds that of client main memory.
Extracted statement — Custom1: A proof of retrievability (POR) is a compact proof by a file system (prover) to a client (verifier) that a target file F is intact, in the sense that the client can fully recover it. As PORs incur lower communication complexity than transmission of F itself, they are an attractive building block for high-assurance remote storage systems.
Research field: Science
Title: Design Principles of Integrated Information
Platform for Emergency Responses: The Case of
2008 Beijing Olympic Games
Abstract: •his paper investigates the challenges faced in designing an integrated information platform for emergency response management and uses the Beijing Olympic Games as a case study. The research methods are grounded in action research, participatory design, and situation-awareness oriented design. The completion of a more than two-year industrial secondment and six-month field studies ensured that a full understanding of user requirements had been obtained. A service-centered architecture was proposed to satisfy these user requirements. The proposed architecture consists mainly of information gathering, database management, and decision support services. The decision support services include situational overview, instant risk assessment, emergency response preplan, and disaster development prediction. Abstracting from the experience obtained while building this system, we outline a set of design principles in the general domain of information systems (IS) development for emergency management. These design principles form a contribution to the information systems literature because they provide guidance to developers who are aiming to support emergency response and the development of such systems that have not yet been adequately met by any existing types of IS. We are proud that the information platform developed was deployed in the real world and used in the 2008 Beijing
Extracted statement — paper:Study Type: action research, participatory design, and situation-awareness oriented design
Research field: Science
Title: Identifying the factors influencing the performance of reverse supply chains (RSC)
Abstract: This paper aims to extract the factors influencing the performance of reverse supply chains (RSCs) based on the structure equation model (SEM). We first introduce the definition of RSC and describe its current status and follow this with a literature review of previous RSC studies and the technology acceptance model . We next develop our research model and 11 hypotheses and then use SEM to test our model and identify those factors that actually influence the success of RSC. Next, we use both questionnaire and web‐based methods to survey five companies which have RSC operation experience in China and Korea. Using the 168 responses, we used measurement modeling test and SEM to validate our proposed hypotheses. As a result, nine hypotheses were accepted while two were rejected. We found that ease of use, perceived usefulness, service quality, channel relationship and RSC cost were the five most important factors which influence the success of RSC. Finally, we conclude by highlighting our research contribution and propose future research.
Extracted statement — Critical success factors: ease of use
Research field: Science
Title: Mobile text alerts are an effective way of communicating emergency information to adolescents: Results from focus groups with 12- to 18-year-olds
Abstract: Mobile phone text messages can be used to disseminate information and advice to the public in disasters. We sought to identify factors influencing how adolescents would respond to receiving emergency text messages. Qualitative interviews were conducted with participants aged 12–18 years. Participants discussed scenarios relating to flooding and the discovery of an unexploded World War Two bomb and were shown example alerts that might be sent out in these circumstances. Intended compliance with the alerts was high. Participants noted that compliance would be more likely if: they were familiar with the system; the messages were sent by a trusted source; messages were reserved for serious incidents; multiple messages were sent; messages were kept short and formal.
Extracted statement — RQ: Identify factors influencing how adolescents would respond to receiving emergency text messages
Research field: Science
Title: Model Free iPID Control for Glycemia Regulation of Type-1 Diabetes
Abstract: Objective: The objective is to design a fully automated glycemia controller of Type-1 Diabetes (T1D) in both fasting and postprandial phases on a large number of virtual patients. Methods: A model-free intelligent proportional-integral-derivative (iPID) is used to infuse insulin. The feasibility of iPID is tested in silico on two simulators with and without measurement noise. The first simulator is derived from a long-term linear time-invariant model. The controller is also validated on the UVa/Padova metabolic simulator on 10 adults under 25 runs/subject for noise robustness test. Results: It was shown that without measurement noise, iPID mimicked the normal pancreatic secretion with a relatively fast reaction to meals as compared to a standard PID. With the UVa/Padova simulator, the robustness against CGM noise was tested. A higher percentage of time in target was obtained with iPID as compared to standard PID with reduced time spent in hyperglycemia. Conclusion: Two different T1D simulators tests showed that iPID detects meals and reacts faster to meal perturbations as compared to a classic PID. The intelligent part turns the controller to be more aggressive immediately after meals without neglecting safety. Further research is suggested to improve the computation of the intelligent part of iPID for such systems under actuator constraints. Any improvement can impact the overall performance of the model-free controller. Significance: The simple structure iPID is a step for PID-like controllers since it combines the classic PID nice properties with new adaptive features.
Extracted statement — Future work/challenges: improve the computation of the intelligent part of iPID