Moussab/ORKG-training-evaluation-set huggingface dataset:
Research field: Biophysics
Title: Direct Visualization of Membrane Leakage Induced by the Antibiotic Peptides: Maculatin, Citropin, and Aurein
Abstract: Membrane lysis caused by antibiotic peptides is often rationalized by means of two different models: the so-called carpet model and the pore-forming model. We report here on the lytic activity of antibiotic peptides from Australian tree frogs, maculatin 1.1, citropin 1.1, and aurein 1.2, on POPC or POPC/POPG model membranes. Leakage experiments using fluorescence spectroscopy indicated that the peptide/lipid mol ratio necessary to induce 50% of probe leakage was smaller for maculatin compared with aurein or citropin, regardless of lipid membrane composition. To gain further insight into the lytic mechanism of these peptides we performed single vesicle experiments using confocal fluorescence microscopy. In these experiments, the time course of leakage for different molecular weight (water soluble) fluorescent markers incorporated inside of single giant unilamellar vesicles is observed after peptide exposure. We conclude that maculatin and its related peptides demonstrate a pore-forming mechanism (differential leakage of small fluorescent probe compared with high molecular weight markers). Conversely, citropin and aurein provoke a total membrane destabilization with vesicle burst without sequential probe leakage, an effect that can be assigned to a carpeting mechanism of lytic action. Additionally, to study the relevance of the proline residue on the membrane-action properties of maculatin, the same experimental approach was used for maculatin-Ala and maculatin-Gly (Pro-15 was replaced by Ala or Gly, respectively). Although a similar peptide/lipid mol ratio was necessary to induce 50% of leakage for POPC membranes, the lytic activity of maculatin-Ala and maculatin-Gly decreased in POPC/POPG (1:1 mol) membranes compared with that observed for the naturally occurring maculatin sequence. As observed for maculatin, the lytic action of Maculatin-Ala and maculatin-Gly is in keeping with the formation of pore-like structures at the membrane independently of lipid composition.
Extracted statement — Lead compound: Maculatin 1.1
Research field: Chemistry
Title: Flash photolysis observation of the absorption spectra of trapped positive holes and electrons in colloidal titanium dioxide
Abstract: Photolyse laser eclair a 347 nm d'un sol de TiO 2 contenant un intercepteur d'electron adsorbe (Pt ou MV 2+ ). Etude par spectres d'absorption des especes piegees. A λ max =475 nm observation de «trous» h + . Vitesses de declin de h + en solutions acide et alcaline. Trous h + en exces. Avec un sol de TiO 2 contenant un intercepteur de trous (alcool polyvinylique ou thiocyanate), observation d'un spectre a λ max =650 nm attribue aux electrons pieges en exces, proches de la surface des particules colloidales
Extracted statement — transient absorption:trapped electrons: 650 nm
Research field: Civil Engineering
Title: A Graph Based Tool for Modelling Planning Processes in Building Engineering
Abstract: The planning process of a building is very complex. Many participants with different technical disciplines are involved and work on certain tasks. To manage the planning process the project leader has to organize participants, tasks and building data. For this purpose modern information and communication technologies can be used very effi ciently. But these technologies require a formal description of the planning process. Within the research project “Relation Based Process Modelling of Co-operative Building Planning” we have defined a consistent mathematical process model for planning processes and have developed a prototype implementation of an application for modelling these processes. Our project is embedded in the priori ty program 1103 “Network-based Co-operative Planning Processes in Structural Engineering” promoted by the German Research Foundation (DFG). In this paper we present the mathematical concept of our relational process model and the tool for building up the m odel and checking the structural consistency and correctness.
Extracted statement — method: the priori ty program 1103
Research field: Cognition and Perception
Title: Do Animals Engage Greater Social Attention in Autism? An Eye Tracking Analysis
Abstract: Background Visual atypicalities in autism spectrum disorder (ASD) are a well documented phenomenon, beginning as early as 2–6 months of age and manifesting in a significantly decreased attention to the eyes, direct gaze and socially salient information. Early emerging neurobiological deficits in perceiving social stimuli as rewarding or its active avoidance due to the anxiety it entails have been widely purported as potential reasons for this atypicality. Parallel research evidence also points to the significant benefits of animal presence for reducing social anxiety and enhancing social interaction in children with autism. While atypicality in social attention in ASD has been widely substantiated, whether this atypicality persists equally across species types or is confined to humans has not been a key focus of research insofar. Methods We attempted a comprehensive examination of the differences in visual attention to static images of human and animal faces (40 images; 20 human faces and 20 animal faces) among children with ASD using an eye tracking paradigm. 44 children (ASD n = 21; TD n = 23) participated in the study (10,362 valid observations) across five regions of interest (left eye, right eye, eye region, face and screen). Results Results obtained revealed significantly greater social attention across human and animal stimuli in typical controls when compared to children with ASD. However in children with ASD, a significantly greater attention allocation was seen to animal faces and eye region and lesser attention to the animal mouth when compared to human faces, indicative of a clear attentional preference to socially salient regions of animal stimuli. The positive attentional bias toward animals was also seen in terms of a significantly greater visual attention to direct gaze in animal images. Conclusion Our results suggest the possibility that atypicalities in social attention in ASD may not be uniform across species. It adds to the current neural and biomarker evidence base of the potentially greater social reward processing and lesser social anxiety underlying animal stimuli as compared to human stimuli in children with ASD.
Extracted statement — Data: 10,362 valid observations
Research field: Computational Engineering
Title: Suspended accounts in retrospect: an analysis of twitter spam
Abstract: In this study, we examine the abuse of online social networks at the hands of spammers through the lens of the tools, techniques, and support infrastructure they rely upon. To perform our analysis, we identify over 1.1 million accounts suspended by Twitter for disruptive activities over the course of seven months. In the process, we collect a dataset of 1.8 billion tweets, 80 million of which belong to spam accounts. We use our dataset to characterize the behavior and lifetime of spam accounts, the campaigns they execute, and the wide-spread abuse of legitimate web services such as URL shorteners and free web hosting. We also identify an emerging marketplace of illegitimate programs operated by spammers that include Twitter account sellers, ad-based URL shorteners, and spam affiliate programs that help enable underground market diversification. Our results show that 77% of spam accounts identified by Twitter are suspended within on day of their first tweet. Because of these pressures, less than 9% of accounts form social relationships with regular Twitter users. Instead, 17% of accounts rely on hijacking trends, while 52% of accounts use unsolicited mentions to reach an audience. In spite of daily account attrition, we show how five spam campaigns controlling 145 thousand accounts combined are able to persist for months at a time, with each campaign enacting a unique spamming strategy. Surprisingly, three of these campaigns send spam directing visitors to reputable store fronts, blurring the line regarding what constitutes spam on social networks.
Extracted statement — dataset: 1.8 billion tweets
Research field: Computational Engineering
Title: Suspended accounts in retrospect: an analysis of twitter spam
Abstract: In this study, we examine the abuse of online social networks at the hands of spammers through the lens of the tools, techniques, and support infrastructure they rely upon. To perform our analysis, we identify over 1.1 million accounts suspended by Twitter for disruptive activities over the course of seven months. In the process, we collect a dataset of 1.8 billion tweets, 80 million of which belong to spam accounts. We use our dataset to characterize the behavior and lifetime of spam accounts, the campaigns they execute, and the wide-spread abuse of legitimate web services such as URL shorteners and free web hosting. We also identify an emerging marketplace of illegitimate programs operated by spammers that include Twitter account sellers, ad-based URL shorteners, and spam affiliate programs that help enable underground market diversification. Our results show that 77% of spam accounts identified by Twitter are suspended within on day of their first tweet. Because of these pressures, less than 9% of accounts form social relationships with regular Twitter users. Instead, 17% of accounts rely on hijacking trends, while 52% of accounts use unsolicited mentions to reach an audience. In spite of daily account attrition, we show how five spam campaigns controlling 145 thousand accounts combined are able to persist for months at a time, with each campaign enacting a unique spamming strategy. Surprisingly, three of these campaigns send spam directing visitors to reputable store fronts, blurring the line regarding what constitutes spam on social networks.
Extracted statement — Accuracy/Results: 77% of spam accounts identified by Twitter are suspended within on day of their first tweet
Research field: Computational Linguistics
Title: Construction of an annotated corpus to support biomedical information extraction
Abstract: Abstract Background Information Extraction (IE) is a component of text mining that facilitates knowledge discovery by automatically locating instances of interesting biomedical events from huge document collections. As events are usually centred on verbs and nominalised verbs, understanding the syntactic and semantic behaviour of these words is highly important. Corpora annotated with information concerning this behaviour can constitute a valuable resource in the training of IE components and resources. Results We have defined a new scheme for annotating sentence-bound gene regulation events, centred on both verbs and nominalised verbs. For each event instance, all participants ( arguments ) in the same sentence are identified and assigned a semantic role from a rich set of 13 roles tailored to biomedical research articles, together with a biological concept type linked to the Gene Regulation Ontology. To our knowledge, our scheme is unique within the biomedical field in terms of the range of event arguments identified. Using the scheme, we have created the Gene Regulation Event Corpus (GREC), consisting of 240 MEDLINE abstracts, in which events relating to gene regulation and expression have been annotated by biologists. A novel method of evaluating various different facets of the annotation task showed that average inter-annotator agreement rates fall within the range of 66% - 90%. Conclusion The GREC is a unique resource within the biomedical field, in that it annotates not only core relationships between entities, but also a range of other important details about these relationships, e.g., location, temporal, manner and environmental conditions. As such, it is specifically designed to support bio-specific tool and resource development. It has already been used to acquire semantic frames for inclusion within the BioLexicon (a lexical, terminological resource to aid biomedical text mining). Initial experiments have also shown that the corpus may viably be used to train IE components, such as semantic role labellers. The corpus and annotation guidelines are freely available for academic purposes.
Extracted statement — number of papers: 240 MEDLINE abstracts
Research field: Computational Linguistics
Title: Annotation of Chemical Named Entities
Abstract: We describe the annotation of chemical named entities in scientific text. A set of annotation guidelines defines 5 types of named entities, and provides instructions for the resolution of special cases. A corpus of fulltext chemistry papers was annotated, with an inter-annotator agreement F score of 93%. An investigation of named entity recognition using LingPipe suggests that F scores of 63% are possible without customisation, and scores of 74% are possible with the addition of custom tokenisation and the use of dictionaries.
Extracted statement — description: annotation of chemical named entities in scientific text. A set of annotation guidelines defines 5 types of named entities, and provides instructions for the resolution of special cases.
Research field: Computational Linguistics
Title: Annotation of Chemical Named Entities
Abstract: We describe the annotation of chemical named entities in scientific text. A set of annotation guidelines defines 5 types of named entities, and provides instructions for the resolution of special cases. A corpus of fulltext chemistry papers was annotated, with an inter-annotator agreement F score of 93%. An investigation of named entity recognition using LingPipe suggests that F scores of 63% are possible without customisation, and scores of 74% are possible with the addition of custom tokenisation and the use of dictionaries.
Extracted statement — inter-coder agreement: F score of 93%
Research field: Computational Linguistics
Title: Leveraging Abstract Meaning Representation for Knowledge Base Question Answering
Abstract: Knowledge base question answering (KBQA) is an important task in Natural Language Processing. Existing approaches face significant challenges including complex question understanding, necessity for reasoning, and lack of large end-to-end training datasets. In this work, we propose Neuro-Symbolic Question Answering (NSQA), a modular KBQA system, that leverages (1) Abstract Meaning Representation (AMR) parses for task-independent question understanding; (2) a simple yet effective graph transformation approach to convert AMR parses into candidate logical queries that are aligned to the KB; (3) a pipeline-based approach which integrates multiple, reusable modules that are trained specifically for their individual tasks (semantic parser, entity and relationship linkers, and neuro-symbolic reasoner) and do not require end-to-end training data. NSQA achieves state-of-the-art performance on two prominent KBQA datasets based on DBpedia (QALD-9 and LC-QuAD 1.0). Furthermore, our analysis emphasizes that AMR is a powerful tool for KBQA systems.
Extracted statement — On evaluation dataset: LC-QuAD 1.0
Research field: Computational Linguistics
Title: Medmentions: a large biomedical corpus annotated with UMLS concepts
Abstract: This paper presents the formal release of {\em MedMentions}, a new manually annotated resource for the recognition of biomedical concepts. What distinguishes MedMentions from other annotated biomedical corpora is its size (over 4,000 abstracts and over 350,000 linked mentions), as well as the size of the concept ontology (over 3 million concepts from UMLS 2017) and its broad coverage of biomedical disciplines. In addition to the full corpus, a sub-corpus of MedMentions is also presented, comprising annotations for a subset of UMLS 2017 targeted towards document retrieval. To encourage research in Biomedical Named Entity Recognition and Linking, data splits for training and testing are included in the release, and a baseline model and its metrics for entity linking are also described.
Extracted statement — number of papers: over 4,000
Research field: Cultural History
Title: A systematic review of literature on contested heritage
Abstract: ABSTRACT Contested heritage has increasingly been studied by scholars over the last two decades in multiple disciplines, however, there is still limited knowledge about what contested heritage is and how it is realized in society. Therefore, the purpose of this paper is to produce a systematic literature review on this topic to provide a holistic understanding of contested heritage, and delineate its current state, trends and gaps. Methodologically, four electronic databases were searched, and 102 journal articles published before 2020 were extracted. A content analysis of each article was then conducted to identify key themes and variables for classification. Findings show that while its research often lacks theoretical underpinnings, contested heritage is marked by its diversity and complexity as it becomes a global issue for both tourism and urbanization. By presenting a holistic understanding of contested heritage, this review offers an extensive investigation of the topic area to help move literature pertaining contested heritage forward.
Extracted statement — has sources: 102 journal articles
Research field: Digital Communications and Networking
Title: MAG: A Multilingual, Knowledge-base Agnostic and Deterministic Entity Linking Approach
Abstract: Entity linking has recently been the subject of a significant body of research. Currently, the best performing approaches rely on trained mono-lingual models. Porting these approaches to other languages is consequently a difficult endeavor as it requires corresponding training data and retraining of the models. We address this drawback by presenting a novel multilingual, knowledge-base agnostic and deterministic approach to entity linking, dubbed MAG. MAG is based on a combination of context-based retrieval on structured knowledge bases and graph algorithms. We evaluate MAG on 23 data sets and in 7 languages. Our results show that the best approach trained on English datasets (PBOH) achieves a micro F-measure that is up to 4 times worse on datasets in other languages. MAG on the other hand achieves state-of-the-art performance on English datasets and reaches a micro F-measure that is up to 0.6 higher than that of PBOH on non-English languages.
Extracted statement — Material: 23 data sets
Research field: Digital Communications and Networking
Title: MAG: A Multilingual, Knowledge-base Agnostic and Deterministic Entity Linking Approach
Abstract: Entity linking has recently been the subject of a significant body of research. Currently, the best performing approaches rely on trained mono-lingual models. Porting these approaches to other languages is consequently a difficult endeavor as it requires corresponding training data and retraining of the models. We address this drawback by presenting a novel multilingual, knowledge-base agnostic and deterministic approach to entity linking, dubbed MAG. MAG is based on a combination of context-based retrieval on structured knowledge bases and graph algorithms. We evaluate MAG on 23 data sets and in 7 languages. Our results show that the best approach trained on English datasets (PBOH) achieves a micro F-measure that is up to 4 times worse on datasets in other languages. MAG on the other hand achieves state-of-the-art performance on English datasets and reaches a micro F-measure that is up to 0.6 higher than that of PBOH on non-English languages.
Extracted statement — Data: 4 times worse
Research field: Digital Communications and Networking
Title: MAG: A Multilingual, Knowledge-base Agnostic and Deterministic Entity Linking Approach
Abstract: Entity linking has recently been the subject of a significant body of research. Currently, the best performing approaches rely on trained mono-lingual models. Porting these approaches to other languages is consequently a difficult endeavor as it requires corresponding training data and retraining of the models. We address this drawback by presenting a novel multilingual, knowledge-base agnostic and deterministic approach to entity linking, dubbed MAG. MAG is based on a combination of context-based retrieval on structured knowledge bases and graph algorithms. We evaluate MAG on 23 data sets and in 7 languages. Our results show that the best approach trained on English datasets (PBOH) achieves a micro F-measure that is up to 4 times worse on datasets in other languages. MAG on the other hand achieves state-of-the-art performance on English datasets and reaches a micro F-measure that is up to 0.6 higher than that of PBOH on non-English languages.
Extracted statement — Material: 7 languages
Research field: Earth Sciences
Title: ASTER Data Analyses for Lithological Discrimination of Sittampundi Anorthositic Complex, Southern India
Abstract: ASTER is an advanced Thermal Emission and Reflection Radiometer, a multispectral sensor, which measures reflected and emitted electromagnetic radiation of earth surface with 14 bands. The present study aims to delineate different rock types in the Sittampundi Anorthositic Complex (SAC), Tamil Nadu using Visible (VIS), near-infrared (NIR) and short wave infrared (SWIR) reflectance data of ASTER 9 band data. We used different band ratioing, band combinations in the VNIR and SWIR region for discriminating lithological boundaries. SAC is also considered as a lunar highland analog rock. Anorthosite is a plagioclase-rich igneous rock with subordinate amounts of pyroxenes, olivine and other minerals. A methodology has been applied to correct the cross talk effect and radiance to reflectance. Principal Component Analysis (PCA) has been realized on the 9 ASTER bands in order to reduce the redundancy information in highly correlated bands. PCA derived FCC results enable the validation and support to demarcate the different lithological boundaries defined on previous geological map. The image derived spectral profiles for anorthosite are compared with the ASTER resampled laboratory spectra, JHU spectral library spectra and Apollo 14 lunar anorthosites spectra. The Spectral Angle Mapping imaging spectroscopy technique has been practiced to classify the ASTER image of the study area and found that, the processing of ASTER remote sensing data set can be used as a powerful tool for mapping the terrestrial Anorthositic regions and similar kind of process could be applied to map the planetary surfaces (E.g. Moon).
Extracted statement — reference: Apollo 14 lunar anorthosites spectra
Research field: Earth Sciences
Title: Development and utilization of urban spectral library for remote sensing of urban environment
Abstract: Hyperspectral technology is useful for urban studies due to its capability in examining detailed spectral characteristics of urban materials. This study aims to develop a spectral library of urban materials and demonstrate its application in remote sensing analysis of an urban environment. Field measurements were conducted by using ASD FieldSpec 3 Spectroradiometer with wavelength range from 350 to 2500 nm. The spectral reflectance curves of urban materials were interpreted and analyzed. A collection of 22 spectral data was compiled into a spectral library. The spectral library was put to practical use by utilizing the reference spectra for WorldView-2 satellite image classification which demonstrates the usability of such infrastructure to facilitate further progress of remote sensing applications in Malaysia.
Extracted statement — Sensors: ASD FieldSpec 3 Spectroradiometer