eScience Infrastructures in Physical Chemistry

As the volume of data associated with scientific research has exploded over recent years, the use of digital infrastructures to support this research and the data underpinning it has increased significantly. Physical chemists have been making use of eScience infrastructures since their conception, but in the last five years their usage has increased even more. While these infrastructures have not greatly affected the chemistry itself, they have in some cases had a significant impact on how the research is undertaken. The combination of the human effort of collaboration to create open source software tools and semantic resources, the increased availability of hardware for the laboratories, and the range of data management tools available has made the life of a physical chemist significantly easier. This review considers the different aspects of eScience infrastructures and explores how they have improved the way in which we can conduct physical chemistry research. Expected final online publication date for the Annual Review of Physical Chemistry, Volume 73 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

ERROR ANALYSIS OF CONJUNCTION IN EXPOSITORY ESSAY WRITING BY JORDANIAN UNDERGRADUATE STUDENTS STUDYING ENGLISH AS A FOREIGN LANGUAGE (EFL)

Academic writing is used a lot in the academic field and general writing as a distinct genre discourse in the linguistic and socio-cultural fields. Good writers generally use well-formed sentences; they often establish connections between sentences. Writing an essay is still a critical problem for most EFL undergraduate students since they are still not able to establish connections between sentences. The purpose of this study is to investigate the usage of conjunctions as cohesive devices in expository essays produced by EFL fourth-year undergraduate students majoring in the English language at the Department of English language and literature, Hashemite University in Jordan. A corpus of 30 expository essays was collected by using a simple purposive sampling technique to answer the questions of the study based on the theory of cohesion analysis by refining the grammatical cohesive related aspect based on Halliday and Hasan's (1976) taxonomy of conjunction. The results of this study confirm earlier studies showing English learners as a foreign language are having difficulty in using conjunctions in their writing. This study contributes to the written discourse and pedagogy within the field of teaching English for academic writing. The study recommends that grammatical cohesive devices and their function should be explained to the students through explicit teaching, not as separated grammatical items but as discourse semantic resources of text creation.

Il personaggio delle Grandi Parodie Disney tra intertestualità e serialità

ABSTRACT: Le Grandi Parodie Disney dei classici della letteratura costituiscono un’originale e intensa impresa creativa, cominciata nel 1949 con L’Inferno di Topolino e ancora oggi portata avanti con successo dagli autori Disney italiani. L’articolo si concentra sui procedimenti adattivi alla base delle Parodie, privilegiando quelli che investono in prima battuta l’elemento narrativo del personaggio. Il close reading condotto sull’Inferno di Topolino, parodia antesignana e manifesto dell’intero corpus, permette di osservare come sul personaggio della parodia si giochi in larga misura il mix di intertestualità e serialità che, con una considerevole prevalenza della seconda sulla prima, caratterizza questi adattamenti. In conclusione, si mostra come le risorse espressive e semantiche del personaggio seriale non solo comportino l’immediata riconoscibilità della parodia, ma sostengano significative innovazioni di ordine tematico-ideologico rispetto all’opera dantesca e coraggiose prese di posizione sull’importanza del fumetto seriale nel sistema culturale contemporaneo.Parole chiave: Grandi Parodie Disney. personaggio seriale. Intertestualità. Divina Commedia. Topolino. Resumo: Le Grandi Parodie Disney dos clássicos da literatura constituem um trabalho criativo original e intenso, que começou em 1949 com o Inferno de Mickey e ainda hoje é apresentado com sucesso por autores italianos da Disney. O artigo enfoca os procedimentos adaptativos subjacentes às paródias, privilegiando aquelas que envolvem, principalmente, o elemento narrativo do personagem. A leitura atenta realizada em O Inferno de Mickey, precursor da paródia e presente em todo o corpus, permite-nos observar como a mistura de intertextualidade e serialidade desempenha, em grande medida, o caráter da paródia que, com uma prevalência considerável do segundo sobre o primeiro, caracteriza essas adaptações. Desse modo, observa-se como os recursos expressivos e semânticos do personagem serial não só levam ao reconhecimento imediato da paródia, mas também sustentam significativas inovações temático-ideológicas no que diz respeito à obra de Dante e às posturas corajosas sobre a importância dos quadrinhos seriados no sistema cultural contemporâneo.Palavras-chave: Grandi Parodie Disney. Personagem serial. Intertextualidade. Divina Commedia. Mickey Mouse. ABSTRACT: The Great Disney Parodies of the classics of literature are a major creative enterprise, begun in 1949 with L’Inferno di Topolino and still successfully carried out by Italian Disney authors today. The article investigates the adaptive procedures of the Parodies, with a special focus on those involving the pivotal narrative element of the character. From the close reading of L’Inferno di Topolino, the first parody to be written and a manifesto of the entire corpus, it is possible to observe how the mix of intertextuality and seriality which distinguishes these adaptations hinges largely on the expressive and semantic resources of Disney serial characters. In the conclusion, the main effects of the prevailing of seriality over intertextuality are discussed, showing how it makes for the immediate recognizability of the parody, supports significant thematic-ideological innovations with respect to Dante's work, and allows for courageous metaliterary assertion on the importance of serial comics in the contemporary cultural system.Keywords: Grandi Parodie Disney. Serial character. Intertextuality. Divine Comedy. Mickey Mouse.

A Fine-Tuned Bidirectional Encoder Representations From Transformers Model for Food Named-Entity Recognition: Algorithm Development and Validation

Background Recently, food science has been garnering a lot of attention. There are many open research questions on food interactions, as one of the main environmental factors, with other health-related entities such as diseases, treatments, and drugs. In the last 2 decades, a large amount of work has been done in natural language processing and machine learning to enable biomedical information extraction. However, machine learning in food science domains remains inadequately resourced, which brings to attention the problem of developing methods for food information extraction. There are only few food semantic resources and few rule-based methods for food information extraction, which often depend on some external resources. However, an annotated corpus with food entities along with their normalization was published in 2019 by using several food semantic resources. Objective In this study, we investigated how the recently published bidirectional encoder representations from transformers (BERT) model, which provides state-of-the-art results in information extraction, can be fine-tuned for food information extraction. Methods We introduce FoodNER, which is a collection of corpus-based food named-entity recognition methods. It consists of 15 different models obtained by fine-tuning 3 pretrained BERT models on 5 groups of semantic resources: food versus nonfood entity, 2 subsets of Hansard food semantic tags, FoodOn semantic tags, and Systematized Nomenclature of Medicine Clinical Terms food semantic tags. Results All BERT models provided very promising results with 93.30% to 94.31% macro F1 scores in the task of distinguishing food versus nonfood entity, which represents the new state-of-the-art technology in food information extraction. Considering the tasks where semantic tags are predicted, all BERT models obtained very promising results once again, with their macro F1 scores ranging from 73.39% to 78.96%. Conclusions FoodNER can be used to extract and annotate food entities in 5 different tasks: food versus nonfood entities and distinguishing food entities on the level of food groups by using the closest Hansard semantic tags, the parent Hansard semantic tags, the FoodOn semantic tags, or the Systematized Nomenclature of Medicine Clinical Terms semantic tags.

Multi-modality Search and Recommendation on Palestinian Cultural Heritage Based on the Holy-Land Ontology and Extrinsic Semantic Resources

The Cultural Heritage (CH) sector and its associated tourism services have been affected notably by the advancement of the Internet as well as the explosive growth of smartphones and other handheld devices. These days, visitors can access reliable CH content using Web and mobile-based interfaces. However, conventional CH systems still lack the ability to provide meaningful semantically overt results that precisely meet user information needs in this domain. In addition, they often ignore the user search context and experience, which hinders their ability to adapt their behavior to the preferences, tasks, interests, and other user functionalities. In this article, we aim to address the issue of designing a precision-oriented multilingual and multi-criteria semantic-based mobile recommender system specifically targeting Palestine's CH, a country with great historical and cultural importance. We aim to better facilitate users’ access to CH content by providing them with multiple search functionalities. In this context, a user can search for relevant information using keywords (a.k.a. tags) or sentence-like queries and the system retrieves all relevant documents based on their semantic similarity. A second option is to search using current location information to retrieve correlated historical places and events. Finally, starting from a picture of interest, a third option makes it possible to extract captions describing its content that can be used to search for additional contextually relevant information. Additionally, the proposed system aims at personalizing users’ experience through progressively delivering output that meets their information needs based on a number of parameters such as users' logging data, interests, previous searches, and location-based information. A prototype of the proposed system has been developed and tested using Android smartphones and a manually constructed ontology enriched with CH links to the Art & Architecture Thesaurus (AAT) and DBpedia. By comparing our system with similar systems in this domain, findings demonstrate that it provides additional search features and functionalities to users. The proposed Holy-Land ontology is the first of its kind attempting to encode knowledge about Palestine's CH. It plays a crucial role in our proposal, serving as a pivotal entity in the combination of language-based, location-based, and visual-based retrieval strategies.

Exploring the Spatiotemporal Patterns of Residents’ Daily Activities Using Text-Based Social Media Data: A Case Study of Beijing, China

The use of social media data provided powerful data support to reveal the spatiotemporal characteristics and mechanisms of human activity, as it integrated rich spatiotemporal and textual semantic information. However, previous research has not fully utilized its semantic and spatiotemporal information, due to its technical and algorithmic limitations. The efficiency of the deep mining of textual semantic resources was also low. In this research, a multi-classification of text model, based on natural language processing technology and the Bidirectional Encoder Representations from Transformers (BERT) framework is constructed. The residents’ activities in Beijing were then classified using the Sina Weibo data in 2019. The results showed that the accuracy of the classifications was more than 90%. The types and distribution of residents’ activities were closely related to the characteristics of the activities and holiday arrangements. From the perspective of a short timescale, the activity rhythm on weekends was delayed by one hour as compared to that on weekdays. There was a significant agglomeration of residents’ activities that presented a spatial co-location cluster pattern, but the proportion of balanced co-location cluster areas was small. The research demonstrated that location conditions, especially the microlocation condition (the distance to the nearest subway station), were the driving factors that affected the resident activity cluster patterns. In this research, the proposed framework integrates textual semantic analysis, statistical method, and spatial techniques, broadens the application areas of social media data, especially text data, and provides a new paradigm for the research of residents’ activities and spatiotemporal behavior.

From Generative Linguistics to Categorial Grammars: Overt Subjects in Control Infinitives

The present thesis lies at the interface of logic and linguistics; its object of study are control sentences with overt pronouns in Romance languages (European and Brazilian Portuguese, Italian and Spanish). This is a topic that has received considerably more attention on the part of linguists, especially in recent years, than from logicians. Perhaps for this reason, much remains to be understood about these linguistic structures and their underlying logical properties. This thesis seeks to fill the lacunas in the literature or at least take steps in this direction by way of addressing a number of issues that have so far been under-explored. To this end, we put forward two key questions, one linguistic and the other logical. These are, respectively, (1) What is the syntactic status of the surface pronoun? and (2) What are the available mechanisms to reuse semantic resources in a contraction-free logical grammar? Accordingly, the thesis is divided into two parts: generative linguistics and categorial grammar. Part I starts by reviewing the recent discussion within the generative literature on infinitive clauses with overt subjects, paying detailed attention to the main accounts in the field. Part II does the same on the logical grammar front, addressing in particular the issues of control and of anaphoric pronouns. Ultimately, the leading accounts from both camps will be found wanting. The closing chapter of each of Part I and Part II will thus put forward alternative candidates, that we contend are more successful than their predecessors. More specifically, in Part I, we offer a linguistic account along the lines of Landau’s T/Agr theory of control. In Part II, we present two alternative categorial accounts: one based on Combinatory Categorial Grammar, the other on Type-Logical Grammar. Each of these accounts offers an improved, more fine-grained perspective on control infinitives featuring overt pronominal subjects. Finally, we include an Appendix in which our type-logical proposal is implemented in a categorial parser/theorem-prover.Abstract prepared by María Inés Corbalán.E-mail: [email protected]: http://repositorio.unicamp.br/jspui/handle/REPOSIP/331697

Participant’s Roles and Cognitive Relations in Niger Delta Conflict News Discourse

Media studies on Niger Delta (ND) conflict discourse have largely utilized stylistic, pragmatic, and critical discourse analytical tools in exploring media representation of news actors and ideologies in news texts but have not accommodated such issues as participants’ roles and cognitive relations in the discourse. This paper analyses the contexts of ND conflict news reporting with a view to revealing not only the participant’s role relations involved, but also the lexico-semantic resources they are characterized by. Forty newspaper reports on ND conflicts (20 from four ND-based newspapers— The Tide, New Waves, The Pointer and Pioneer, and 20 from four national newspapers— The Punch, The Guardian, Vanguard and THISDAY), published between 2003 and 2009, were sampled and subjected to discourse analysis, with insights from van Dijk’s context models and aspects of relational semantics. Four types of role were identified, viz. interactional (embracing the participants in conflict), communicative (relating to the production roles), social (involving group membership), and instrumental (dealing with the entities utilized in actualizing specific goals). The cognitive foci of these roles are associated with participants’ goals and beliefs, and these inform the participants’ position and hence role in the conflict events. Linguistically, the interactional and social roles are marked by synonymous and converse lexical items, while the communicative and instrumental roles are indexed by homonymous and antonymous lexical features. The findings corroborate the fact that there is an interaction between participant roles and cognitive relations in the ND conflict events reported in Nigerian newspapers.

Universal Discourse Representation Structure Parsing

We consider the task of cross-lingual semantic parsing in the style of Discourse Representation Theory (DRT) where knowledge from annotated corpora in a resource-rich language is transferred via bitext to guide learning in other languages. We introduce Universal Discourse Representation Theory (UDRT), a variant of DRT that explicitly anchors semantic representations to tokens in the linguistic input. We develop a semantic parsing framework based on the Transformer architecture and employ it to obtain semantic resources in multiple languages following two learning schemes. The Many-to-One approach translates non-English text to English, and then runs a relatively accurate English parser on the translated text, while the One-to-Many approach translates gold standard English to non-English text and trains multiple parsers (one per language) on the translations. Experimental results on the Parallel Meaning Bank show that our proposal outperforms strong baselines by a wide margin and can be used to construct (silver-standard) meaning banks for 99 languages.