Appl In Vitro Toxicol. 2022 Mar 1;8(1):2-13. doi: 10.1089/aivt.2021.0010. Epub 2022 Mar 17.

ABSTRACT

INTRODUCTION: The AOP-Wiki is the main platform for the development and storage of adverse outcome pathways (AOPs). These AOPs describe mechanistic information about toxicodynamic processes and can be used to develop effective risk assessment strategies. However, it is challenging to automatically and systematically parse, filter, and use its contents. We explored solutions to better structure the AOP-Wiki content, and to link it with chemical and biological resources. Together, this allows more detailed exploration, which can be automated.

MATERIALS AND METHODS: We converted the complete AOP-Wiki content into resource description framework (RDF) triples. We used >20 ontologies for the semantic annotation of property-object relations, including the Chemical Information Ontology, Dublin Core, and the AOP Ontology.

RESULTS: The resulting RDF contains >122,000 triples describing 158 unique properties of >15,000 unique subjects. Furthermore, >3500 link-outs were added to 12 chemical databases, and >7500 link-outs to 4 gene and protein databases. The AOP-Wiki RDF has been made available at https://aopwiki.rdf.bigcat-bioinformatics.org.

DISCUSSION: SPARQL queries can be used to answer biological and toxicological questions, such as listing measurement methods for all Key Events leading to an Adverse Outcome of interest. The full power that the use of this new resource provides becomes apparent when combining the content with external databases using federated queries.

CONCLUSION: Overall, the AOP-Wiki RDF allows new ways to explore the rapidly growing AOP knowledge and makes the integration of this database in automated workflows possible, making the AOP-Wiki more FAIR.

PMID:35388368 | PMC:PMC8978481 | DOI:10.1089/aivt.2021.0010

Behav Res Methods. 2022 Apr 4. doi: 10.3758/s13428-021-01768-2. Online ahead of print.

ABSTRACT

For experimental research on language production, temporal precision and high quality of the recorded audio files are imperative. These requirements are a considerable challenge if language production is to be investigated online. However, online research has huge potential in terms of efficiency, ecological validity and diversity of study populations in psycholinguistic and related research, also beyond the current situation. Here, we supply confirmatory evidence that language production can be investigated online and that reaction time (RT) distributions and error rates are similar in written naming responses (using the keyboard) and typical overt spoken responses. To assess semantic interference effects in both modalities, we performed two pre-registered experiments (n = 30 each) in online settings using the participants' web browsers. A cumulative semantic interference (CSI) paradigm was employed that required naming several exemplars of semantic categories within a seemingly unrelated sequence of objects. RT is expected to increase linearly for each additional exemplar of a category. In Experiment 1, CSI effects in naming times described in lab-based studies were replicated. In Experiment 2, the responses were typed on participants' computer keyboards, and the first correct key press was used for RT analysis. This novel response assessment yielded a qualitatively similar, very robust CSI effect. Besides technical ease of application, collecting typewritten responses and automatic data preprocessing substantially reduce the work load for language production research. Results of both experiments open new perspectives for research on RT effects in language experiments across a wide range of contexts. JavaScript- and R-based implementations for data collection and processing are available for download.

PMID:35378676 | DOI:10.3758/s13428-021-01768-2

Proceedings (IEEE Int Conf Bioinformatics Biomed). 2021 Dec;2021:1818-1825. doi: 10.1109/bibm52615.2021.9669748.

ABSTRACT

The quality of patient-provider communication can predict the healthcare outcomes in patients, and therefore, training dental providers to handle the communication effort with patients is crucial. In our previous work, we developed an ontology model that can standardize and represent patient-provider communication, which can later be integrated in conversational agents as tools for dental communication training. In this study, we embark on enriching our previous model with an ontology of patient personas to portray and express types of dental patient archetypes. The Ontology of Patient Personas that we developed was rooted in terminologies from an OBO Foundry ontology and dental electronic health record data elements. We discuss how this ontology aims to enhance the aforementioned dialogue ontology and future direction in executing our model in software agents to train dental students.

PMID:35371617 | PMC:PMC8972912 | DOI:10.1109/bibm52615.2021.9669748

BMJ Open. 2022 Mar 29;12(3):e053123. doi: 10.1136/bmjopen-2021-053123.

ABSTRACT

INTRODUCTION: UK ambulance services have identified a concern with high users of the 999 service and have set up 'frequent callers' services, ranging from within-service management to cross-sectoral multidisciplinary case management approaches. There is little evidence about how to address the needs of this patient group.

AIM: To evaluate effectiveness, safety and efficiency of case management approaches to the care of people who frequently call the emergency ambulance service, and gain an understanding of barriers and facilitators to implementation.

OBJECTIVES: (1) Develop an understanding of predicted mechanisms of change to underpin evaluation. (2) Describe epidemiology of sustained high users of 999 services. (3) Evaluate case management approaches to the care of people who call the 999 ambulance service frequently in terms of: (i) Further emergency contacts (999, emergency department, emergency admissions to hospital) (ii) Effects on other services (iii) Adverse events (deaths, injuries, serious medical emergencies and police arrests) (iv) Costs of intervention and care (v) Patient experience of care. (4) Identify challenges and opportunities associated with using case management models, including features associated with success, and develop theories about how case management works in this population.

METHODS AND ANALYSIS: We will conduct a multisite mixed-methods evaluation of case management for people who use ambulance services frequently by using anonymised linked routine data outcomes in a 'natural experiment' cohort design, in four regional ambulance services. We will conduct interviews and focus groups with service users, commissioners and emergency and non-acute care providers. The planned start and end dates of the study are 1 April 2019 and 1 September 2022, respectively ETHICS AND DISSEMINATION: The study received approval from the UK Health Research Authority (Confidentiality Advisory Group reference number: 19/CAG/0195; research ethics committee reference number: 19/WA/0216).We will collate feedback from our Lived Experience Advisory Panel, the Frequent Caller National Network and Research Management Group for targeted dissemination activities.

PMID:35351702 | PMC:PMC8966558 | DOI:10.1136/bmjopen-2021-053123

J Biomed Semantics. 2022 Mar 28;13(1):11. doi: 10.1186/s13326-022-00266-4.

ABSTRACT

BACKGROUND: In life sciences, there has been a long-standing effort of standardization and integration of reference datasets and databases. Despite these efforts, many studies data are provided using specific and non-standard formats. This hampers the capacity to reuse the studies data in other pipelines, the capacity to reuse the pipelines results in other studies, and the capacity to enrich the data with additional information. The Regulatory Circuits project is one of the largest efforts for integrating human cell genomics data to predict tissue-specific transcription factor-genes interaction networks. In spite of its success, it exhibits the usual shortcomings limiting its update, its reuse (as a whole or partially), and its extension with new data samples. To address these limitations, the resource has previously been integrated in an RDF triplestore so that TF-gene interaction networks could be generated with two SPARQL queries. However, this triplestore did not store the computed networks and did not integrate metadata about tissues and samples, therefore limiting the reuse of this dataset. In particular, it does not enable to reuse only a portion of Regulatory Circuits if a study focuses on a subset of the tissues, nor to combine the samples described in the datasets with samples from other studies. Overall, these limitations advocate for the design of a complete, flexible and reusable representation of the Regulatory Circuits dataset based on Semantic Web technologies.

RESULTS: We provide a modular RDF representation of the Regulatory Circuits, called Linked Extended Regulatory Circuits (LERC). It consists in (i) descriptions of biological and experimental context mapped to the references databases, (ii) annotations about TF-gene interactions at the sample level for 808 samples, (iii) annotations about TF-gene interactions at the tissue level for 394 tissues, (iv) metadata connecting the knowledge graphs cited above. LERC is based on a modular organisation into 1,205 RDF named graphs for representing the biological data, the sample-specific and the tissue-specific networks, and the corresponding metadata. In total it contains 3,910,794,050 triples and is available as a SPARQL endpoint.

CONCLUSION: The flexible and modular architecture of LERC supports biologically-relevant SPARQL queries. It allows an easy and fast querying of the resources related to the initial Regulatory Circuits datasets and facilitates its reuse in other studies. ASSOCIATED WEBSITE: https://regulatorycircuits-lod.genouest.org.

PMID:35346379 | DOI:10.1186/s13326-022-00266-4

Cortex. 2022 May;150:48-60. doi: 10.1016/j.cortex.2022.01.019. Epub 2022 Feb 26.

ABSTRACT

Semantic cognition allows us to make sense of our varied experiences, including the words we hear and the objects we see. Contemporary accounts identify multiple interacting components that underpin semantic cognition, including diverse unimodal "spoke" systems that are integrated by a heteromodal "hub", and control processes that allow us to access weakly-encoded as well as dominant aspects of knowledge to suit the circumstances. The current study examined how these dimensions of semantic cognition might be related to whole-brain-derived components (or gradients) of connectivity. A nonlinear dimensionality reduction technique was applied to resting-state functional magnetic resonance imaging from 176 participants to characterise the strength of two key connectivity gradients in each individual: the principal gradient captured the separation between unimodal and heteromodal cortex, while the second gradient corresponded to the distinction between motor and visual cortex. We then examined whether the magnitude of these gradients within the semantic network was related to specific aspects of semantic cognition by examining individual differences in semantic and non-semantic tasks. Participants whose intrinsic connectivity showed a better fit with Gradient 1 had faster identification of weak semantic associations. Furthermore, a better fit with Gradient 2 was linked to faster performance on picture semantic judgements. These findings show that individual differences in aspects of semantic cognition can be related to components of connectivity within the semantic network.

PMID:35339787 | DOI:10.1016/j.cortex.2022.01.019

BMJ Open. 2022 Mar 24;12(3):e056974. doi: 10.1136/bmjopen-2021-056974.

ABSTRACT

OBJECTIVE: To improve our understanding of cancer in adults with intellectual disabilities.

DESIGN: Population-based study using linked data about deceased adults from the Learning (Intellectual) Disabilities Mortality Review (LeDeR) programme, the national cancer registry and NHS Digital.

SETTING: England.

PARTICIPANTS: 1096 adults with intellectual disabilities identified by the LeDeR programme who died between 1 January 2017 and 31 December 2019.

OUTCOME MEASURE: Any form of cancer listed as a long-term health condition by a LeDeR reviewer or 10th edition of the International Classification of Diseases codes C00-D49 included on Parts I or II of the Medical Certificate of Cause of Death.

RESULTS: In decedents with intellectual disabilities and cancer, more than a third (35%; n=162) had cancer diagnosed via emergency presentations. Almost half (45%; n=228) of cancers were at stage IV when diagnosed. More than a third (36%; n=309) of underlying causes of deaths were of cancers of the digestive system; almost half of these (48%; n=147) were cancer of the colon, rectum or anus. Of those who died with colorectal cancer, 43% were below the age threshold for colorectal screening.

CONCLUSIONS: In decedents with intellectual disabilities, symptoms suggestive of cancer had tended to be identified most frequently as an emergency and at a late stage. There is a need for greater awareness of symptoms of cancer in this population, a lower threshold for referral by General Practitioners (GPs), accelerated access to diagnosis and treatment and consideration paid to lowering the age for colorectal screening.

PMID:35332044 | PMC:PMC8948391 | DOI:10.1136/bmjopen-2021-056974

J Pers Med. 2022 Feb 25;12(3):354. doi: 10.3390/jpm12030354.

ABSTRACT

Ageism refers to stereotyping (how we think), prejudice (how we feel), and discrimination (how we act) against people based on their age. It is a serious public health issue that can negatively impact older people's health and quality of life. The present protocol has several goals: (1) adapt the Ambivalent Ageism Scale for the general Portuguese population and healthcare professionals; (2) assess the factorial invariance of the questionnaire between general population vs. healthcare professionals; (3) evaluate the level of ageism and its predictors in the general population and evaluate the level of ageism and its predictors in healthcare professionals; (4) compare the levels of ageism between groups and the invariance between groups regarding the explanatory model of predictors of ageism. This quantitative, cross-sectional, descriptive, observational study will be developed in partnership with several Healthcare Professional Boards/Associations, National Geriatrics and Gerontology Associations, and the Universities of the Third Age Network Association. The web-based survey will be conducted on a convenience sample recruited via various social media and institutional channels. The survey consists of three questionnaires: (1) Demographic data; (2) Ambivalent Ageism Scale; (3) Palmore-Neri and Cachioni questionnaire. The methodology of this study will include translation, pilot testing, semantic adjustment, exploratory and confirmatory factor analysis, and multigroup analysis of the Ambivalent Ageism Scale. Data will be treated using International Business Machines Corporation (IBM®) Statistical Package for the Social Sciences (SPSS) software and Analysis of Moment Structures (AMOS). Descriptive analysis will be conducted to assess the level of ageism in the study sample. The ageism levels between the two groups will be compared using the t-student test, and two Structural Equation Modeling will be developed to evaluate the predictors of ageism. Assessing ageism is necessary to allow healthcare professionals and policymakers to design and implement strategies to solve or reduce this issue. Findings from this study will generate knowledge relevant to healthcare and medical courses along with anti-ageism education for the Portuguese population.

PMID:35330354 | DOI:10.3390/jpm12030354

BMC Musculoskelet Disord. 2022 Mar 23;23(1):275. doi: 10.1186/s12891-022-05209-9.

ABSTRACT

BACKGROUND: In Sweden, the incidence of a prosthetic joint infection (PJI) after a planned Total Hip Arthroplasty (THA) is 1.3%, but the worldwide incidence of PJI after THA is unknown. This study explores associations between reoperation due to PJI and potential risk factors.

METHODS: Primary elective THA surgery registered in both the Swedish Hip Arthroplasty Registry (SHAR) and the Swedish Perioperative Registry (SPOR) between 1 January 2015 and 31 December 2019 were included in this registry study, resulting in a total study population of 35,056 cases. The outcome variable was reoperation as the result of PJI within a year after surgery. Data were analysed using a multivariable Cox regression model.

RESULTS: Reoperation due to PJI occurred in 460 cases (i.e., 1.3% of the study population). Each year of age increased the risk with 2% (HR 1.02 Cl 1.01, 1.03 P = < 0.001). Compared to men, women had significantly less risk for reoperation (HR 2.17 Cl 1.79, 2.53 P = < 0.001). For patients with obesity (BMI > 30), the risk increased considerably compared to underweight, normal weight, or overweight patients (HR 1.89 Cl 1.43, 2.51 P = < 0.001). The risk also increased by 6% for every 10 min of operative time (HR 1.06 Cl 1.02, 1.09 P = < 0.001). Patients having general anaesthesia had greater risk compared to those with spinal anaesthesia (HR 1.34 Cl 1.04, 1.73 P = 0.024). Finally, a lateral approach showed higher risk of reoperation than a posterior approach (HR 1.43 Cl 1.18, 1.73 P = < 0.001).

CONCLUSION: Recognition of the several risk factors identified in this study will be important for the perioperative management of patients undergoing THA.

PMID:35321672 | DOI:10.1186/s12891-022-05209-9

Environ Sci Pollut Res Int. 2022 Mar 22. doi: 10.1007/s11356-022-19733-7. Online ahead of print.

ABSTRACT

Hyperlipidemia, the most common form of dyslipidemia, is the main source of cardiovascular disorders, characterized by elevated level of total cholesterol (TC), triglycerides (TG) and low-density lipoprotein cholesterol (LDL-C) with high-density lipoprotein cholesterol (HDL-C) in peripheral blood. It is caused by a defect in lipid metabolism in the surface of Apoprotein C-II or a defect in lipoprotein lipase activity as well as reported in genetic, dietary and environmental factors. Several electronic databases were investigated as information sources, including Google Scholar, PubMed, Web of Science, Scopus, ScienceDirect, SpringerLink, Semantic Scholar, MEDLINE and CNKI Scholar. The current review focused on the risk factors of dyslipidemia, synthetic medication with their side effects and different types of medicinal plants having significant potential for the management of hyperlipidemia. The management of hyperlipidemia mostly involves a constant decrease in lipid level using different remedial drugs like statin, fibrate, bile acid sequestrates and niacin. However, this extensive review suggested that the consequences of these drugs are arguable, due to their numerous adverse effects. The selected parts of herb plants are used intact or their extracts containing active phytoconstituents to regulate the lipids in blood level. It was also noted that the Chinese herbal medicine and combination therapy is promising for the lowering of hyperlipidemia. This review intends to provide a scientific base for future endeavors, such as in-depth biological and chemical investigations into previously researched topics.

PMID:35320475 | DOI:10.1007/s11356-022-19733-7

Neuropsychol Rev. 2022 Mar 23. doi: 10.1007/s11065-022-09540-9. Online ahead of print.

ABSTRACT

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) or globus pallidum internus (GPi) improves motor functions in patients with Parkinson's disease (PD) but may cause a decline in specific cognitive domains. The aim of this systematic review and meta-analysis was to assess the long-term (1-3 years) effects of STN or GPi DBS on four cognitive functions: (i) memory (delayed recall, working memory, immediate recall), (ii) executive functions including inhibition control (Color-Word Stroop test) and flexibility (phonemic verbal fluency), (iii) language (semantic verbal fluency), and (iv) mood (anxiety and depression). Medline and Web of Science were searched, and studies published before July 2021 investigating long-term changes in PD patients following DBS were included. Random-effects model meta-analyses were performed using the R software to estimate the standardized mean difference (SMD) computed as Hedges' g with 95% CI. 2522 publications were identified, 48 of which satisfied the inclusion criteria. Fourteen meta-analyses were performed including 2039 adults with a clinical diagnosis of PD undergoing DBS surgery and 271 PD controls. Our findings add new information to the existing literature by demonstrating that, at a long follow-up interval (1-3 years), both positive effects, such as a mild improvement in anxiety and depression (STN, Hedges' g = 0,34, p = 0,02), and negative effects, such as a decrease of long-term memory (Hedges' g = -0,40, p = 0,02), verbal fluency such as phonemic fluency (Hedges' g = -0,56, p < 0,0001), and specific subdomains of executive functions such as Color-Word Stroop test (Hedges' g = -0,45, p = 0,003) were observed. The level of evidence as qualified with GRADE varied from low for the pre- verses post-analysis to medium when compared to a control group.

PMID:35318587 | DOI:10.1007/s11065-022-09540-9

AMIA Annu Symp Proc. 2022 Feb 21;2021:197-206. eCollection 2021.

ABSTRACT

The informed consent process is a complicated procedure involving permissions as well a variety of entities and actions. In this paper, we discuss the use of Semantic Web Rule Language (SWRL) to further extend the Informed Consent Ontology (ICO) to allow for semantic machine-based reasoning to manage and generate important permission-based information that can later be viewed by stakeholders. We present four use cases of permissions from the All of Us informed consent document and translate these permissions into SWRL expressions to extend and operationalize ICO. Our efforts show how SWRL is able to infer some of the implicit information based on the defined rules, and demonstrate the utility of ICO through the use of SWRL extensions. Future work will include developing formal and generalized rules and expressing permissions from the entire document, as well as working towards integrating ICO into software systems to enhance the semantic representation of informed consent for biomedical research.

PMID:35309008 | PMC:PMC8861693

World Wide Web. 2022 Mar 16:1-16. doi: 10.1007/s11280-022-01034-1. Online ahead of print.

ABSTRACT

Every epidemic affects the real lives of many people around the world and leads to terrible consequences. Recently, many tweets about the COVID-19 pandemic have been shared publicly on social media platforms. The analysis of these tweets is helpful for emergency response organizations to prioritize their tasks and make better decisions. However, most of these tweets are non-informative, which is a challenge for establishing an automated system to detect useful information in social media. Furthermore, existing methods ignore unlabeled data and topic background knowledge, which can provide additional semantic information. In this paper, we propose a novel Topic-Aware BERT (TABERT) model to solve the above challenges. TABERT first leverages a topic model to extract the latent topics of tweets. Secondly, a flexible framework is used to combine topic information with the output of BERT. Finally, we adopt adversarial training to achieve semi-supervised learning, and a large amount of unlabeled data can be used to improve inner representations of the model. Experimental results on the dataset of COVID-19 English tweets show that our model outperforms classic and state-of-the-art baselines.

PMID:35308294 | PMC:PMC8924578 | DOI:10.1007/s11280-022-01034-1

Front Toxicol. 2022 Feb 14;4:803983. doi: 10.3389/ftox.2022.803983. eCollection 2022.

ABSTRACT

Computational toxicology is central to the current transformation occurring in toxicology and chemical risk assessment. There is a need for more efficient use of existing data to characterize human toxicological response data for environmental chemicals in the US and Europe. The Adverse Outcome Pathway (AOP) framework helps to organize existing mechanistic information and contributes to what is currently being described as New Approach Methodologies (NAMs). AOP knowledge and data are currently submitted directly by users and stored in the AOP-Wiki (https://aopwiki.org/). Automatic and systematic parsing of AOP-Wiki data is challenging, so we have created the EPA Adverse Outcome Pathway Database. The AOP-DB, developed by the US EPA to assist in the biological and mechanistic characterization of AOP data, provides a broad, systems-level overview of the biological context of AOPs. Here we describe the recent semantic mapping efforts for the AOP-DB, and how this process facilitates the integration of AOP-DB data with other toxicologically relevant datasets through a use case example.

PMID:35295213 | PMC:PMC8915825 | DOI:10.3389/ftox.2022.803983

Sci Total Environ. 2022 Mar 12:154523. doi: 10.1016/j.scitotenv.2022.154523. Online ahead of print.

ABSTRACT

In this article, we propose that ecosystem services (ES) should be studied integrating social participation and the narrative of social actors. We analyzed the ES literature (1996-2020) in Latin America (LA), basing our review on the concept that the study of this topic should be transdisciplinary and post-normal (i.e., extended peer communities). We prepared the review using the Scopus® and Web of Science™ (WoS) databases. We found 1069 articles related to social participation in ES studies in 20 LA countries, identifying 310 articles for further analysis using screening and eligibility protocols. We also used a random sample (n = 50) of the 310 articles for a detailed analysis of social participation and extended peer communities. Results showed that articles increased from seven in 2010 to 39 per year from 2015 to 2019. English is the primary language used (91% of the articles), with only one journal accepting publications in Spanish. The most common collaboration combination has been one LA author and one or more non-LA authors (41% of the articles). The semantic network analysis showed 35 thematic clusters, with the most common corresponding to ES protection and provision issues. Direct social participation was included in 62% of the articles, mainly through interviews; however, consultancy processes have dominated the participatory perspective of the authors without transformative involvement. We discuss article language and low inter-countries collaboration, both influencing the lack of social participation required for the transdisciplinary analysis of ES.

PMID:35292319 | DOI:10.1016/j.scitotenv.2022.154523

J Biomed Semantics. 2022 Mar 15;13(1):9. doi: 10.1186/s13326-022-00264-6.

ABSTRACT

BACKGROUND: The European Platform on Rare Disease Registration (EU RD Platform) aims to address the fragmentation of European rare disease (RD) patient data, scattered among hundreds of independent and non-coordinating registries, by establishing standards for integration and interoperability. The first practical output of this effort was a set of 16 Common Data Elements (CDEs) that should be implemented by all RD registries. Interoperability, however, requires decisions beyond data elements - including data models, formats, and semantics. Within the European Joint Programme on Rare Diseases (EJP RD), we aim to further the goals of the EU RD Platform by generating reusable RD semantic model templates that follow the FAIR Data Principles.

RESULTS: Through a team-based iterative approach, we created semantically grounded models to represent each of the CDEs, using the SemanticScience Integrated Ontology as the core framework for representing the entities and their relationships. Within that framework, we mapped the concepts represented in the CDEs, and their possible values, into domain ontologies such as the Orphanet Rare Disease Ontology, Human Phenotype Ontology and National Cancer Institute Thesaurus. Finally, we created an exemplar, reusable ETL pipeline that we will be deploying over these non-coordinating data repositories to assist them in creating model-compliant FAIR data without requiring site-specific coding nor expertise in Linked Data or FAIR.

CONCLUSIONS: Within the EJP RD project, we determined that creating reusable, expert-designed templates reduced or eliminated the requirement for our participating biomedical domain experts and rare disease data hosts to understand OWL semantics. This enabled them to publish highly expressive FAIR data using tools and approaches that were already familiar to them.

PMID:35292119 | DOI:10.1186/s13326-022-00264-6

World Wide Web. 2022 Mar 10:1-25. doi: 10.1007/s11280-022-01005-6. Online ahead of print.

ABSTRACT

Online forumpost evaluationis an effective way for instructors to assess students' knowledge understanding and writing mechanics. Manually evaluating massive posts costs a lot of time. Automatically grading online posts could significantly alleviate instructors' burden. Similar text assessment tasks like Automated Text Scoring evaluate the writing quality of independent texts or relevance between text and prompt. And Automatic Short Answer Grading measures the semantic matching of short answers according to given problems and correct answers. Different from existing tasks, we propose a novel task, Automated Post Scoring (APS), which grades all online discussion posts in each thread of each student with given topics and quoted posts. APS evaluates not only the writing quality of posts automatically but also the relevance to topics. To measure the relevance, we model the semantic consistency between posts and topics. Supporting arguments are also extracted from quoted posts to enhance posts evaluation. Specifically, we propose a mixture model including a hierarchical text model to measure the writing quality, a semantic matching model to model topic relevance, and a semantic representation model to integrate quoted posts. We also construct a new dataset called Online Discussion Dataset containing 2,542 online posts from 694 students of a social science course. The proposed models are evaluated on the dataset with correlation and residual based evaluation metrics. Compared with measuring posts alone, experimental results demonstrate that incorporating topics and quoted posts could improve the performance of APS by a large margin, more than 9 percent on QWK.

PMID:35287331 | PMC:PMC8907391 | DOI:10.1007/s11280-022-01005-6

Can Rev Sociol. 2022 Mar 14. doi: 10.1111/cars.12377. Online ahead of print.

ABSTRACT

While sociologists have studied social networks for about one hundred years, recent developments in data, technology, and methods of analysis provide opportunities for social network analysis (SNA) to play a prominent role in the new research world of big data and computational social science (CSS). In our review, we focus on four broad topics: (1) Collecting Social Network Data from the Web, (2) Non-traditional and Bipartite/Multi-mode Networks, including Discourse and Semantic Networks, and Social-Ecological Networks, (3) Recent Developments in Statistical Inference for Networks, and (4) Ethics in Computational Network Research.

PMID:35286014 | DOI:10.1111/cars.12377

Proc Symp Appl Comput. 2021 Mar;2021:1941-1949. doi: 10.1145/3412841.3442066. Epub 2021 Apr 22.

ABSTRACT

Navigating back-and-forth between segments in webpages is well-known to be an arduous endeavor for blind screen-reader users, due to the serial nature of content navigation coupled with the inconsistent usage of accessibility enhancing features such as WAI-ARIA landmarks and skip navigation links by web developers. Without these supporting features, navigating modern webpages that typically contain thousands of HTML elements in their DOMs, is both tedious and cumbersome for blind screen-reader users. Existing approaches to improve non-visual navigation efficiency typically propose 'one-size-fits-all' solutions that do not accommodate the personal needs and preferences of screen-reader users. To fill this void, in this paper, we present sTag, a browser extension embodying a semi-automatic method that enables users to easily create their own Table Of Contents (TOC) for any webpage by simply 'tagging' their preferred 'semantically-meaningful' segments (e.g., search results, filter options, forms, menus, etc.) while navigating the webpage. This way, all subsequent accesses to these segments can be made via the generated TOC that is made instantly accessible via a special shortcut or a repurposed mouse/touchpad action. As tags in sTag are attached to the abstract semantic segments instead of actual DOM nodes in the webpage, sTag can automatically generate equivalent TOCs for other similar webpages, without requiring the users to duplicate their tagging efforts from scratch in these webpages. An evaluation with 15 blind screen-reader users revealed that sTag significantly reduced the content-navigation time and effort compared to those with a state-of-the-art solution.

PMID:35265951 | PMC:PMC8903019 | DOI:10.1145/3412841.3442066

Sci Rep. 2022 Mar 7;12(1):3672. doi: 10.1038/s41598-022-07615-4.

ABSTRACT

Semantic web (SW) technology has been widely applied to many domains such as medicine, health care, finance, geology. At present, researchers mainly rely on their experience and preferences to develop and evaluate the work of SW technology. Although the general architecture (e.g., Tim Berners-Lee's Semantic Web Layer Cake) of SW technology was proposed many years ago and has been well-known, it still lacks a concrete guideline for standardizing the development of SW technology. In this paper, we propose an SW technology index to standardize the development for ensuring that the work of SW technology is designed well and to quantitatively evaluate the quality of the work in SW technology. This index consists of 10 criteria that quantify the quality as a score of [Formula: see text]. We address each criterion in detail for a clear explanation from three aspects: (1) what is the criterion? (2) why do we consider this criterion and (3) how do the current studies meet this criterion? Finally, we present the validation of this index by providing some examples of how to apply the index to the validation cases. We conclude that the index is a useful standard to guide and evaluate the work in SW technology.

PMID:35256665 | DOI:10.1038/s41598-022-07615-4