DETEXA: declarative extensible text exploration and analysis through SQL.

Metadata enrichment through text mining techniques is becoming one of the most significant tasks in digital libraries. Due to the exponential increase of open access publications, several new challenges have emerged. Raw data are usually big, unstructured, and come from heterogeneous data sources. In this paper, we introduce a text analysis framework implemented in extended SQL that exploits the scalability characteristics of modern database management systems. The purpose of this framework is to provide the opportunity to build performant end-to-end text mining pipelines which include data harvesting, cleaning, processing, and text analysis at once. SQL is selected due to its declarative nature which offers fast experimentation and the ability to build APIs so that domain experts can edit text mining workflows via easy-to-use graphical interfaces. Our experimental analysis demonstrates that the proposed framework is very effective and achieves significant speedup, up to three times faster, in common use cases compared to other popular approaches.

Comparing Different Grasping Visualizations for Object Manipulation in VR using Controllers.

Virtual grasping is one of the most common and important interactions performed in a Virtual Environment (VE). Even though there has been substantial research using hand tracking methods exploring different ways of visualizing grasping, there are only a few studies that focus on handheld controllers. This gap in research is particularly crucial, since controllers remain the most used input modality in commercial Virtual Reality (VR). Extending existing research, we designed an experiment comparing three different grasping visualizations when users are interacting with virtual objects in immersive VR using controllers. We examine the following visualizations: the Auto-Pose (AP), where the hand is automatically adjusted to the object upon grasping; the Simple-Pose (SP), where the hand closes fully when selecting the object; and the Disappearing-Hand (DH), where the hand becomes invisible after selecting an object, and turns visible again after positioning it on the target. We recruited 38 participants in order to measure if and how their performance, sense of embodiment, and preference are affected. Our results show that while in terms of performance there is almost no significant difference in any of the visualizations, the perceived sense of embodiment is stronger with the AP, and is generally preferred by the users. Thus, this study incentivizes the inclusion of similar visualizations in relevant future research and VR experiences.

Linking Brain Structure, Activity, and Cognitive Function through Computation.

Understanding the human brain is a "Grand Challenge" for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuroscience, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neuroscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.

Wearables in sociodrama: An embodied mixed-methods study of expressiveness in social interactions.

This mixed-methods study investigates the use of wearable technology in embodied psychology research and explores the potential of incorporating bio-signals to focus on the bodily impact of the social experience. The study relies on scientifically established psychological methods of studying social issues, collective relationships and emotional overloads, such as sociodrama, in combination with participant observation to qualitatively detect and observe verbal and nonverbal aspects of social behavior. We evaluate the proposed method through a pilot sociodrama session and reflect on the outcomes. By utilizing an experimental setting that combines video cameras, microphones, and wearable sensors measuring physiological signals, specifically, heart rate, we explore how the synchronization and analysis of the different signals and annotations enables a mixed-method that combines qualitative and quantitative instruments in studying embodied expressiveness and social interaction.

Erratum: Wearables in sociodrama: An embodied mixed-methods study of expressiveness in social interactions-CORRIGENDUM.

[This corrects the article DOI: 10.1017/wtc.2022.7.].

NMR-STAR: comprehensive ontology for representing, archiving and exchanging data from nuclear magnetic resonance spectroscopic experiments.

The growth of the biological nuclear magnetic resonance (NMR) field and the development of new experimental technology have mandated the revision and enlargement of the NMR-STAR ontology used to represent experiments, spectral and derived data, and supporting metadata. We present here a brief description of the NMR-STAR ontology and software tools for manipulating NMR-STAR data files, editing the files, extracting selected data, and creating data visualizations. Detailed information on these is accessible from the links provided.

Prediction of inactive disease in juvenile idiopathic arthritis: a multicentre observational cohort study.

Objectives: To predict the occurrence of inactive disease in JIA in the first 2 years of disease. Methods: An inception cohort of 152 treatment-naïve JIA patients with disease duration <6 months was analysed. Potential predictors were baseline clinical variables, joint US, gut microbiota composition and a panel of inflammation-related compounds in blood plasma. Various algorithms were employed to predict inactive disease according to Wallace criteria at 6-month intervals in the first 2 years. Performance of the models was evaluated using the split-cohort technique. The cohort was analysed in its entirety, and separate models were developed for oligoarticular patients, polyarticular RF negative patients and ANA positive patients. Results: All models analysing the cohort as a whole showed poor performance in test data [area under the curve (AUC): <0.65]. The subgroup models performed better. Inactive disease was predicted by lower baseline juvenile arthritis DAS (JADAS)-71 and lower relative abundance of the operational taxonomic unit Mogibacteriaceae for oligoarticular patients (AUC in test data: 0.69); shorter duration of morning stiffness, higher haemoglobin and lower CXCL-9 levels at baseline for polyarticular RF negative patients (AUC in test data: 0.69); and shorter duration of morning stiffness and higher baseline haemoglobin for ANA positive patients (AUC in test data: 0.72). Conclusion: Inactive disease could not be predicted with satisfactory accuracy in the whole cohort, likely due to disease heterogeneity. Interesting predictors were found in more homogeneous subgroups. These need to be validated in future studies.

Nuclear markers support the mitochondrial phylogeny of Vipera ursinii-renardi complex (Squamata: Viperidae) and species status for the Greek meadow viper.

Meadow vipers (Vipera ursinii-renardi complex) are small-bodied snakes that live in either lowland grasslands or montane subalpine-alpine meadows spanning a distribution from France to western China. This complex has previously been the focus of several taxonomic studies which were based mainly on morphological, allozyme or immunological characters and did not clearly resolve the relationships between the various taxa. Recent mitochondrial DNA analyses found unexpected relationships within the complex which had taxonomical consequences for the detected lineages. The most surprising was the basal phylogenetic position of Vipera ursinii graeca, a taxon described almost 30 years ago from the mountains of Greece. We present here new analyses of three nuclear markers (BDNF, NT3, PRLR; a first for studies of meadow and steppe vipers) as well as analyses of newly obtained mitochondrial DNA sequences (CYT B, ND4).Our Bayesian analyses of nuclear sequences are concordant with previous studies of mitochondrial DNA, in that the phylogenetic position of the graeca clade is a clearly distinguished and distinct lineage separated from all other taxa in the complex. These phylogenetic results are also supported by a distinct morphology, ecology and isolated distribution of this unique taxon. Based on several data sets and an integrative species concept we recommend to elevate this taxon to species level: Vipera graeca Nilson & Andrén, 1988 stat. nov.

Publication of nuclear magnetic resonance experimental data with semantic web technology and the application thereof to biomedical research of proteins.

BACKGROUND: The nuclear magnetic resonance (NMR) spectroscopic data for biological macromolecules archived at the BioMagResBank (BMRB) provide a rich resource of biophysical information at atomic resolution. The NMR data archived in NMR-STAR ASCII format have been implemented in a relational database. However, it is still fairly difficult for users to retrieve data from the NMR-STAR files or the relational database in association with data from other biological databases. FINDINGS: To enhance the interoperability of the BMRB database, we present a full conversion of BMRB entries to two standard structured data formats, XML and RDF, as common open representations of the NMR-STAR data. Moreover, a SPARQL endpoint has been deployed. The described case study demonstrates that a simple query of the SPARQL endpoints of the BMRB, UniProt, and Online Mendelian Inheritance in Man (OMIM), can be used in NMR and structure-based analysis of proteins combined with information of single nucleotide polymorphisms (SNPs) and their phenotypes. CONCLUSIONS: We have developed BMRB/XML and BMRB/RDF and demonstrate their use in performing a federated SPARQL query linking the BMRB to other databases through standard semantic web technologies. This will facilitate data exchange across diverse information resources.

BioMagResBank.

The BioMagResBank (BMRB: www.bmrb.wisc.edu) is a repository for experimental and derived data gathered from nuclear magnetic resonance (NMR) spectroscopic studies of biological molecules. BMRB is a partner in the Worldwide Protein Data Bank (wwPDB). The BMRB archive consists of four main data depositories: (i) quantitative NMR spectral parameters for proteins, peptides, nucleic acids, carbohydrates and ligands or cofactors (assigned chemical shifts, coupling constants and peak lists) and derived data (relaxation parameters, residual dipolar couplings, hydrogen exchange rates, pK(a) values, etc.), (ii) databases for NMR restraints processed from original author depositions available from the Protein Data Bank, (iii) time-domain (raw) spectral data from NMR experiments used to assign spectral resonances and determine the structures of biological macromolecules and (iv) a database of one- and two-dimensional (1)H and (13)C one- and two-dimensional NMR spectra for over 250 metabolites. The BMRB website provides free access to all of these data. BMRB has tools for querying the archive and retrieving information and an ftp site (ftp.bmrb.wisc.edu) where data in the archive can be downloaded in bulk. Two BMRB mirror sites exist: one at the PDBj, Protein Research Institute, Osaka University, Osaka, Japan (bmrb.protein.osaka-u.ac.jp) and the other at CERM, University of Florence, Florence, Italy (bmrb.postgenomicnmr.net/). The site at Osaka also accepts and processes data depositions.