Miracle-dz/UniFAR-FTUs huggingface dataset:
Facilitating Corpus Usage: Making Icelandic Corpora More Accessible for Researchers and Language Users

We introduce an array of open and accessible tools to facilitate the use of the Icelandic Gigaword Corpus, in the field of Natural Language Processing as well as for students, linguists, sociologists and others benefitting from using large corpora. A KWIC engine, powered by the Swedish Korp tool is adapted to the specifics of the corpus. An n-gram viewer, highly customizable to suit different needs, allows users to study word usage throughout the period of our text collection. A frequency dictionary provides much sought after information about word frequency statistics, computed for each subcorpus as well as aggregate, disambiguating homographs based on their respective lemmas and morphosyntactic tags. Furthermore, we provide n-grams based on the corpus, and a variety of pre-trained word embeddings models, based on word2vec, GloVe, fastText and ELMo. For three of the model types, multiple word embedding models are available trained with different algorithms and using either lemmatised or unlemmatised texts.
Event Extraction from Unstructured Amharic Text

In information extraction, event extraction is one of the types that extract the specific knowledge of certain incidents from texts. Event extraction has been done on different languages text but not on one of the Semitic language, Amharic. In this study, we present a system that extracts an event from unstructured Amharic text. The system has designed by the integration of supervised machine learning and rule-based approaches. We call this system a hybrid system. The system uses the supervised machine learning to detect events from the text and the handcrafted and the rule-based rules to extract the event from the text. For the event extraction, we have been using event arguments. Event arguments identify event triggering words or phrases that clearly express the occurrence of the event. The event argument attributes can be verbs, nouns, sometimes adjectives (such as ̃rg/wedding) and time as well. The hybrid system has compared with the standalone rule-based method that is well known for event extraction. The study has shown that the hybrid system has outperformed the standalone rule-based method.
Developing a Corpus of Indirect Speech Act Schemas

Resolving Indirect Speech Acts (ISAs), in which the intended meaning of an utterance is not identical to its literal meaning, is essential to enabling the participation of intelligent systems in peoples’ everyday lives. Especially challenging are those cases in which the interpretation of such ISAs depends on context. To test a system’s ability to perform ISA resolution we need a corpus, but developing such a corpus is difficult, especialy given the contex-dependent requirement. This paper addresses the difficult problems of constructing a corpus of ISAs, taking inspiration from relevant work in using corpora for reasoning tasks. We present a formal representation of ISA Schemas required for such testing, including a measure of the difficulty of a particular schema. We develop an approach to authoring these schemas using corpus analysis and crowdsourcing, to maximize realism and minimize the amount of expert authoring needed. Finally, we describe several characteristics of collected data, and potential future work.
A Lime-Flavored REST API for Alignment Services

A practical alignment service should be flexible enough to handle the varied alignment scenarios that arise in the real world, while minimizing the need for manual configuration. MAPLE, an orchestration framework for ontology alignment, supports this goal by coordinating a few loosely coupled actors, which communicate and cooperate to solve a matching task using explicit metadata about the input ontologies, other available resources and the task itself. The alignment task is thus summarized by a report listing its characteristics and suggesting alignment strategies. The schema of the report is based on several metadata vocabularies, among which the Lime module of the OntoLex-Lemon model is particularly important, summarizing the lexical content of the input ontologies and describing external language resources that may be exploited for performing the alignment. In this paper, we propose a REST API that enables the participation of downstream alignment services in the process orchestrated by MAPLE, helping them self-adapt in order to handle heterogeneous alignment tasks and scenarios. The realization of this alignment orchestration effort has been performed through two main phases: we first described its API as an OpenAPI specification (a la API-first), which we then exploited to generate server stubs and compliant client libraries. Finally, we switched our focus to the integration of existing alignment systems, with one fully integrated system and an additional one being worked on, in the effort to propose the API as a valuable addendum to any system being developed.
Visual Grounding Annotation of Recipe Flow Graph

In this paper, we provide a dataset that gives visual grounding annotations to recipe flow graphs. A recipe flow graph is a representation of the cooking workflow, which is designed with the aim of understanding the workflow from natural language processing. Such a workflow will increase its value when grounded to real-world activities, and visual grounding is a way to do so. Visual grounding is provided as bounding boxes to image sequences of recipes, and each bounding box is linked to an element of the workflow. Because the workflows are also linked to the text, this annotation gives visual grounding with workflow’s contextual information between procedural text and visual observation in an indirect manner. We subsidiarily annotated two types of event attributes with each bounding box: “doing-the-action,” or “done-the-action”. As a result of the annotation, we got 2,300 bounding boxes in 272 flow graph recipes. Various experiments showed that the proposed dataset enables us to estimate contextual information described in recipe flow graphs from an image sequence.
Constructing Web-Accessible Semantic Role Labels and Frames for Japanese as Additions to the NPCMJ Parsed Corpus

As part of constructing the NINJAL Parsed Corpus of Modern Japanese (NPCMJ), a web-accessible language resource, we are adding frame information for predicates, together with two types of semantic role labels that mark the contributions of arguments. One role type consists of numbered semantic roles, like in PropBank, to capture relations between arguments in different syntactic patterns. The other role type consists of semantic roles with conventional names.Both role types are compatible with hierarchical frames that belong to related predicates. Adding semantic role and frame information to the NPCMJ will support a web environment where language learners and linguists can search examples of Japanese for syntactic and semantic features. The annotation will also provide a language resource for NLP researchers making semantic parsing models (e.g., for AMR parsing) following machine learning approaches. In this paper, we describe how the two types of semantic role labels are defined under the frame based approach, i.e., both types can be consistently applied when linked to corresponding frames. Then we show special cases of syntactic patterns and the current status of the annotation work.
Comparing Machine Learning and Deep Learning Approaches on NLP Tasks for the Italian Language

We present a comparison between deep learning and traditional machine learning methods for various NLP tasks in Italian. We carried on experiments using available datasets (e.g., from the Evalita shared tasks) on two sequence tagging tasks (i.e., named entities recognition and nominal entities recognition) and four classification tasks (i.e., lexical relations among words, semantic relations among sentences, sentiment analysis and text classification). We show that deep learning approaches outperform traditional machine learning algorithms in sequence tagging, while for classification tasks that heavily rely on semantics approaches based on feature engineering are still competitive. We think that a similar analysis could be carried out for other languages to provide an assessment of machine learning / deep learning models across different languages.
How to Compare Automatically Two Phonological Strings: Application to Intelligibility Measurement in the Case of Atypical Speech

Atypical speech productions, regardless of their origins (accents, learning, pathology), need to be assessed with regard to “typical” or “expected” productions. Evaluation is necessarily based on comparisons between linguistic forms produced and linguistic forms expected. In the field of speech disorders, the intelligibility of a patient is evaluated in order to measure the functional impact of his/her pathology on his/her oral communication. The usual method is to transcribe orthographic linguistic forms perceived and to assign a global and imprecise rating based on their correctness or incorrect. To obtain a more precise evaluation of the production deviations, we propose a measurement method based on phonological transcriptions. An algorithm computes automatically and finely the distances between the phonological forms produced and expected from cost matrices based on the differences of features between phonemes. A first test of this method among a large population of healthy speakers and patients treated for cancer of the oral and pharyngeal cavities has proved its validity.
Automatic Extraction of Verb Paradigms in Regional Languages: the case of the Linguistic Crescent varieties

Language documentation is crucial for endangered varieties all over the world. Verb conjugation is a key aspect of this documentation for Romance varieties such as those spoken in central France, in the area of the Linguistic Crescent, which extends overs significant portions of the old provinces of Marche and Bourbonnais. We present a first methodological experiment using automatic speech processing tools for the extraction of verbal paradigms collected and recorded during fieldworks sessions made in situ. In order to prove the feasibility of the approach, we test it with different protocols, on good quality data, and we offer possible ways of extension for this research.
Collection and Annotation of the Romanian Legal Corpus

We present the Romanian legislative corpus which is a valuable linguistic asset for the development of machine translation systems, especially for under-resourced languages. The knowledge that can be extracted from this resource is necessary for a deeper understanding of how law terminology is used and how it can be made more consistent. At this moment the corpus contains more than 140k documents representing the legislative body of Romania. This corpus is processed and annotated at different levels: linguistically (tokenized, lemmatized and pos-tagged), dependency parsed, chunked, named entities identified and labeled with IATE terms and EUROVOC descriptors. Each annotated document has a CONLL-U Plus format consisting in 14 columns, in addition to the standard 10-column format, four other types of annotations were added. Moreover the repository will be periodically updated as new legislative texts are published. These will be automatically collected and transmitted to the processing and annotation pipeline. The access to the corpus will be done through ELRC infrastructure.
Growth limitation of submerged aquatic macrophytes by inorganic carbon

SUMMARY 1. This study determined the effects of CO2 and HCO3- enrichment on in situ growth of two submerged macrophytes, Elodea canadensis and Callitriche cophocarpa, in two Danish lakes: Lake Hampen and Lake Vaeng. Lake Hampen is an oligotrophic low-alkaline lake (0.4 meq −1) and Lake Vaeng is mesotrophic with an alkalinity of 1.1 meq 1-−1. In Lake Hampen experiments were carried out throughout the growth season, whereas experiments in Lake Vaeng were restricted to late summer. The CO2 and HCO3-enrichment procedures used increased the concentration of free-CO2 by 500–1000 μM and the concentration of HCO3- by about 80 μM. 2. The concentration of free-CO2 in Lake Hampen was about five times atmospheric equilibrium concentration (55 μM) in early summer declining to virtually zero at the end of summer. 3. Under ambient conditions Callitriche, which is restricted to CO2 use, was unable to grow and survive in both lakes. In contrast, Elodea, which has the potential to use HCO3- in photosynthesis, grew at rates varying from 0.046 to 0.080 day−1 over the season. 4. Under CO2 enrichment the growth rate of Callitriche varied from 0.089 to 0.124 day−1 and for Elodea from 0.076 to 0.117 day−1 over the season. Enrichment with HCO3-affected Elodea only and only to a limited extent. This may be a result of insufficient increase in [HCO3-] upon enrichment or to a limited capacity of the plants to take up HCO3-. 5. The substantial stimulation of in situ growth of Elodea and Callitriche by enhanced concentrations of free-CO2 shows that inorganic carbon is an important determinant of growth of submerged macrophytes and that inorganic carbon limitation of in situ growth may be a common phenomenon in nature, even in lakes with an alkalinity as high a 1 meq 1-−1. Inorganic carbon, however, is only one of many parameters important for growth, and the growth rates of Elodea at both ambient and high free-CO2 were closely coupled to day length and photon irradiance, indicating that light had an ultimate control on growth.
Modification of AQI as an Effective Representation of Air Quality by Considering Weighting Factors

Controversy persists because residents in regions where air quality is poor are always dissatisfied with the presentation of the air quality index (AQI). To make management policies acceptable, it needs to be determined whether adding the various weighting factors can make the AQI more reasonable and practical. The authors selected three indices i.e. AQI, revised air quality index (RAQI), and the air-dispersion AQI (ADRAQI) to compare their results in different atmospheric situations and to determine whether the AQI was made more reliable by adding various weighting factors such as multi-air pollutants and air dispersion derived from the mean function and an entropy function. Results show in comparison to AQI, the RAQI and ADRAQI have greater values in the multi-air pollutant and poor dispersion events, leading to a great difference between single air pollutant and multi-air pollutant events. The eclipsed phenomena in the AQI for the means of diseases related to air pollution such as acute atopic conjunctivitis, other chronic allergic conjunctivitis, other atopic dermatitis and related conditions, contact dermatitis and other eczema, and unspecified causes clearly appear. The findings suggest that the representation of AQI can be modified by considering the weighting factors of multiple air pollutants along with air dispersion; these can easily be applied to similar regions elsewhere.
The introduced seaweed Grateloupia turuturu (Rhodophyta, Halymeniales) in two Mediterranean transitional water systems

Abstract Lagoon environments are particularly subject to the introduction, either accidental or voluntary, of alien species that may cause biological pollution. On the basis of morphological data and molecular analyses (rbcL and mitochondrial cox2-cox3 spacer sequences) we confirmed the taxonomic identity (previously only hypothesised) of Grateloupia turuturu in both the Lagoon of Venice and the Mar Piccolo basin of Taranto, where it was most probably introduced by shellfish transfers. A detailed morphological description of vegetative and reproductive thalli is given, focusing particularly on the encrusting bases. The bases act as resting structures that are able to survive during unfavourable environmental conditions. In both the Lagoon of Venice and the Mar Piccolo of Taranto, G. turuturu does not yet exhibit invasive behaviour.
Inflammation and the glutamate system in schizophrenia: implications for therapeutic targets and drug development

Background: Despite the progress in antipsychotic therapy for schizophrenia, the effects are still not satisfactory. There is a high percentage of therapy-resistant patients and the overall course of the disease is unfavourable in many affected individuals. Therefore, other therapeutic targets than dopaminergic and serotonergic neurotransmitters are being considered. Objective: Glutamatergic hypofunction, mediated mainly by NMDA receptor blockade, is suggested to be indirectly responsible for dopaminergic dysfunction in schizophrenia. Increased levels of kynurenic acid (KYN-A), an endogenous NMDA receptor antagonist, resulting from disturbed tryptophan/kynurenine metabolism can explain psychotic symptoms and cognitive deterioration. Methods: The role of the immune system in the production of KYN-A and therapeutic targets in the immune and glutamate systems are outlined. Conclusions: Therapeutic consequences are discussed. Glutamate modulators that particularly influence the NMDA co-transmitters glycine and serine, including inhibitors of glycine transporters, are described and initial clinical evidence is discussed. Another target of the glutamate system is the metabotropic mGlu2/3 receptor; Preliminary clinical results of a study with a mGlu2/3 receptor agonist in schizophrenia are mentioned.
Measurable residual disease of acute lymphoblastic leukemia in allograft settings: how to evaluate and intervene

ABSTRACT Introduction Allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains a curable strategy for acute lymphoblastic leukemia (ALL), especially for adult cases. However, leukemia relapse after allograft restricts the improvement of transplant outcomes. Measurable residual disease (MRD) has been the strongest predictor for relapse after allo-HSCT, allowing MRD-directed preemptive therapy. Areas covered This manuscript summarizes the detection of MRD in patients with ALL who undergo allo-HSCT, focusing the effects of positive pre-HSCT MRD and post-HSCT MRD on outcomes as well as MRD-directed interventions. Expert opinion Except for MFC and RQ-PCR, other strategies, such as next-generation sequencing and RNAseq, have been developed for MRD determination. Negative effects of positive MRD peri-transplantation on outcomes of ALL patients were observed both in human leukocyte antigen (HLA)-matched sibling donor transplantation and in alternative donor transplantation. Advances have been made in determining the need for transplant according to MRD evaluation after induction or consolidation therapy. A number of approaches, including CAR-T-cell therapy, antibodies (blinatumomab, etc), targeted therapy (imatinib, etc), transplant donor selection, as well as donor lymphocyte infusion and interferon-α, have been successfully used or are promising for peri-transplantation MRD interventions. This progress could lead to the significant improvement of transplant outcomes for ALL patients.
Evaluation of a Blended Physical Activity Intervention for Older Adults: Mixed Methods Study

Background Physical activity can prolong the ability of older adults to live independently. Home-based exercises can help achieve the recommended physical activity levels. A blended intervention was developed to support older adults in performing home-based exercises. A tablet and a personal coach were provided to facilitate the self-regulation of exercise behavior. Objective In line with the Medical Research Council framework, this study aimed to carry out process evaluation of a blended intervention. The objectives were (1) to assess the long-term usability of the tablet adopted in the blended intervention and (2) to explore how the tablet, in conjunction with a personal coach, supported older adults in performing home-based exercises. Methods The process evaluation was conducted with a mixed-methods approach. At baseline, older adults participating in the blended intervention were asked to fill out a questionnaire about their general experience with information and communication technology (ICT) devices and rate their own skill level. After 6 months, participants filled out the Usefulness, Satisfaction, and Ease of use (USE) questionnaire to assess the usefulness, satisfaction, and ease of use of the tablet. With a random selection of participants, in-depth interviews were held to explore how the tablet and coach supported the self-regulation. The interviews were double coded and analyzed with the directed content analysis method. Results At baseline, 29% (65/224) of participants who started the intervention (mean age 72 years) filled out the ICT survey and 36% (37/103) of participants who used the tablet for 6 months (mean age 71 years) filled out the USE questionnaire. Furthermore, with 17% (18/103) of participants (mean age 73 years), follow-up interviews were held. The results of the baseline questionnaire showed that the large majority of participants already had experience with a tablet, used it regularly, and reported being skillful in operating ICT devices. After 6 months of use, the participants rated the usefulness, satisfaction, and ease of use of the tablet on average as 3.8, 4.2, and 4.1, respectively, on a 5-point scale. The analysis of the interviews showed that the participants felt that the tablet supported action planning, behavior execution, and self-monitoring. On the other hand, especially during the first few months, the personal coach added value during the goal setting, behavior execution, and evaluation phases of self-regulation. Conclusions The results of the process evaluation showed that older adults who participated in the study were positive about the blended intervention that was designed to support them in performing home-based exercises. Participants reported that the tablet helped them to perform the exercises better, more frequently, and safely. It supported them in various phases of self-regulation. The availability of a personal coach was nevertheless crucial. To support physical activity in older adults, a blended approach is promising.
True S-cones are concentrated in the ventral mouse retina and wired for color detection in the upper visual field

Color, an important visual cue for survival, is encoded by comparing signals from photoreceptors with different spectral sensitivities. The mouse retina expresses a short wavelength-sensitive and a middle/long wavelength-sensitive opsin (S- and M-opsin), forming opposing, overlapping gradients along the dorsal-ventral axis. Here, we analyzed the distribution of all cone types across the entire retina for two commonly used mouse strains. We found, unexpectedly, that ‘true S-cones’ (S-opsin only) are highly concentrated (up to 30% of cones) in ventral retina. Moreover, S-cone bipolar cells (SCBCs) are also skewed towards ventral retina, with wiring patterns matching the distribution of true S-cones. In addition, true S-cones in the ventral retina form clusters, which may augment synaptic input to SCBCs. Such a unique true S-cone and SCBC connecting pattern forms a basis for mouse color vision, likely reflecting evolutionary adaptation to enhance color coding for the upper visual field suitable for mice’s habitat and behavior.
Sublittoral abundance and food consumption of Baltic gobies

Two small demersal fishes, the sand goby Pomatoschistus minutus and the common goby Pomatoschistus microps, were quantified on soft bottoms at 20–40 m depth in the Baltic Sea, using a camera placed above the bottom. The largest numbers of gobies were seen following the settlement of young in late summer and autumn. Most recorded fishes were sand gobies. An annual average of 4·7 individuals m−2(0·24 g dry mass m−2) was recorded in 1983–1985 and 2·5 individuals m−2(0·13 g m−2) in 1997–1998. Using these densities, the annual goby food consumption was estimated to 100 kJ m−2 in 1983–1985 and 50 kJ m−2 in 1997–1998, corresponding to most of the annual macrobenthos production available to the gobies. The resulting goby production, assumed equal to 25% of the food consumed, must have been an important food source for the larger fishes occasionally recorded in the photographs.