Miracle-dz/UniFAR-FTUs huggingface dataset:
Do You Believe It Happened? Assessing Chinese Readers’ Veridicality Judgments

This work collects and studies Chinese readers’ veridicality judgments to news events (whether an event is viewed as happening or not). For instance, in “The FBI alleged in court documents that Zazi had admitted having a handwritten recipe for explosives on his computer”, do people believe that Zazi had a handwritten recipe for explosives? The goal is to observe the pragmatic behaviors of linguistic features under context which affects readers in making veridicality judgments. Exploring from the datasets, it is found that features such as event-selecting predicates (ESP), modality markers, adverbs, temporal information, and statistics have an impact on readers’ veridicality judgments. We further investigated that modality markers with high certainty do not necessarily trigger readers to have high confidence in believing an event happened. Additionally, the source of information introduced by an ESP presents low effects to veridicality judgments, even when an event is attributed to an authority (e.g. “The FBI”). A corpus annotated with Chinese readers’ veridicality judgments is released as the Chinese PragBank for further analysis.
Towards Flexible Cross-Resource Exploitation of Heterogeneous Language Documentation Data

This paper reports on challenges and solution approaches in the development of methods for language resource overarching data analysis in the field of language documentation. It is based on the successful outcomes of the initial phase of an 18 year long-term project on lesser resourced and mostly endangered indigenous languages of the Northern Eurasian area, which included the finalization and publication of multiple language corpora and additional language resources. While aiming at comprehensive cross-resource data analysis, the project at the same time is confronted with a dynamic and complex resource landscape, especially resulting from a vast amount of multi-layered information stored in the form of analogue primary data in different widespread archives on the territory of the Russian Federation. The methods described aim at solving the tension between unification of data sets and vocabularies on the one hand and maximum openness for the integration of future resources and adaption of external information on the other hand.
Do You Really Want to Hurt Me? Predicting Abusive Swearing in Social Media

Swearing plays an ubiquitous role in everyday conversations among humans, both in oral and textual communication, and occurs frequently in social media texts, typically featured by informal language and spontaneous writing. Such occurrences can be linked to an abusive context, when they contribute to the expression of hatred and to the abusive effect, causing harm and offense. However, swearing is multifaceted and is often used in casual contexts, also with positive social functions. In this study, we explore the phenomenon of swearing in Twitter conversations, taking the possibility of predicting the abusiveness of a swear word in a tweet context as the main investigation perspective. We developed the Twitter English corpus SWAD (Swear Words Abusiveness Dataset), where abusive swearing is manually annotated at the word level. Our collection consists of 1,511 unique swear words from 1,320 tweets. We developed models to automatically predict abusive swearing, to provide an intrinsic evaluation of SWAD and confirm the robustness of the resource. We also present the results of a glass box ablation study in order to investigate which lexical, syntactic, and affective features are more informative towards the automatic prediction of the function of swearing.
DiscSense: Automated Semantic Analysis of Discourse Markers

Using a model trained to predict discourse markers between sentence pairs, we predict plausible markers between sentence pairs with a known semantic relation (provided by existing classification datasets). These predictions allow us to study the link between discourse markers and the semantic relations annotated in classification datasets. Handcrafted mappings have been proposed between markers and discourse relations on a limited set of markers and a limited set of categories, but there exists hundreds of discourse markers expressing a wide variety of relations, and there is no consensus on the taxonomy of relations between competing discourse theories (which are largely built in a top-down fashion). By using an automatic prediction method over existing semantically annotated datasets, we provide a bottom-up characterization of discourse markers in English. The resulting dataset, named DiscSense, is publicly available.
Nuclear Countermeasure Activity of TP508 Linked to Restoration of Endothelial Function and Acceleration of DNA Repair

There is increasing evidence that radiation-induced damage to endothelial cells and loss of endothelial function may contribute to both acute radiation syndromes and long-term effects of whole-body nuclear irradiation. Therefore, several drugs are being developed to mitigate the effects of nuclear radiation, most of these drugs will target and protect or regenerate leukocytes and platelets. Our laboratory has demonstrated that TP508, a 23-amino acid thrombin peptide, activates endothelial cells and stem cells to revascularize and regenerate tissues. We now show that TP508 can mitigate radiation-induced damage to endothelial cells in vitro and in vivo. Our in vitro results demonstrate that human endothelial cells irradiation attenuates nitric oxide (NO) signaling, disrupts tube formation and induces DNA double-strand breaks (DSB). TP508 treatment reverses radiation effects on NO signaling, restores tube formation and accelerates the repair of radiation-induced DSB. The radiation-mitigating effects of TP508 on endothelial cells were also seen in CD-1 mice where systemic injection of TP508 stimulated endothelial cell sprouting from aortic explants after 8 Gy irradiation. Systemic doses of TP508 that mitigated radiation-induced endothelial cell damage, also significantly increased survival of CD-1 mice when injected 24 h after 8.5 Gy exposure. These data suggest that increased survival observed with TP508 treatment may be due to its effects on vascular and microvascular endothelial cells. Our study supports the usage of a regenerative drug such as TP508 to activate endothelial cells as a countermeasure for mitigating the effects of nuclear radiation.
Multi-scale rigid registration to detect damage in micro-CT images of progressively loaded bones

We present a method to detect damage in time-lapsed, micro-CT images of progressively loaded bone. The method we have developed splits the image into regions and performs registration on each region individually. The procedure is repeated with progressively smaller regions until either a minimum size or a maximum number of levels is reached. The regions are then classified as damaged or undamaged. This method has been successfully applied to three sets of images and tested with simulated damage. It will allow us to determine the characteristics of trabecular architecture that provide strength and to predict regions that are most likely to be damaged based on their structure.
Adjustable Robust OPF With Renewable Energy Sources

This paper presents an adjustable robust optimization approach to account for the uncertainty of renewable energy sources (RESs) in optimal power flow (OPF). It proposes an affinely adjustable robust OPF formulation where the base-point generation is calculated to serve the forecast load which is not balanced by RESs, and the generation control through participation factors ensures a feasible solution for all realizations of RES output within a prescribed uncertainty set. The adjustable robust OPF framework is solved using quadratic programming with successive constraint enforcement and can coordinate the computation of both the base-point generation and participation factors. Numerical results on standard test networks reveal a relatively small increase in the expected operational cost as the uncertainty level increases. In addition, solutions of networks that include both uncertain wind generation and Gaussian distributed demand are shown to have less cost and a higher level of robustness as compared to those from a recent robust scheduling method.
Broadband High-Gain SIW Cavity-Backed Circular-Polarized Array Antenna

A circularly polarized (CP) 4 × 4 array antenna based on substrate integrated waveguide (SIW) technology is presented. Circular polarization is achieved by applying the sequential rotation technique (SRT) with a well-designed sequential feed network and linear-polarized array elements. The proposed 4 × 4 array has a wide axial ratio (AR) bandwidth of 14% from 18.3 to 21.1 GHz with gain >13 dBic. Then, the array is expanded to achieve higher gains. A 16 × 16-element array is designed, fabricated, and tested. Test results show that the 16 × 16 array has an AR bandwidth of 13.8% from 18.5 to 21.25 GHz and a peak gain of 25.9 dBic at 20.5 GHz.
The BDCamões Collection of Portuguese Literary Documents: a Research Resource for Digital Humanities and Language Technology

This paper presents the BDCamões Collection of Portuguese Literary Documents, a new corpus of literary texts written in Portuguese that in its inaugural version includes close to 4 million words from over 200 complete documents from 83 authors in 14 genres, covering a time span from the 16th to the 21st century, and adhering to different orthographic conventions. Many of the texts in the corpus have also been automatically parsed with state-of-the-art language processing tools, forming the BDCamões Treebank subcorpus. This set of characteristics makes of BDCamões an invaluable resource for research in language technology (e.g. authorship detection, genre classification, etc.) and in language science and digital humanities (e.g. comparative literature, diachronic linguistics, etc.).
The outlook with bundle-branch block.

A series of papers on patients with various degrees of heart block (Campbell, 1942, 1943a, b, 1944) was meant to be completed with one on bundle-branch block. But when the war ended, my Lumleian lectures on the paroxysmal tachycardias (Campbell, 1947) occupied all my time until I became deeply involved in problems of malformations of the heart and their surgical treatment. Recently, when clearing out some filing cabinets I found these data on 50 patients with bundle-branch block. As most of them had been followed till they died, it seemed possible that they might still be of interest, especially as one with left bundle-branch block when 32 is still leading an active life after another 32 years.
Influence of physician empathy on the outcome of botulinum toxin treatment for upper limb spasticity in patients with chronic stroke: A cohort study.

OBJECTIVE To examine the relationship between patient-rated physician empathy and outcome of botulinum toxin treatment for post-stroke upper limb spasticity. DESIGN Cohort study. SUBJECTS Twenty chronic stroke patients with upper limb spasticity. METHODS All patients received incobotulinumtoxinA injection in at least one muscle for each of the following patterns: flexed elbow, flexed wrist and clenched fist. Each treatment was performed by 1 of 5 physiatrists with equivalent clinical experience. Patient-rated physician empathy was quantified with the Consultation and Relational Empathy Measure immediately after botulinum toxin treatment. Patients were evaluated before and at 4 weeks after botulinum toxin treatment by means of the following outcome measures: Modified Ashworth Scale; Wolf Motor Function Test; Disability Assessment Scale; Goal Attainment Scaling. RESULTS Ordinal regression analysis showed a significant influence of patient-rated physician empathy (independent variable) on the outcome (dependent variables) of botulinum toxin treatment at 4 weeks after injection, as measured by Goal Attainment Scaling (p<0.001). CONCLUSION These findings support the hypothesis that patient-rated physician empathy may influence the outcome of botulinum toxin treatment in chronic stroke patients with upper limb spasticity as measured by Goal Attainment Scaling.
Murine cytomegalovirus M78 protein, a G protein-coupled receptor homologue, is a constituent of the virion and facilitates accumulation of immediate-early viral mRNA

The M78 protein of murine cytomegalovirus exhibits sequence features of a G protein-coupled receptor. It is synthesized with early kinetics, it becomes partially colocalized with Golgi markers, and it is incorporated into viral particles. We have constructed a viral substitution mutant, SMsubM78, which lacks most of the M78 ORF. The mutant produces a reduced yield in cultured 10.1 fibroblast and IC21 macrophage cell lines. The defect is multiplicity dependent and greater in the macrophage cell line. Consistent with its growth defect in cultured cells, the mutant exhibits reduced pathogenicity in mice, generating less infectious progeny than wild-type virus in all organs assayed. SMsubM78 fails to efficiently activate accumulation of the viral m123 immediate-early mRNA in infected macrophages. M78 facilitates the accumulation of the immediate-early mRNA in cycloheximide-treated cells, arguing that it acts in the absence of de novo protein synthesis. We conclude that the M78 G protein-coupled receptor homologue is delivered to cells as a constituent of the virion, and it acts to facilitate the accumulation of immediate-early mRNA.
Variants of Vector Space Reductions for Predicting the Compositionality of English Noun Compounds

Predicting the degree of compositionality of noun compounds such as “snowball” and “butterfly” is a crucial ingredient for lexicography and Natural Language Processing applications, to know whether the compound should be treated as a whole, or through its constituents, and what it means. Computational approaches for an automatic prediction typically represent and compare compounds and their constituents within a vector space and use distributional similarity as a proxy to predict the semantic relatedness between the compounds and their constituents as the compound’s degree of compositionality. This paper provides a systematic evaluation of vector-space reduction variants across kinds, exploring reductions based on part-of-speech next to and also in combination with Principal Components Analysis using Singular Value and word2vec embeddings. We show that word2vec and nouns only dimensionality reductions are the most successful and stable vector space variants for our task.
A Supervised Part-Of-Speech Tagger for the Greek Language of the Social Web

The increasing volume of communication via microblogging messages on social networks has created the need for efficient Natural Language Processing (NLP) tools, especially for unstructured text processing. Extracting information from unstructured social text is one of the most demanding NLP tasks. This paper presents the first part-of-speech tagged data set of social text in Greek, as well as the first supervised part-of-speech tagger developed for such data sets.
Siamese-twin random projection neural network with Bagging Trees tuning for unsupervised binary image hashing

In this paper a Siamese-Twin Random Projection Neural Network (ST-RPNN) is proposed for unsupervised binary hashing of images. ST-RPNN is made of two identical random projection neural networks with hard threshold neurons where the binary code is taken as the neuron outputs. The learning objective is to produce similar binary codes for similar input image pairs and different binary codes otherwise. The learning process is divided into two steps. Firstly, overcomplete random projection is used to produce a sufficiently long code, followed by a fast sparse technique for neurons selection (FSNS). Bootstrap Aggregation Trees or Bagging Trees (BT) is then used to make a refined compact code section. BT is also used as a fast retrieval tool that ranks the database with respect to a query without distance calculations and with a significantly lower complexity than Hamming distance approach. The proposed technique is compared with 10 unsupervised image binary hashing techniques on the COREL1K dataset and the CIFAR10 dataset. The proposed technique obtained better precision-recall results than all compared techniques on the COREL1K dataset, and better than 8 of them on the CIFAR10 dataset.
EstNLTK 1.6: Remastered Estonian NLP Pipeline

The goal of the EstNLTK Python library is to provide a unified programming interface for natural language processing in Estonian. As such, previous versions of the library have been immensely successful both in academic and industrial circles. However, they also contained serious structural limitations – it was hard to add new components and there was a lack of fine-grained control needed for back-end programming. These issues have been explicitly addressed in the EstNLTK library while preserving the intuitive interface for novices. We have remastered the basic NLP pipeline by adding many data cleaning steps that are necessary for analyzing real-life texts, and state of the art components for morphological analysis and fact extraction. Our evaluation on unlabelled data shows that the remastered basic NLP pipeline outperforms both the previous version of the toolkit, as well as neural models of StanfordNLP. In addition, EstNLTK contains a new interface for storing, processing and querying text objects in Postgres database which greatly simplifies processing of large text collections. EstNLTK is freely available under the GNU GPL version 2 license, which is standard for academic software.
Outcome of Depression in Psychiatric Settings

We reviewed follow-up studies of adults with depressive disorders seen in psychiatric settings, and noted outcomes in terms of recovery, recurrence, and persistent depression, at six months, one year, two to five years, and ten or more years after an index episode of depression. Recovery increased with time: about half recovered at least briefly by six months, and a large majority did so in the long term. Only about a quarter recovered from an index episode and remained well more than ten years thereafter. A quarter of patients suffered recurrence of depression within a year of an index episode, and three-quarters did so at least once during follow-up periods lasting more than ten years. For more than one in ten patients, the depression proved persistent, the proportion affected remaining relatively stable over time. The review highlighted a relative paucity of conclusive investigations on the outcome of the commonest psychiatric disorder in clinical settings.
Neurogenesis in the mossy chiton, Mopalia muscosa (gould) (polyplacophora): Evidence against molluscan metamerism

Neurogenesis in the chiton Mopalia muscosa (Gould, 1846) was investigated by applying differential interference contrast microscopy, semithin serial sectioning combined with reconstruction techniques, as well as confocal laser scanning microscopy for the detection of fluorescence‐conjugated antibodies against serotonin and FMRFamide. The ontogeny of serotonergic nervous structures starts with cells of the apical organ followed by those of the cerebral commissure, whereas the serotonergic prototroch innervation, pedal system, and the lateral cords develop later. In addition, there are eight symmetrically arranged serotonergic sensory cells in the dorsal pretrochal area of the larva. FMRFamide‐positive neural elements include the cerebral commissure, specific “ampullary” sensory cells in the pretrochal region, as well as the larval lateral and pedal system. In the early juvenile the cerebral system no longer stains with either of the two antibodies and the pedal system lacks anti‐FMRFamide immunoreactivity. Outgroup comparison with all other molluscan classes and related phyla suggests that the cord‐like, nonganglionized cerebral system in the Polyplacophora is a reduced condition rather than a primitive molluscan condition. The immunosensitivity of the pedal commissures develops from posterior to anterior, suggesting independent serial repetition rather than annelid‐like conditions and there is no trace of true segmentation during nervous system development. Polyplacophoran neurogenesis and all other available data on the subject contradict the idea of a segmented molluscan stem species. J. Morphol. 253:109–117, 2002. © 2002 Wiley‐Liss, Inc.
Cairo Student Code-Switch (CSCS) Corpus: An Annotated Egyptian Arabic-English Corpus

Code-switching has become a prevalent phenomenon across many communities. It poses a challenge to NLP researchers, mainly due to the lack of available data needed for training and testing applications. In this paper, we introduce a new resource: a corpus of Egyptian- Arabic code-switch speech data that is fully tokenized, lemmatized and annotated for part-of-speech tags. Beside the corpus itself, we provide annotation guidelines to address the unique challenges of annotating code-switch data. Another challenge that we address is the fact that Egyptian Arabic orthography and grammar are not standardized.
Trypanosoma cruzi genotypes in Mepraia gajardoi from wild ecotopes in northern Chile.

We evaluated Trypanosoma cruzi infection in 397 wild Mepraia gajardoi specimens from five coastal localities in northern Chile by detection of minicircle DNA by polymerase chain reaction. The wild capture sites were classified into two ecotopes: a fully wild ecotope (ecotope 1) and a wild ecotope near human dwellings (ecotope 2). Infection rates varied between 11% and 27%. Minicircle hybridization assays showed that T. cruzi lineages Tc II and Tc VI were commonly detected in ecotope 1 and ecotope 2, respectively. These results are discussed in the context of insect proximity to human dwellings, the alimentary profile of Mepraia sp. , T. cruzi lineages detected in the past in the same disease-endemic area circulating in humans, and Triatoma infestans.
Tagging Location Phrases in Text

For over thirty years researchers have studied the problem of automatically detecting named entities in written language. Throughout this time the majority of such work has focused on detection and classification of entities into coarse-grained types like: PERSON, ORGANIZATION, and LOCATION. Less attention has been focused on non-named mentions of entities, including non-named location phrases such as “the medical clinic in Telonge” or “2 km below the Dolin Maniche bridge”. In this work we describe the Location Phrase Detection task to identify such spans. Our key accomplishments include: developing a sequential tagging approach; crafting annotation guidelines; building annotated datasets for English and Russian news; and, conducting experiments in automated detection of location phrases with both statistical and neural taggers. This work is motivated by extracting rich location information to support situational awareness during humanitarian crises such as natural disasters.
Turkish version of the Short Depression-Happiness Scale (SDHS): A validity and reliability study

The current study aims to adapt the Short Depression-Happiness Scale (SDHS) to Turkish culture and to investigate the psychometric characteristics of this scale. There were 380 respondents (179 female/199 male) ranging in age from 16 to 78 years. Confirmatory Factor Analysis (CFA) was used to explore construct validity of the SDHS and was correlated with OHQ-SF and SWLS as part of criterion-related validity. The reliability of the SDHS was analyzed by the internal consistency method. According to DFA results, that was conducted to determine whether the one-factor construct of the SDHS could be verified. Goodness of fit indices showed that a one-factor construct of the scale was also confirmed. Criterion-related validity analysis found that there were significant relationships between the SDHS and other measurement tools with regard to evaluating happiness. The internal consistency coefficient was . 80. Findings suggest that the Turkish form of the SDHS has a one factor construct, which could be used as a valid and reliable measurement tool for evaluating depression and happiness.