Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisiting the disease specificity and nomenclature of ficolin‐1–positive monocyte‐derived dendritic cells in diffuse cutaneous systemic sclerosis: comment on the article by Xue et al

measures; instead, information on a validated measure of disease activity would be ideal. Nevertheless, given the heterogeneity of the PsA diagnosis and the spectra of treatment strategies, we believe that assessing the impact of treatment exposure in detail provides important insights that augment the understanding of risks associated with a diagnosis of PsA. In our study, we found that adverse outcomes were more common among pregnant women with PsA than among pregnant women without PsA and that the highest risks were seen among those who were treated with antirheumatic medications, especially bDMARDs, during pregnancy. Although the use of bDMARDs during pregnancy has lately becomemore widespread, in our cohort of PsA pregnancies, 11% of women took bDMARDs during pregnancy, indirectly suggesting that women continuing this treatment most probably had severe disease. We do not attribute the increased risk of preterm birth and caesarean delivery to bDMARD treatment as such; however, we described an increased risk of adverse pregnancy outcomes in PsA patients who took bDMARDs compared with pregnancy outcomes in those without PsA. Our interpretation, as also expressed in our study, is that the increased risk of adverse outcomes in pregnancies with antirheumatic treatment is probably attributed to disease severity rather than an effect of the treatment itself. We agree that the underlying mechanisms of spontaneous preterm birth in women with PsA are not fully understood. We also endorse that metabolic factors might be of importance, as explored in a previous study from our group (2). In our current study, we were able to take known risk factors for spontaneous preterm birth into account. Very few of the 921 pregnant women with PsA in our cohort had hypertension or diabetes before pregnancy, although more women with PsA than without PsA were categorized as obese. However, in distribution of women with PsA in terms of obesity, the lowest proportion of obesity was among those who were taking bDMARDs, indicating that metabolic syndrome was not the main explanation for the increased risk of preterm birth in this cohort. In conclusion, our findings support that the risk of adverse pregnancy outcomes varies with presence, timing, and also type of antirheumatic treatment in women with PsA. The outcomes should not be interpreted as caused by the medications. It is of great importance to further elucidate the impact of maternal disease activity on pregnancy outcomes in PsA.
Altered intrinsic brain activity and connectivity in unaffected parents of individuals with autism spectrum disorder: a resting-state fMRI study

Objectives: Autism spectrum disorder (ASD) is a juvenile onset neurodevelopmental disorder with social impairment and stereotyped behavior as the main symptoms. Unaffected relatives may also exhibit similar ASD features due to genetic factors. Although previous studies have demonstrated atypical brain morphological features as well as task-state brain function abnormalities in unaffected parents with ASD children, it remains unclear the pattern of brain function in the resting state. Methods: A total of 42 unaffected parents of ASD children (pASD) and 39 age-, sex-, and handedness-matched controls were enrolled. Multiple resting-state fMRI (rsfMRI) analyzing methods were applied, including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), degree centrality (DC), and functional connectivity (FC), to reveal the functional abnormalities of unaffected parents in ASD-related brain regions. Spearman Rho correlation analysis between imaging metric values and the severity of ASD traits were evaluated as well. Results: ALFF, ReHo, and DC methods all revealed abnormal brain regions in the pASD group, such as the left medial orbitofrontal cortex (mOFC) and rectal gyrus (ROI-1), bilateral supplementary motor area (ROI-2), right caudate nucleus head and right amygdala/para-hippocampal gyrus (ROI-3). FC decreasing was observed between ROI-1 and right anterior cingulate cortex (ACC), ROI-2, and bilateral precuneus. FC enhancing was observed between ROI-3 and right anterior cerebellar lobe, left medial temporal gyrus, left superior temporal gyrus, left medial frontal gyrus, left precentral gyrus, right postcentral gyrus in pASD. In addition, ALFF values in ROI-1, DC values in ROI-3 were positively correlated with AQ scores in pASD (ρ1 = 0.298, P1 = 0.007; ρ2 = 0.220, P2 = 0.040), while FC values between ROI-1 and right ACC were negatively correlated with AQ scores (ρ3 = −0.334, P3 = 0.002). Conclusion: rsfMRI metrics could be used as biomarkers to reveal the underlying neurobiological feature of ASD for unaffected parents.
A review of the effects of artificial light at night in urban areas on the ecosystem level and the remedial measures

This paper attempts to realize the balance between humans and ecology in designing the nighttime light environment of urban parks by clarifying the influence of nighttime artificial light on the ecosystem of urban parks. Firstly, we reviewed the effects of nighttime artificial light on individual predation and reproduction of animals and personal growth and reproduction of plants. Secondly, we discuss the impact of individual changes caused by artificial lighting on ecosystem function at the ecosystem and analyze its advantages and disadvantages. The results showed that nighttime artificial light had a double-sided impact on the ecosystem, which would hurt the ecosystem function, but had a positive effect on the green space, which lacked natural light and had high plant density. This paper focuses on the areas with increased application of artificial lighting and rich species of animals and plants in night cities, such as urban forest parks and urban green spaces. It discusses how to reduce the intrusion of artificial lighting on ecosystems and how to make better use of the positive effect of artificial light.
Utility of dual-layer spectral-detector CT imaging for predicting pathological tumor stages and histologic grades of colorectal adenocarcinoma

Objectives To assess the utility of Dual-layer spectral-detector CT (DLCT) in predicting the pT stage and histologic grade for colorectal adenocarcinoma (CRAC). Methods A total of 131 patients (mean 62.7 ± 12.9 years; 72 female, 59 male) with pathologically confirmed CRAC (35 pT1-2, 61 pT3, and 35 pT4; 32 high grade and 99 low grade), who received dual-phase DLCT were enrolled in this retrospective study. Normalized iodine concentration (NIC), slope of the spectral HU curve (λHU), and effective atomic number (Eff-Z) were measured for each lesion by two radiologists independently. Intraobserver reliability and interobserver agreement were assessed. The above values were compared between three pT-stage and two histologic-grade groups. The correlation between the pT stages and above values were assessed. Receiver operating characteristic (ROC) curves were calculated to evaluate the diagnostic efficacy. Results Intra-class correlation coefficients were ranged from 0.856 to 0.983 for all measurements. Eff-Z [7.21(0.09) vs 7.31 (0.10) vs 7.35 (0.19)], NICAP [0.11 (0.05) vs 0.15 (0.08) vs 0.15 (0.08)], NICVP [0.27 (0.06) vs 0.34 (0.11) vs 0.35 (0.12)], λHUAP [1.20 (0.45) vs 1.93 (1.18) vs 2.37 (0.91)], and λHUVP [2.07 (0.68) vs 2.35 (0.62) vs 3.09 (1.07)] were significantly different among pT stage groups (all P<0.001) and exhibited a positive correlation with pT stages (r= 0.503, 0.455, 0.394, 0.512, 0.376, respectively, all P<0.001). Eff-Z [7.37 (0.10) vs 7.28 (0.08)], NICAP[0.20 (0.10) vs 0.13 (0.08)], NICVP[0.35 (0.07) vs 0.31 (0.11)], and λHUAP [2.59 (1.11) vs 1.63 (0.75)] in the high-grade group were markedly higher than those in the low-grade group (all P<0.05). For discriminating the advanced- from early-stage CARC, the AUCs of Eff-Z, NICAP, NICVP, λHUAP, and λHUVP were 0.83, 0.80, 0.79, 0.86, and 0.68, respectively (all P<0.001). For discriminating the high- from low-grade CARC, the AUCs of Eff-Z, NICAP, NICVP, and λHUAP were 0.81, 0.81, 0.64, and 0.81, respectively (all P<0.05). Conclusions The quantitative parameters derived from DLCT may provide new markers for assessing pT stages and histologic differentiation in patients with CRAC.
Repeated inhibition of sigma-1 receptor suppresses GABAA receptor expression and long-term depression in the nucleus accumbens leading to depressive-like behaviors

Sigma-1 receptor (σ1R) downregulation in male mice is known to cause a depressive-like phenotype. The nucleus accumbens (NAc), a region associated with affective regulation, has high levels of σ1R. Here, we investigated the effect of repeated inhibition of σ1R in the NAc on depressive-like behaviors and synaptic plasticity by microinjecting σ1R antagonist NE-100 into NAc nuclei in mice (NE-100 mice); this was followed by behavioral tests and field potentials recordings. We first examined the effect of NE-100 administration on σ1R expression and found that cell surface levels of σ1R were significantly reduced in the NAc of NE-100 mice. Compared to control mice, NE-100 mice exhibited significantly prolonged immobility in forced swim test (FST) and tail suspension test (TST), impaired long-term depression (LTD) as well as multi-spike waveform field excitatory postsynaptic potential (fEPSP) with an extended duration and an increased paired-pulse ratio (PPR). Reduced levels of GABAA receptor (GABAAR)-α1, -α2, -β2, and -β3 subunits, membrane D2R, and PKC phosphorylation in the NAc were observed in NE-100 mice. Activation of GABAAR by muscimol corrected the extended fEPSP duration and increased PPR, restored LTD maintenance as well as alleviated depressive-like behaviors in NE-100 mice. The decline of PKC phosphorylation in the NAc of NE-100 mice was corrected by injecting NAc with quinpirole, a D2R agonist. Injections of quinpirole or PMA (a PKC activator) into NAc of NE-100 mice rescued the expression levels of GABAAR, and alleviated the increase in PPR and impairment in LTD; these effects were sensitive to GF109203X, a PKC inhibitor. Furthermore, injecting NAc with quinpirole or PMA relieved depressive-like behaviors in NE-100 mice. Collectively, these results indicate that repeated inhibition of σ1R in the NAc reduces D2R-mediated PKC phosphorylation and suppresses GABAAR expression, thus impairing LTD maintenance and leading to depressive-like behaviors.
Editorial: Nutritional management for the development and gut health of young ruminants

COPYRIGHT © 2022 He, Gebeyew and Gha ari. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Nutritional management for the development and gut health of young ruminants
Multi-Epoch VERA Observations of Sagittarius A*. I. Images and Structural Variability

We report the results of multi-epoch observations of Sgr A* with VLBI Exploration of Radio Astrometry (VERA) at 43 GHz, carried out from 2004 to 2008. We detected a time variation of flux at 11 % level and intrinsic size at 19 %. In addition, comparisons with previous Very Long Baseline Array (VLBA) results shows that Sgr A* underwent the flaring event at least longer than 10 days in May 2007. The intrinsic size of Sgr A* remained unchanged within 1 � level from the size before/after the flaring event, indicating that the brightness temperature of Sgr A* was increased. The flaring event occurred within 31 d, which is shorter than the refractive time scale. Moreover it is difficult to explain the increase in the spectral index at the flaring event by the simple interstellar scattering model. Hence, the flaring event is most likely associated with the changes in intrinsic properties of Sgr A*. We considered the origin of the brightness temperature variation, and concluded that the flaring event of Sgr A* could be explained by the continuous heating of electrons, such as a standing shock in accretion flow.
Continuous lighting can improve yield and reduce energy costs while increasing or maintaining nutritional contents of microgreens

Microgreens represent a fast growing segment of the edible greens industry. They are prized for their colour, texture, and flavour. Compared to their mature counterparts, microgreens have much higher antioxidant and nutrient content categorizing them as a functional food. However, current production practices in plant factories with artificial light are energy intensive. Specifically, the lack of sunlight within the indoor structure means all of the light must be provided via energy consuming light fixtures, which is energy intensive and costly. Plant growth is usually increased with the total amount of light provided to the plants - daily light integral (DLI). Long photoperiods of low intensity lighting (greater than 18h) providing the desired/target DLI can reduce the capital costs for light fixtures and electricity costs. This is achieved by moving the electricity use from peak daytime hours (high price) to off-peak hours (low price) during the night in regions with time-based pricing scheme and lowering the electricity use for air conditioning, if plant growth is not compromised. However, lighting with photoperiods longer than tolerance thresholds (species/cultivar specific) usually leads to plant stress/damage. Therefore, we investigated the effects of continuous 24h white light (CL) at two DLIs (~14 and 21 mol m-2 d-1) on plant growth, yield, and antioxidant content on 4 types of microgreens - amaranth, collard greens, green basil, and purple basil to see if it compromises microgreen production. It was found that amaranth and green basil had larger fresh biomass when grown under CL compared to 16h when the DLIs were the same. In addition, purple basil had higher biomass at higher DLI, but was unaffected by photoperiods. Plants grown under the CL treatments had higher energy-use-efficiencies for lighting (10-42%) than plants grown under the 16h photoperiods at the same DLI. Notably, the electricity cost per unit of fresh biomass ($ g-1) was reduced (8-38%) in all microgreens studied when plants were grown under CL lighting at the same DLIs. Amaranth and collard greens also had higher antioxidant content. Taken together, growing microgreens under CL can reduce electricity costs and increase yield while maintaining or improving nutritional content.
Multilingual Abstract Meaning Representation for Celtic Languages

Deep Semantic Parsing into Abstract Meaning Representation (AMR) graphs has reached a high quality with neural-based seq2seq approaches. However, the training corpus for AMR is only available for English. Several approaches to process other languages exist, but only for high resource languages. We present an approach to create a multilingual text-to-AMR model for three Celtic languages, Welsh (P-Celtic) and the closely related Irish and Scottish-Gaelic (Q-Celtic). The main success of this approach are underlying multilingual transformers like mT5. We finally show that machine translated test corpora unfairly improve the AMR evaluation for about 1 or 2 points (depending on the language).
Crawling Under-Resourced Languages - a Portal for Community-Contributed Corpus Collection

The “Web as corpus” paradigm opens opportunities for enhancing the current state of language resources for endangered and under-resourced languages. However, standard crawling strategies tend to overlook available resources of these languages in favor of already well-documented ones. Since 2016, the “Crawling Under-Resourced Languages” portal (CURL) has been contributing to bridging the gap between established crawling techniques and knowledge about relevant Web resources that is only available in the specific language communities. The aim of the CURL portal is to enlarge the amount of available text material for under-resourced languages thereby developing available datasets further and to use them as a basis for statistical evaluation and enrichment of already available resources. The application is currently provided and further developed as part of the thematic cluster “Non-Latin scripts and Under-resourced languages” in the German national research consortium Text+. In this context, its focus lies on the extraction of text material and statistical information for the data domain “Lexical resources”.
MWE for Essay Scoring English as a Foreign Language

Mastering a foreign language like English can bring better opportunities. In this context, although multiword expressions (MWE) are associated with proficiency, they are usually neglected in the works of automatic scoring language learners. Therefore, we study MWE-based features (i.e., occurrence and concreteness) in this work, aiming at assessing their relevance for automated essay scoring. To achieve this goal, we also compare MWE features with other classic features, such as length-based, graded resource, orthographic neighbors, part-of-speech, morphology, dependency relations, verb tense, language development, and coherence. Although the results indicate that classic features are more significant than MWE for automatic scoring, we observed encouraging results when looking at the MWE concreteness through the levels.
Extraction and Classification of Acoustic Features from Italian Speaking Children with Autism Spectrum Disorders.

Autism Spectrum Disorders (ASD) are a group of complex developmental conditions whose effects and severity show high intraindividual variability. However, one of the main symptoms shared along the spectrum is social interaction impairments that can be explored through acoustic analysis of speech production. In this paper, we compare 14 Italian-speaking children with ASD and 14 typically developing peers. Accordingly, we extracted and selected the acoustic features related to prosody, quality of voice, loudness, and spectral distribution using the parameter set eGeMAPS provided by the openSMILE feature extraction toolkit. We implemented four supervised machine learning methods to evaluate the extraction performances. Our findings show that Decision Trees (DTs) and Support Vector Machines (SVMs) are the best-performing methods. The overall DT models reach a 100% recall on all the trials, meaning they correctly recognise autistic features. However, half of its models overfit, while SVMs are more consistent. One of the results of the work is the creation of a speech pipeline to extract Italian speech biomarkers typical of ASD by comparing our results with studies based on other languages. A better understanding of this topic can support clinicians in diagnosing the disorder.
Entity Linking in the ParlaMint Corpus

The ParlaMint corpus is a multilingual corpus consisting of the parliamentary debates of seventeen European countries over a span of roughly five years. The automatically annotated versions of these corpora provide us with a wealth of linguistic information, including Named Entities. In order to further increase the research opportunities that can be created with this corpus, the linking of Named Entities to a knowledge base is a crucial step. If this can be done successfully and accurately, a lot of additional information can be gathered from the entities, such as political stance and party affiliation, not only within countries but also between the parliaments of different countries. However, due to the nature of the ParlaMint dataset, this entity linking task is challenging. In this paper, we investigate the task of linking entities from ParlaMint in different languages to a knowledge base, and evaluating the performance of three entity linking methods. We will be using DBPedia spotlight, WikiData and YAGO as the entity linking tools, and evaluate them on local politicians from several countries. We discuss two problems that arise with the entity linking in the ParlaMint corpus, namely inflection, and aliasing or the existence of name variants in text. This paper provides a first baseline on entity linking performance on multiple multilingual parliamentary debates, describes the problems that occur when attempting to link entities in ParlaMint, and makes a first attempt at tackling the aforementioned problems with existing methods.
Movie Rating Prediction using Sentiment Features

We analyze the impact of using sentiment features in the prediction of movie review scores. The effort included the creation of a new lexicon, Expanded OntoSenticNet (EON), by merging OntoSenticNet and SentiWordNet, and experiments were made on the “IMDB movie review” dataset, with the three main approaches for sentiment analysis: lexicon-based, supervised machine learning and hybrids of the previous. Hybrid approaches performed the best, demonstrating the potential of merging knowledge bases and machine learning, but supervised approaches based on review embeddings were not far.
PriPA: A Tool for Privacy-Preserving Analytics of Linguistic Data

The days of large amorphous corpora collected with armies of Web crawlers and stored indefinitely are, or should be, coming to an end. There is a wealth of hidden linguistic information that is increasingly difficult to access, hidden in personal data that would be unethical and technically challenging to collect using traditional methods such as Web crawling and mass surveillance of online discussion spaces. Advances in privacy regulations such as GDPR and changes in the public perception of privacy bring into question the problematic ethical dimension of extracting information from unaware if not unwilling participants. Modern corpora need to adapt, be focused on testing specific hypotheses, and be respectful of the privacy of the people who generated its data. Our work focuses on using a distributed participatory approach and continuous informed consent to solve these issues, by allowing participants to voluntarily contribute their own censored personal data at a granular level. We evaluate our approach in a three-pronged manner, testing the accuracy of measurement of statistical measures of language with respect to standard corpus linguistics tools, evaluating the usability of our application with a participant involvement panel, and using the tool for a case study on health communication.
SciPar: A Collection of Parallel Corpora from Scientific Abstracts

This paper presents SciPar, a new collection of parallel corpora created from openly available metadata of bachelor theses, master theses and doctoral dissertations hosted in institutional repositories, digital libraries of universities and national archives. We describe first how we harvested and processed metadata from 86, mainly European, repositories to extract bilingual titles and abstracts, and then how we mined high quality sentence pairs in a wide range of scientific areas and sub-disciplines. In total, the resource includes 9.17 million segment alignments in 31 language pairs and is publicly available via the ELRC-SHARE repository. The bilingual corpora in this collection could prove valuable in various applications, such as cross-lingual plagiarism detection or adapting Machine Translation systems for the translation of scientific texts and academic writing in general, especially for language pairs which include English.