Miracle-dz/UniFAR-FTUs huggingface dataset:
Touching virtual objects in mid-air: a study on shape recognition

Mid-air haptic technology allows designers to build touchless interfaces incorporating tactile feedback. In the present study, 17 students of the University of Siena were engaged in an experiment where they had to recognize shapes (a circle, a square, or a point) presented one at a time as mid-air haptic stimuli. The task was to discriminate if a stimulus (e.g. round stimulus on the palm of the hand) was compatible with an image (e.g. a circle) or a word (e.g. “circle”) displayed on a screen. The results indicate that only the “point” stimulus can lead to appreciable recognition performance, both in terms of accuracy and in relation to the time needed for the identification. No learning-based performance improvements were found. These results suggest that the haptic feedback provided by the mid-air technology used in the experiment is informative but difficult to discriminate and therefore it should be carefully designed in particular when associated to tasks requiring accuracy and speed of recognition.
Advances and Challenges in Unsupervised Neural Machine Translation

Unsupervised cross-lingual language representation initialization methods, together with mechanisms such as denoising and back-translation, have advanced unsupervised neural machine translation (UNMT), which has achieved impressive results. Meanwhile, there are still several challenges for UNMT. This tutorial first introduces the background and the latest progress of UNMT. We then examine a number of challenges to UNMT and give empirical results on how well the technology currently holds up.
To Block or not to Block: Experiments with Machine Learning for News Comment Moderation

Today, news media organizations regularly engage with readers by enabling them to comment on news articles. This creates the need for comment moderation and removal of disallowed comments – a time-consuming task often performed by human moderators. In this paper we approach the problem of automatic news comment moderation as classification of comments into blocked and not blocked categories. We construct a novel dataset of annotated English comments, experiment with cross-lingual transfer of comment labels and evaluate several machine learning models on datasets of Croatian and Estonian news comments. Team name: SuperAdmin; Challenge: Detection of blocked comments; Tools/models: CroSloEn BERT, FinEst BERT, 24Sata comment dataset, Ekspress comment dataset.
Social Media Variety Geolocation with geoBERT

This paper describes the Helsinki–Ljubljana contribution to the VarDial 2021 shared task on social media variety geolocation. Following our successful participation at VarDial 2020, we again propose constrained and unconstrained systems based on the BERT architecture. In this paper, we report experiments with different tokenization settings and different pre-trained models, and we contrast our parameter-free regression approach with various classification schemes proposed by other participants at VarDial 2020. Both the code and the best-performing pre-trained models are made freely available.
Sarcasm and Sentiment Detection in Arabic: investigating the interest of character-level features

We present three methods developed for the Shared Task on Sarcasm and Sentiment Detection in Arabic. We present a baseline that uses character n-gram features. We also propose two more sophisticated methods: a recurrent neural network with a word level representation and an ensemble classifier relying on word and character-level features. We chose to present results from an ensemble classifier but it was not very successful as compared to the best systems : 22th/37 on sarcasm detection and 15th/22 on sentiment detection. It finally appeared that our baseline could have been improved and beat those results.
Pathology Reporting in Neuroendocrine Neoplasms of the Digestive System: Everything You Always Wanted to Know but Were Too Afraid to Ask

During the 5th NIKE (Neuroendocrine tumors Innovation in Knowledge and Education) meeting, held in Naples, Italy, in May 2019, discussions centered on the understanding of pathology reports of gastroenetropancreactic neuroendocrine neoplasms. In particular, the main problem concerned the difficulty that clinicians experience in extrapolating relevant information from neuroendocrine tumor pathology reports. During the meeting, participants were asked to identify and rate issues which they have encountered, for which the input of an expert pathologist would have been appreciated. This article is a collection of the most rated questions and relative answers, focusing on three main topics: 1) morphology and classification; 2) Ki67 and grading; 3) immunohistochemistry. Patient management should be based on multidisciplinary decisions, taking into account clinical and pathology-related features with clear comprehension between all health care professionals. Indeed, pathologists require clinical details and laboratory findings when relevant, while clinicians require concise and standardized reports. In keeping with this last statement, the minimum requirements in pathology datasets are provided in this paper and should be a baseline for all neuroendocrine tumor professionals.
Named Entity Recognition and Linking Augmented with Large-Scale Structured Data

In this paper we describe our submissions to the 2nd and 3rd SlavNER Shared Tasks held at BSNLP 2019 and BSNLP 2021, respectively. The tasks focused on the analysis of Named Entities in multilingual Web documents in Slavic languages with rich inflection. Our solution takes advantage of large collections of both unstructured and structured documents. The former serve as data for unsupervised training of language models and embeddings of lexical units. The latter refers to Wikipedia and its structured counterpart - Wikidata, our source of lemmatization rules, and real-world entities. With the aid of those resources, our system could recognize, normalize and link entities, while being trained with only small amounts of labeled data.
Partisanship and Fear are Associated with Resistance to COVID-19 Directives

Ideological differences have had a large impact on individual and community response to the COVID-19 pandemic in the United States. Early behavioral research during the pandemic showed that conservatives were less likely to adhere to health directives, which contradicts a body of work suggesting that conservative ideology emphasizes a rule abiding, loss aversion, and prevention focus. We reconcile this contradiction by analyzing semantic content of local press releases, federal press releases, and localized tweets during the first month of the government response to COVID-19 in the United States. Controlling for factors such as COVID-19 confirmed cases and deaths, local economic indicators, and more, we find that online expressions of fear in conservative areas lead to an increase in adherence to public health recommendations concerning COVID-19, and that expressions of fear in government press releases are a significant predictor of expressed fear on Twitter.
20-Years Cumulative Impact From Shrimp Farming on Mangroves of Northeast Brazil

Brazilian mangroves cover about 11,100 km2 and provide a wide range of ecosystem services. Despite their importance, they are one of the most impacted ecosystems because of combined influences of climate change, pollution, and direct conversion and loss. A major driver of environmental impacts is shrimp farming and this is particularly acute in the semi-arid northeast of Brazil, where mangroves are constrained in a narrow band along ephemeral estuaries that are often impacted by multi-year droughts. Recent changes to Brazilian law, in particular the Forest Code, have weakened protection for mangroves and associated “apicum” (salt pan) ecosystems. In NE Brazil, most shrimp ponds are converted from mangrove-adjacent “apicuns” rather than the mangroves themselves with periodic hydrological connectivity through dammed channels, allowing the flushing of effluents. As a result, the main impacts on mangroves are typically indirect, because of pollution inputs from shrimp pond effluents and associated loss of ecosystem services including reductions in primary productivity, carbon storage capacity, resilience to other environmental stressors, their efficiency as estuarine filters, and biodiversity and abundance of subsistence use of marine species. Soil damage and infrastructure remaining after shrimp pond deactivation impairs mangrove recovery. This extends the duration of the damage and allows the occupation of degraded areas by other activities that can permanently impair ecosystem function. In this review, we address several aspects of the shrimp culture boom in NE Brazilian, their features and consequences, and the future of mangroves in the region considering climate change and rising poverty. Our conclusions on the practices and outcomes of shrimp farming in mangroves are likely to apply to areas with similar environmental settings, e.g., semiarid regions worldwide, and particularly in the Latin America and Caribbean region, and our findings can be taken into account to improve conservation and management of these forests at the least to a regional scale.
Enhancement of antioxidant activity, α-glucosidase and α-amylase inhibitory activities by spontaneous and bacterial monoculture fermentation of Indonesian black grape juices

This study was conducted to evaluate the in vitro antioxidant activity, α-glucosidase and α-amylase inhibitor activity of fermented black grape (Vitisvinifera) juice. In the present study black grape juice was prepared using spontaneous (SF) and monoculture fermentation (FL) of Lactobacillus plantarum FNCC 0027 and incubated for 48 h. The antioxidant capacity increased after fermentation. FL had the highest DPPH inhibition (81.32±3.45; p ≤ 0.05) compared to SF and unfermented (UF) black grape juice (75.17±1.47 and 65.63±1.02%, respectively). The pH values decreased during fermentation for both, SF and FL. M also had highest inhibition of α-glucosidase (80.15±3.23) and α-amylase (39.95±0.88). Fermentation of black grape juice using monoculture of L. plantarum has higher antioxidant activities and enzyme inhibitor effect than spontaneous and unfermented black grape juices (p ≤ 0.05). Thus fermented black grape juice may have the potential to serve as enhanced functional juice with anti-diabetic properties.
Language that Captivates the Audience: Predicting Affective Ratings of TED Talks in a Multi-Label Classification Task

The aim of the paper is twofold: (1) to automatically predict the ratings assigned by viewers to 14 categories available for TED talks in a multi-label classification task and (2) to determine what types of features drive classification accuracy for each of the categories. The focus is on features of language usage from five groups pertaining to syntactic complexity, lexical richness, register-based n-gram measures, information-theoretic measures and LIWC-style measures. We show that a Recurrent Neural Network classifier trained exclusively on within-text distributions of such features can reach relatively high levels of overall accuracy (69%) across the 14 categories. We find that features from two groups are strong predictors of the affective ratings across all categories and that there are distinct patterns of language usage for each rating category.
HerBERT: Efficiently Pretrained Transformer-based Language Model for Polish

BERT-based models are currently used for solving nearly all Natural Language Processing (NLP) tasks and most often achieve state-of-the-art results. Therefore, the NLP community conducts extensive research on understanding these models, but above all on designing effective and efficient training procedures. Several ablation studies investigating how to train BERT-like models have been carried out, but the vast majority of them concerned only the English language. A training procedure designed for English does not have to be universal and applicable to other especially typologically different languages. Therefore, this paper presents the first ablation study focused on Polish, which, unlike the isolating English language, is a fusional language. We design and thoroughly evaluate a pretraining procedure of transferring knowledge from multilingual to monolingual BERT-based models. In addition to multilingual model initialization, other factors that possibly influence pretraining are also explored, i.e. training objective, corpus size, BPE-Dropout, and pretraining length. Based on the proposed procedure, a Polish BERT-based language model – HerBERT – is trained. This model achieves state-of-the-art results on multiple downstream tasks.
Fine-tuning Distributional Semantic Models for Closely-Related Languages

In this paper we compare the performance of three models: SGNS (skip-gram negative sampling) and augmented versions of SVD (singular value decomposition) and PPMI (Positive Pointwise Mutual Information) on a word similarity task. We particularly focus on the role of hyperparameter tuning for Hindi based on recommendations made in previous work (on English). Our results show that there are language specific preferences for these hyperparameters. We extend the best settings for Hindi to a set of related languages: Punjabi, Gujarati and Marathi with favourable results. We also find that a suitably tuned SVD model outperforms SGNS for most of our languages and is also more robust in a low-resource setting.
New data on linyphiid spiders of Nepal (Arachnida: Araneae), with the description of a new genus and two species

Abstract: A new genus, Himalafurca gen. nov., with two new species, Himalafurca martensi sp. nov., the type species, and H. schawalleri sp. nov., are described from the Nepal Himalayas. The genus resembles Ketambea Millidge & Russell-Smith, 1992 and some other genera of unclear subfamily affiliation, but strongly differs by a few important structural features in the palp. All records of Collinsia japonica (Oi, 1964) from Nepal actually refer to Halorates crassipalpis (Caporiacco, 1935) comb. nov., here transferred from Collinsia. New localities for 21 species known from Nepal are given and six additional species are reported for the fauna of Nepal for the first time: Agyneta pakistanica Tanasevitch, 2011, Bathyphantes paracymbialis Tanasevitch, 2014a, Gnathonarium gibberum Oi, 1960, Nematogmus dentimanus Simon, 1886, Tiso aestivus (L. Koch, 1872) and T. indianus Tanasevitch, 2011. All mentioned species, except the last one, are also new to the fauna of the Himalayas. Taking into account the new data, the spider fauna of Nepal is currently known to include at least 107 linyphiid species, 90% of which presently can be considered as Himalayan endemics.
Deep Multi-Task Model for Sarcasm Detection and Sentiment Analysis in Arabic Language

The prominence of figurative language devices, such as sarcasm and irony, poses serious challenges for Arabic Sentiment Analysis (SA). While previous research works tackle SA and sarcasm detection separately, this paper introduces an end-to-end deep Multi-Task Learning (MTL) model, allowing knowledge interaction between the two tasks. Our MTL model’s architecture consists of a Bidirectional Encoder Representation from Transformers (BERT) model, a multi-task attention interaction module, and two task classifiers. The overall obtained results show that our proposed model outperforms its single-task and MTL counterparts on both sarcasm and sentiment detection subtasks.
Regression Analysis of Lexical and Morpho-Syntactic Properties of Kiezdeutsch

Kiezdeutsch is a variety of German predominantly spoken by teenagers from multi-ethnic urban neighborhoods in casual conversations with their peers. In recent years, the popularity of Kiezdeutsch has increased among young people, independently of their socio-economic origin, and has spread in social media, too. While previous studies have extensively investigated this language variety from a linguistic and qualitative perspective, not much has been done from a quantitative point of view. We perform the first large-scale data-driven analysis of the lexical and morpho-syntactic properties of Kiezdeutsch in comparison with standard German. At the level of results, we confirm predictions of previous qualitative analyses and integrate them with further observations on specific linguistic phenomena such as slang and self-centered speaker attitude. At the methodological level, we provide logistic regression as a framework to perform bottom-up feature selection in order to quantify differences across language varieties.
Freeze-drying synthesis and characterisation of Na composites of ZnO, TiO2 and ZnTiO3 semiconductor oxides

The freeze-drying method of metal oxides synthesis has a number of advantages such as high homogeneity, varying porous structures, morphologies and uniform particle size distribution, etc. Because of these advantages, the binary metal oxides ZnO, TiO2 and ternary metal oxide ZnTiO3 were synthesised by the freeze-drying method. The synthesised materials were characterised by X-ray diffraction (XRD), Fourier transform-infra red spectroscopy (FT-IR), UV-VIS spectroscopy, scanning electron microscopy (SEM) and energy dispersive X-ray analysis (EDAX). The as-synthesised metal oxides were calcined at different temperatures to study the phase evolution and morphological changes. The crystalline cubic-phase ZnTiO3 (a = 8.3948 Å) was obtained on calcination of the precursor at 600°C, and decomposed to the cubic phase Zn2TiO4 (a = 8.4580 Å) and rutile TiO2 (a = 4.5955 Å and c = 2.9593 Å) at 1000°C. The band gap of ZnO (3.28−3.10 eV), TiO2 (3.37−2.97 eV) and ZnTiO3 (3.92−3.80 eV) calculated using Tauc’s relation was found to vary inversely with calcination temperature and phase transition.
Effect of Educational Program About Partograph on Maternity Nurses’ Knowledge at Qena University Hospital –Egypt

Back ground: Half a million women lose their lives every year because of pregnancy related complications. Obstructed labour and ruptured uterus contributes up to 70% of maternal mortality. Early detection of abnormal progress and prevention of prolonged labour can significantly reduce it, so Partograph is considered to be a very effective tool to monitor labour and prevent prolonged and obstructed labour. Aim: to evaluate effect of educational program about partograph on maternity nurses’ knowledge at Qena University Hospital, Egypt. Subjects and Methods: A quiz -experimental research design was utilized in this study. The study was conducted at Qena University Hospital, Obstetric and Gynecological department and outpatient clinics Sample: Non probability convenience method was used as a technique of sampling; The total number of sample were consisting of 50 nurses Tools: The questionnaire was consisted of section A about demographic data section B about (questions related to partograph as fetal condition, maternal condition and progress of labour) Results: It was clear that 52.0 % of nurses aged <25 years. Also mean knowledge score in pretest is 10.04±4.59 and 40.48±3.51 in posttest. Conclusion: The finding concluded that the educational programme was a very successful way to develop the awareness of nurses about the use of partograph. Recommendation: Application of educational program, training course and workshop for all maternity nurses to enhance their knowledge regarding how using and application of partograph.
Chemie angeregter Zustände

Auf Grund des existierenden Zusammenhanges zwischen Charge-Transfer(CT)-Bande und Struktur von 7r-7T-Molekülkomplexen wird der Versuch unternommen, die experimentell unbekannte Konfiguration des Azulen-Tetracyanoäthylen(TCNÄ)-Komplexes theoretisch vorauszusagen. Zu diesem Zweck wird eine von KURODA et al. entwickelte SCF-MO-CI-Methode (in der 7t-Elektronennäherung) angewandt, die den Komplex als einheitliches rc-Elektronensystem unter Einschluß aller ß-Terme behandelt. Es wurden 24 verschiedene Konfigurationen des Komplexes berechnet, wobei die parallelen Molekülebenen der Komponenten sowohl horizontal als auch vertikal gegeneinander verschoben sind. Die vorgelagerte CT-Bande (bei etwa 13,5 kern ) zeigt eine wesentlich stärkere funktionelle Abhängigkeit bezüglich der räumlichen Orientierung der Komponenten, als dies beim Restspektrum der Fall ist. Aus der berechneten Lage der CT-Banden der einzelnen Konfigurationen und der Sequenz der intermolekularen Wechselwirkungsenergien bei festgehaltenem Molekülebenabstand ergibt sich im Rahmen dieses Modells die günstigste Konfiguration, wenn das TCNÄ-Molekül über dem 5-Ring (bei 3,4 A Molekülebenenabstand) nahe der 9-10-Bindung des Azulens liegt.
Framing Protest in Online News and Readers’ Comments: The Case of Serbian Protest “Against Dictatorship”

This research examines the “protest paradigm” in the digital news environment of a politically polarized media system by considering relations between news and online readers’ comments about the Serbian protest Against Dictatorship, which was held in 2017. Applying content analysis to news and comments from two news websites, our study indicates the need to account for opposing framing of the protest (violence/peacefulness, de/legitimizing and un/democratic) in a polarized environment. The results show that the distribution of opposing frames is guided by the media relations with the government. Online readers’ comments generally enhance this polarized pattern of frame distribution, with the exception of the performance frame, which remains prolific in the media, but absent from readers’ comments.
Thrust Measurements on the High Efficient and Reliable Vacuum Arc Thruster (HERVAT)

In this work, thrust measurements of the high efficient and reliable vacuum arc thruster (HERVAT) are performed for different pulse energies. The thruster system includes a thruster head together with a newly developed pulse processing unit (PPU). The complete system (HERVAT + PPU) is able to perform more than 1 × 107 pulses. Moreover, the influence of an integrated active magnetic nozzle is investigated. As a result, the thrust to power ratio, the average thrust level and the impulse bit for each configuration are measured and calculated. For the thrust measurements, a highly sensitive horizontal thrust balance with an active force actuator is used and operated in the thrust compensation mode. The investigated system is able to achieve levels from 5 to 40 μN and thrust to power ratios from 1 to 2 μN/W. The experimental results are compared to the data available in literature.
THE ROLE OF ORGANIZATIONAL COMMITMENT ON INDIVIDUAL CHARACTERISTICS THAT INFLUENCE OF AUDITOR ACCEPTANCE OF DYSFUNCTIONAL AUDIT BEHAVIOR

The purpose of this study is to analyze the organizational commitment that moderating effect on the individual characteristics, ie turnover intentions and the auditor performance toward the acceptance of dysfunctional audit behavior. The important issue that motivated this study is rampant various cases involving auditors. The important issue that motivated this study is rampant various cases involving auditors. The theory used in this research is attribution theory. The population in this study were the auditors who work in public accounting firm in Indonesia. Auditors who already have a working period at least one year as a criteria sample. Data obtained by questionnaire and analyzed using regression. The results showed that the characteristics of individuals which turnover intentions have a positive influence on the acceptance of dysfunctional audit behavior. While the auditors performance has a negative influence on the acceptance of dysfunctional audit behavior. The results of this study indicate that organizational commitment have a role as a moderating influence on the turmover intentions and auditor performance toward the acceptance of dysfunctional audit behavior. The results obtained from this study are expected to contribute to the development of the auditing literature, especially regarding the influence of individual characteristics on the performance of auditors which can be used as a reference in similar studies as well as an input for the firm in making policies to increase the performance of auditors.