Miracle-dz/UniFAR-FTUs huggingface dataset:
Overview of MEX-A3T at IberLEF 2020: Fake News and Aggressiveness Analysis in Mexican Spanish

This paper presents the overview of MEX-A3T 2020, the third edition of this lab under the IberLEF conference. The main purpose of MEX-A3T is to explore different methodologies and strategies related to the analysis of social media content in Mexican Spanish. This year edition focuses in the identification of fake news and the detection of aggressive tweets. For this purpose, we provided different news from verified web sources and a corpus of tweets from Mexican users
End-to-End Neural Coder for Tumor Named Entity Recognition

This paper describes E2ENC, the system that we have developed to participate in CANTEMIST (CANcer TExt Mining Shared Task – tumor named entity recognition). E2ENC is a data-driven and end-to-end neural network-based system. It does not rely on external resources such as part-of-speech tagger. It proposes to solve two problems jointly; the first problem is to automatically extract the tumor morphology mentions that can be found in medical documents written in Spanish. The second task is to find the corresponding eCIE-O-3.1 codes for each extracted entity. E2ENC shows promising results, comparing to the baseline system. The reported results show that the proposed system achieve a micro-F1 of 84.9% and 77.7% on the test set for the first and second sub-tasks, respectively, and a MAP of 73.7% on the third sub-task.
High-resolution analogue of time-domain phonon spectroscopy in the transmission electron microscope

Femtosecond photoexcitation of semiconducting materials leads to the generation of coherent acoustic phonons (CAPs), the behaviours of which are linked to intrinsic and engineered electronic, optical and structural properties. While often studied with pump-probe spectroscopic techniques, the influence of nanoscale structure and morphology on CAP dynamics can be challenging to resolve with these all-optical methods. Here, we used ultrafast electron microscopy (UEM) to resolve variations in CAP dynamics caused by differences in the degree of crystallinity in as-prepared and annealed GaAs lamellae. Following in situ femtosecond photoexcitation, we directly imaged the generation and propagation dynamics of hypersonic CAPs in a mostly amorphous and, following an in situ photothermal anneal, a mostly crystalline lamella. Subtle differences in both the initial hypersonic velocities and the asymptotic relaxation behaviours were resolved via construction of space-time contour plots from phonon wavefronts. Comparison to bulk sound velocities in crystalline and amorphous GaAs reveals the influence of the mixed amorphous-crystalline morphology on CAP dispersion behaviours. Further, an increase in the asymptotic velocity following annealing establishes the sensitivity of quantitative UEM imaging to both structural and compositional variations through differences in bonding and elasticity. Implications of extending the methods and results reported here to elucidating correlated electronic, optical and structural behaviours in semiconducting materials are discussed. This article is part of a discussion meeting issue ‘Dynamic in situ microscopy relating structure and function'.
Visualizing single atom dynamics in heterogeneous catalysis using analytical in situ environmental scanning transmission electron microscopy

Progress is reported in analytical in situ environmental scanning transmission electron microscopy (ESTEM) for visualizing and analysing in real-time dynamic gas–solid catalyst reactions at the single-atom level under controlled reaction conditions of gas environment and temperature. The recent development of the ESTEM advances the capability of the established ETEM with the detection of fundamental single atoms, and the associated atomic structure of selected solid-state heterogeneous catalysts, in catalytic reactions in their working state. The new data provide improved understanding of dynamic atomic processes and reaction mechanisms, in activity and deactivation, at the fundamental level; and in the chemistry underpinning important technological processes. The benefits of atomic resolution-E(S)TEM to science and technology include new knowledge leading to improved technological processes, reductions in energy requirements and better management of environmental waste. This article is part of a discussion meeting issue ‘Dynamic in situ microscopy relating structure and function’.
End-to-End Learning for Conversational Recommendation: A Long Way to Go?

Conversational Recommender Systems (CRS) have received increased interest in recent years due to advances in natural language processing and the wider use of voice-controlled smart assistants. One technical approach to build such systems is to learn, in an end-to-end way, from recorded dialogs between humans. Recent proposals rely on neural architectures for learning such models. These models are often evaluated both with the help of computational metrics and with the help of human annotators. In the latter case, the task of human judges may consist of assessing the utterances generated by the models, e.g., in terms of their consistency with previous dialog utterances. However, such assessments may tell us not enough about the true usefulness of the resulting recommendation model, in particular when the judges only assess how good one model is compared to another. In this work, we therefore analyze the utterances generated by two recent end-to-end learning approaches for CRS on an absolute scale. Our initial analyses reveals that for each system about one third of the system utterances are not meaningful in the given context and would probably lead to a broken conversation. Furthermore, about less than two third of the recommendations were considered to be meaningful. Interestingly, none of the two systems “generated” utterances, as almost all system responses were already present in the training data. Overall, our works shows that (i) current approaches that are published at high-quality research outlets may have severe limitations regarding their usability in practice and (ii) our academic evaluation approaches for CRS should be reconsidered.
Featuristic: An interactive hybrid system for generating explainable recommendations - beyond system accuracy

Hybrid recommender systems (RS) have shown to improve system accuracy by combining beneﬁts from the collaborative ﬁltering (CF) and content-based (CB) approaches. Recently, the increasing complexity of such algorithms has fueled a demand for researchers to focus more on the user-oriented aspects such as explainability, user interaction, and control mechanisms. Even in cases, where explanations are provided, the systems mostly fall short in explaining the connection be-tween the recommended items and users’ preferred features. Additionally, in most cases, rating or re-evaluating items is typically the only option for users to specify or manipulate their preferences. With the purpose to provide advanced explanations, we implemented a prototype system called Featuristic , by applying a hybrid approach that uses content-features in a CF approach and exploits feature-based similarities. Ad-dressing important user-oriented aspects, we have integrated interactive mechanisms into the system to improve both preference elicitation and preference manipulation. Besides, we have integrated explanations for the recommendations into these interactive mechanisms. We evaluated our prototype system in two user studies to investigate the impact of the interactive explanations on the user-oriented aspects. The results showed that the Featuristic System with interactive explanations have signiﬁcantly improved users’ perception of the system in terms of the preference elicitation, explainability, and preference manipulation – compared to the systems that provide non-interactive explanations.
NCU-IISR: Pre-trained Language Model for CANTEMIST Named Entity Recognition

Since BERT has brought a huge improvement in various NLP tasks, the great constructed pre-trained language model shows its power of being fine-tuned in other downstream tasks either. In this paper, NCU-IISR team adopted the Spanish BERT, BETO, as our pre-trained model, and the model was fine-tuned on CANTEMIST Named Entity Recognition (NER) data. Besides, we also compared it with another fine-tuned version, which was trained on an external Spanish medical text. Finally, our best score achieved an F1-measure of 0.85 in the official test set result for CANTEMIST-NER task.
Fraudulent Behaviour Identification in Ethereum Blockchain

The phenomenon of cryptocurrencies continues to draw a lot of attention from investors, innovators and the general public. There are over 1300 different cryptocurrencies, including Bitcoin, Ethereum and Litecoin. While the scope of blockchain technology and cryptocurrencies continues to increase, identification of unethical and fraudulent behaviour still remains an open issue. The absence of regulation of the cryptocurrencies ecosystem and the lack of transparency of the transactions may lead to an increased number of fraudulent cases. In this research, we have analyzed the possibility to identify fraudulent behaviour using different classification techniques. Based on Etherium transactional data, we constructed a transaction network which was analyzed using a graph traversal algorithm. Data clustering was performed using three machine learning algorithms: k-means clustering, Support Vector Machine and random forest classifier. The performance of the classifiers was evaluated using a few accuracy metrics that can be calculated from confusion matrix. Research results revealed that the best performance was achieved using a random forest classification model
The Effect of Personality Traits on Persuading Recommender System Users

Persuasive Recommender System is a relatively new research direction that emphasizes on using persuasive approaches to increase user’s acceptance of the recommendations. Recent studies have demonstrated the feasibility of deploying the six persuasive principles of Cialdini as explanations besides the recommended items. These principles, however, should not be treated in a one-size-fits-all approach. Instead, they should be deployed in a personalized manner. The factors that help to personalize these principles for the users of recommender systems have not been fully explored. To fill this gap, this paper investigates one of these factors, which is personality traits. In particular, it explores the influence of the Big Five Personalities on recommender system users’ susceptibility to Ciladini’s persuasive principles. The study contains two parts; the impact of personality traits as an independent variable, and the impact of personality traits in conjunction with the application domain. We explored these factors through a questionnaire disseminated online. The analysis of the data received from (279) responses shows that personality traits are an important factor that influences the efficiency of the six principles of Cialdini. Moreover, the effect of personality traits becomes more significant if they are considered in combination with the application domain.
Analysis of complex, beam-sensitive materials by transmission electron microscopy and associated techniques

We review the use of transmission electron microscopy (TEM) and associated techniques for the analysis of beam-sensitive materials and complex, multiphase systems in-situ or close to their native state. We focus on materials prone to damage by radiolysis and explain that this process cannot be eliminated or switched off, requiring TEM analysis to be done within a dose budget to achieve an optimum dose-limited resolution. We highlight the importance of determining the damage sensitivity of a particular system in terms of characteristic changes that occur on irradiation under both an electron fluence and flux by presenting results from a series of molecular crystals. We discuss the choice of electron beam accelerating voltage and detectors for optimizing resolution and outline the different strategies employed for low-dose microscopy in relation to the damage processes in operation. In particular, we discuss the use of scanning TEM (STEM) techniques for maximizing information content from high-resolution imaging and spectroscopy of minerals and molecular crystals. We suggest how this understanding can then be carried forward for in-situ analysis of samples interacting with liquids and gases, provided any electron beam-induced alteration of a specimen is controlled or used to drive a chosen reaction. Finally, we demonstrate that cryo-TEM of nanoparticle samples snap-frozen in vitreous ice can play a significant role in benchmarking dynamic processes at higher resolution. This article is part of a discussion meeting issue ‘Dynamic in situ microscopy relating structure and function’.
Taxonomic Status of a Population of Black Ixalotriton from Cerro Baúl, Chiapas, México

Abstract Only two species of Ixalotriton, I. niger and I. parvus, are currently known, and both are endemic to small regions of Chiapas, México. An additional population of black Ixalotriton has recently been reported from caves on Cerro Baúl, near the only known locality of I. parvus. We conducted morphological and molecular analyses of animals from the new population and I. niger to determine whether they are conspecific. Animals from the Cerro Baúl population resemble I. niger morphologically, but they are somewhat divergent in mitochondrial sequence. We assign them to I. niger because of the lack of diagnostic morphological differences. This expands the range of I. niger to a second locality and puts the two species of Ixalotriton in sympatry, although they are separated by microhabitat. Protection for the new population is urgently needed, given declines in abundance of I. niger at the type locality.
Climate and land use change impacts on Mediterranean high-mountain vegetation in the Apennines since the 1950s

Background: High-mountain ecosystems are centres of plant diversity that are particularly sensitive to land-use and climate change. Aims: We investigated the ecological trends associated with land use and climate change since the 1950s in different vegetation types in high-mountain habitats in the central Apennines. Methods: We analysed temporal changes in: Pinus mugo scrub, calcareous subalpine grasslands and alpine scree vegetation, comparing historical and recent vegetation records from vegetation plots from two periods (1955–1980 and 1990–2014) for their ecological indicator values (Landolt temperature and nutrient indicators) and structural traits (growth forms) over time using generalised linear models (GLMs). Results: We observed significant temporal differences in the ecology and structure of the analysed habitats. In the Pinus mugo scrub we detected a reduction of subalpine and herbaceous species and in calcareous alpine screes we observed an increment of the lower montane, montane and subalpine species and of dwarf shrubs. Conversely, subalpine grasslands were stable over time. Conclusions: Ecological changes that have occurred in the Central Apennines, following changes in type and intensity of land use and recent warming are consistent with those observed in other European mountains, for which climate and land-use changes are claimed as the main driving forces.
Effect of heat shock protein 27 on the in vitro degradation of myofibrils by caspase‐3 and &mgr;‐calpain

Summary This study was designed to investigate the effect of heat shock protein 27 (HSP27) on the in vitro degradation of myofibrils induced by caspase-3 or μ-calpain. Myofibrillar proteins were prepared from at-death beef muscles and incubated with caspase-3 or μ-calpain with and without HSP27, or with HSP27 alone, at 30 °C for 2 h, and protein degradation was assessed. Results showed that caspase-3 promoted the degradation of titin, nebulin and troponin-T, and μ-calpain promoted the degradation of nebulin, desmin and troponin-T, observed during normal PM ageing. Moreover, the addition of HSP27 restricted the degradation of troponin-T in μ-calpain- and caspase-3-treated myofilaments, and restricted the degradation of desmin in μ-calpain-treated myofilaments. Therefore, HSP27 may indirectly or directly interact with caspase-3 and μ-calpain, reducing their activity and mediating PM proteolysis of muscle proteins to affect meat tenderisation.
Biomodification Strategies for the Development of Antimicrobial Urinary Catheters: Overview and Advances

Microbial burden associated with medical devices poses serious health challenges and is accountable for an increased number of deaths leading to enormous medical costs. Catheter‐associated urinary tract infections are the most common hospital‐acquired infections with enhanced patient morbidity. Quite often, catheter‐associated bacteriuria produces apparent adverse outcomes such as urosepsis and even death. Taking this into account, the methods to modify urinary catheters to control microbial infections with relevance to clinical drug resistance are systematically evaluated in this review. Technologies to restrict biofilm formation at initial stages by using functional nanomaterials are elucidated. The conventional methodology of using single therapeutic intervention for developing an antimicrobial catheter lacks clinically meaningful benefit. Therefore, catheter modification using naturally derived antimicrobials such as essential oils, curcumin, enzymes, and antimicrobial peptides in combination with synthetic antibiotics/nanoantibiotics is likely to exert sufficient inhibitory effect on uropathogens and is extensively discussed. Futuristic efforts in this area are projected here that demand clinical studies to address areas of uncertainty to avoid development of bacterial resistance to the new generation therapy with minimum discomfort to the patients.
An ODE-based mixed modelling approach for B- and T-cell dynamics induced by Varicella-Zoster Virus vaccines in adults shows higher T-cell proliferation with Shingrix compared to Varilrix

Clinical trials covering the immunogenicity of a vaccine aim to study the longitudinal dynamics of certain immune cells after vaccination. The corresponding immunogenicity datasets are mainly analyzed by the use of statistical (mixed effects) models. This paper proposes the use of mathematical ordinary differential equation (ODE) models, combined with a mixed effects approach. ODE models are capable of translating underlying immunological post vaccination processes into mathematical formulas thereby enabling a testable data analysis. Mixed models include both population-averaged parameters (fixed effects) and individual-specific parameters (random effects) for dealing with inter-and intra-individual variability, respectively. This paper models B-cell and T-cell datasets of a phase I/II, open-label, randomized, parallel-group study in which the immunogenicity of a new Herpes Zoster vaccine (Shingrix) is compared with the original Varicella Zoster Virus vaccine (Varilrix). Since few significant correlations were assessed between the B-cell datasets and T-cell datasets, each dataset was modeled separately. By following a general approach to both the formulation of several different models and the procedure of selecting the most suitable model, we were able propose a mathematical ODE mixed-effects model for each dataset. As such, the use of ODE-based mixed effects models offers a suitable framework for handling longitudinal vaccine immunogenicity data. Moreover, it is possible to test differences in immunological processes between the two vaccines. We found that the Shingrix vaccination schedule led to a more pronounced proliferation of T-cells, without a difference in T-cell decay rate compared to the Varilrix vaccination schedule. Author summary Upon vaccination, B-cells and T-cells are activated to induce an immune response against the vaccine antigen at hand. In this paper, we study and compare the longitudinal dynamics of the specific immune response based on a vaccine trial in which the immunogenicity of a new Herpes Zoster vaccine (Shingrix) is compared with the original Varicella Zoster Virus vaccine (Varilrix). We combine the use of ordinary differential equations (ODEs), i.e. mathematical models which are used to describe the dynamics of the immune response, with advanced regression analyses enabling us to infer the model parameters describing these dynamics. The resulting ODE-based mixed effects models enable describing the immune response dynamics allowing for both inter-and intra-individual variability; comparing the dynamics induced by the two vaccines and studying the B-and T-cell interactions. We found a more pronounced proliferation of T-cells for the Shingrix vaccination schedule as compared to the Varilrix vaccination schedule. The proposed methodology offers a suitable framework for better understanding the immunogenicity of vaccines.
Complete chloroplast genome of the tree fern Alsophila podophylla (Cyatheaceae)

Abstract The chloroplast genome of the tree fern Alsophila podophylla has been completely sequenced. The genome is 166,151 bp in size and features a typical quadripartite structure with the large (LSC, 86,762 bp) and small single copy (SSC, 21,641 bp) regions separated by a pair of inverted repeats (IRs, 28,874 bp each). It encodes 133 genes including 91 protein-coding genes, 33 tRNA genes, eight rRNA genes, and one pseudogene. Maximum-likelihood tree indicates that A. podophylla is sister to A. spinulosa. This work provides a solid molecular resource for surveying phylogeny and chloroplast genomics of ferns.
Gene-set Enrichment with Mathematical Biology (GEMB)

Gene-set analyses measure the association between a disease of interest and a set of genes related to a biological pathway. These analyses often incorporate gene network properties to account for the differential contributions of each gene. Extending this concept further, mathematical models of biology can be leveraged to define gene interactions based on biophysical principles by predicting the effects of genetic perturbations on a particular downstream function. We present a method that combines gene weights from model predictions and gene ranks from genome-wide association studies into a weighted gene-set test. Using publicly-available summary data from the Psychiatric Genetics Consortium (n=41,653; ~9) million SNPs), we examine an a priori hypothesis that intracellular calcium ion concentrations contribute to bipolar disorder. In this case study, we are able to strengthen inferences from a P-value of 0.081 to 1.7×10−4 by moving from a general calcium signaling pathway to a specific model-predicted function.
Phosphorus demand and uptake during growth and maturation of the brown alga Sargassum macrocarpum

We investigated the monthly variations of estimated in‐situ uptake and growth‐related demand for phosphorus in Sargassum macrocarpum during a growth period from December 2017 to April 2018, a maturation period from May to August 2018, and the second‐growth period from September 2018 to January 2019. Phosphate uptake was relatively low during maturation and high during growth, and coincided with changes in external phosphate levels. The demand for phosphorus was at its highest in March 2018, which corresponded with the highest growth rate and tissue phosphorus levels. Thereafter, the demand was relatively constant between April 2018 and January 2019. Consequently, the uptake rate exceeded demand from December 2017 to February 2018 and December 2018 to January 2019, suggesting that phosphorus accumulated in tissues. Additionally, the uptake rates between March 2018 and November 2018 were 0.1–0.8 times lower than the demand, probably resulting in the effective use of stored phosphorus to sustain growth during this phosphate‐depleted period. The variations between estimated uptake and demands for P found in S. macrocarpum indicate that P dynamics vary with life stage and are implicitly linked to the season.