Miracle-dz/UniFAR-FTUs huggingface dataset:
Seasonality of Oithona similis and Calanus helgolandicus reproduction and abundance: contrasting responses to environmental variation at a shelf site

The pelagic copepods Oithona similis and Calanus helgolandicus have overlapping geographic ranges, yet contrast in feeding mode, reproductive strategy, and body size. We investigate how these contrasting traits influence the seasonality of copepod abundance and reproductive output under environmental variation, using time series data collected over 25 years at the Western Channel Observatory station L4. The proportional change in Egg Production Rate (EPR, eggs female-1 d-1) over the annual cycle was ~10-fold and similar for both species, although EPR of O. similis was only ~ 11% that of C. helgolandicus. The timing of EPR maxima for O. similis coincided with increased Sea Surface Temperature (SST) in summer, likely due to a temperature-dependent brooding period. Conversely, EPR of broadcast spawning C. helgolandicus was more strongly related to Net Heat Flux (NHF) and diatom biomass, both parameters associated with the spring phytoplankton bloom. In both species, female body mass negatively correlated with SST, with a 7.5% reduction in body mass per °C in C. helgolandicus compared to just 2.3% in O. similis. Finally, seasonality of EPR and adult and copepodite abundance was strongly decoupled in both species, suggesting that optimum conditions for reproduction and abundance occur at different times of the year.
KT-XL: A Knowledge Tracing Model for Predicting Learning Performance Based on Transformer-XL

With the development of artificial intelligence (AI) technology, online teaching systems have become intellectualized. Knowledge tracing is an important task of intelligent teaching system. The goal of knowledge tracing is to trace students' knowledge status based on their past performance. It is widely used for predicting students' performance and building knowledge graph, which plays an important role in constructing adaptive (personalized) teaching systems. Previous models can not deal with subjective problems, and the performance is somewhat poor when input exercise sequences are long. In this paper, we propose a knowledge tracing model for subjective problems based on Transformer-XL, which can predict students' performance of a specific exercise. Specifically, we introduce a recurrence mechanism to the model to capture longer-term dependency and achieve better performance on both short and long sequences. Experiments on multiple real-world data sets and synthetic data sets show that our model performs better in predicting students' performance than state of the art models.
Co-Designing Personas for User Experience and Engagement in Automation

The aim of this workshop is to engage in co-design of personas to explore the interplay of autonomous technologies with user experience and engagement. Automating a process that is embedded into people's everyday lives and activities will surely impact their experience. In a time where there is strong push towards more and more automation in our daily life, the workshop will explore the value of co-design in bringing to the fore the opportunities and issues of such trend on users’ experiences and engagements in multiple contexts such as work, health, entertainment and learning. Through the co-design of personas in future scenarios of automation the workshop will concretely identify valuable automation design goals for user experience and engagement drawing on participants’ knowledge from industry projects and academic research. Tree concrete outcomes from the workshop are the following:
Validity frame concept as effort-cutting technique within the verification and validation of complex cyber-physical systems

The increasing performance demands and certification needs of complex cyber-physical systems (CPS) raise the complexity of the engineering process, not only within the development phase, but also in the Verification and Validation (V&V) phase. A proven technique to handle the complexity of CPSs is Model-Based Design (MBD). Nevertheless, the verification and validation of complex CPSs is still an exhaustive process and the usability of the models to front-load V&V activities heavily depends on the knowledge of the models and the correctness of the conducted virtual experiments. In this paper, we explore how the effort (and cost) of the V&V phase of the engineering process of complex CPSs can be reduced by enhancing the knowledge about the system components, and explicitly capturing it within their corresponding validity frame. This effort reduction originates from exploiting the captured system knowledge to generate efficient V&V processes and by automating activities at different model life stages, such as the setup and execution of boundary-value or fault-injection tests. This will be discussed in the context of a complex CPS: a safety-critical adaptive cruise control system.
Ein systematischer Backstepping-Zugang zur Regelung gekoppelter ODE-PDE-ODE-Systeme

Zusammenfassung Der systematische Zugang zum Backstepping-Entwurf von Zustandsrückführungen für gekoppelte ODE-PDE-ODE-Systeme, die sich zumeist für verteilt-parametrische Prozesse unter Berücksichtigung der Dynamik von Aktoren und Sensoren ergeben, erlaubt nicht nur die sukzessive und vereinfachte Herleitung von bereits bekannten Backstepping-Reglern sondern ermöglicht auch deren Entwurf für bisher nicht betrachtete Systemklassen. Der Zugang nutzt dabei die diesen Systemen inhärente strenge Rückkopplungsform aus. Wie beim klassischen Integrator-Backstepping wird das ODE-PDE-ODE-System schrittweise durch virtuelle Zustandsrückführungen stabilisiert und der Zustand in Fehlerkoordinaten überführt. Der vorgeschlagene, modulare Entwurf ist dabei im Wesentlichen unabhängig davon, ob der verteilt-parametrische Teil des Systems parabolisch oder hyperbolisch ist.
The Properties and Utility of Less Evaluative Personality Scales: Reduction of Social Desirability; Increase of Construct and Discriminant Validity

Evaluative neutralization implies rephrasing items such that it is less clear to the respondent what would be a desirable response in the given population. The current research compares evaluatively neutralized scales measuring the FFM model with standard counterparts. Study 1 reveals that evaluatively neutralized scales are less influenced by social desirability. Study 2 estimates higher-order factor models for neutralized vs. standard five-factor scales. In contrast to standard inventories, there was little support for higher-order factors for neutralized scales. Study 3 demonstrates the convergent and discriminant validity for the neutralized scales, e.g., by less inflated correlations to external measures. It is argued that evaluatively neutralized inventories help researchers come to grips with social desirability in personality measurement, and are particularly useful when the factor structure is central to the research question and there is a focus on discriminant validity.
Test mocks for low-code applications built with OutSystems

Unit testing is a core component of continuous integration and delivery, which in turn is key to faster and more frequent delivery of solutions to customers. Testing at the unit level allows program components to be tested in complete isolation, therefore these tests can be carried out quicker thus reducing troubleshoot time. But to test at this level, dependencies between application components (e.g. a web service connection) need to be removed. There have been advances in mocking and stubbing techniques that remove these dependencies. However, these advances have been made for high-level programming languages, while low-code development technology has yet to take full advantage of these techniques. This paper presents a mocking solution prototype for the OutSystems low-code development platform. The proposed mocking mechanism removes dependencies to components that the developer wants to abstract a test from, as for instance web services or other pieces of logic of an application.
IXA-AAA at CLEF eHealth 2020 CodiEsp. Automatic Classification of Medical Records with Multi-label Classifiers and Similarity Match Coders

These working notes present the participation of the IXA-AAA team on the CodiEsp Track, as part of the CLEF 2020. The track is about automatic coding of clinical records according to the International Classiﬁcation of Diseases 10th revision (ICD-10). There are three sub-tasks: CodiEsp-D, CodiEsp-P and CodiEsp-X. The two main tasks, CodiEsp-D and CodiEsp-P, aim to develop systems able to automatically classify clinical texts according to the ICD-10, respectively for diagnostics and procedures. CodiEsp-X, by contrast, is an exploratory sub-task within the framework of Explainable AI in which the goal is to detect the text fragment that motivates the presence of the ICD code. For the IXA-AAA team participation, we have developed several systems to cope with the three sub-tasks, including tree-based multi-label classi-ﬁers, similarity match strategies, and ensemble models. For the similarity match, we have explored several approaches and algorithms from string edit distances as Levenshtein to dense representation with Transform-ers grounded BERT models. Our best results overall are achieved by the combination of models, with a MAP of 69.8% for CodiEsp-D and 48.1% for CodiEsp-P. Regarding the exploratory task, CodiEsp-X, our best coder achieve a micro F1-Score of 30.6%.
Multilingual ICD-10 Code Assignment with Transformer Architectures using MIMIC-III Discharge Summaries

In this work, we present the participation of FHDO Biomedical Computer Science Group (BCSG) to the CLEF eHealth challenge 2020 Task 1 on automatic assignment of ICD-10 codes (CIE-10 in the Spanish translation) to clinical case studies. Training data has been augmented with documents from the Medical Information Mart for Intensive Care (MIMIC-III), a critical care database. ICD-10 CM General Equiv-alence Mappings (GEMs) were subsequently used to convert the codiﬁ-cation from ICD-9 to ICD-10. Recent state-of-the-art Transformer-based models, such as BioBERT and ClinicalBERT are compared to the Generalized Autoregressive Pretraining for Language Understanding (XLNet) model. Finally, the apriori algorithm has been applied to build association rules by ﬁnding frequent item sets. An ensemble of BioBERT and XLNet achieved a mean Average Precision (MAP) score of 0 . 259 (0 . 306 for the subset of codes only present in the training and validation sets).
Multilingual Detection of Fake News Spreaders via Sparse Matrix Factorization

Fake news is an emerging problem in online news and social media. Efﬁcient detection of fake news spreaders and spurious accounts across multiple languages is becoming an interesting research problem, and is the key focus of this paper. Our proposed solution to PAN 2020 fake news spreaders challenge models the accounts responsible for spreading the fake news by accounting for different types of textual features, decomposed via sparse matrix factorization, to obtain easy-to-learn-from, compact representations, including the information from multiple languages. The key contribution of this work is the exploration of how powerful and scalable matrix factorization-based classiﬁcation can be in a multilingual setting, where the learner is presented with the data from multiple languages simultaneously. Finally, we explore the joint latent space, where patterns from individual languages are maintained. The proposed approach scored second on the 2020 PAN shared task for identiﬁcation of fake news spreaders.
Fine‐scale demographic processes resulting from multiple overseas colonization events of the Japanese stream tree frog, Buergeria japonica

Amphibians are considered poor transoceanic dispersers because of their permeable skin. However, overseas dispersal of amphibian species has been revealed by recent phylogeographical studies and the role of overseas colonization of amphibians on their evolution and diversification has also been highlighted. However, no studies have investigated in detail the demographic processes related to these overseas colonization events. To clarify how amphibians achieve overseas colonization, we estimated the demographic history of the Japanese stream tree frog, Buergeria japonica, which is distributed on Amami Island and four northern neighbouring islands of the Tokara Archipelago, Japan.
Essex at ImageCLEFcaption 2020 Task

The University of Essex participated in the fourth edition of the ImageCLEFcaption task which aims to detect concepts on radiology images as an approach to medical image understanding. In this paper, the University of Essex team presents its participation in the ImageCLEF 2020 caption task based on a retrieval based approach for concept detection. A Densely Connected Convolutional Network is used to encode the images. This paper explores compares several modiﬁ-cation of the baseline considering several aspects such as the image modality or the selection of concepts among the top retrieved images. The University of Essex was third best team participating in the task achieving a 0.381 mean F1 score, very close to the results obtained by the top two teams. Code and pre-trained models are available at https://github.com/fjpa121197/ImageCLEFmedEssex2020.
Profiling Fake News Spreaders: Stylometry, Personality, Emotions and Embeddings

This paper describes our proposed solution for the Proﬁling Fake News Spreaders on Twitter shared task at PAN 2020 [23]. The task consists in determining whether a given author a set of Twitter posts is a fake news spreader or not, both for the English and Spanish languages. The proposed approach is based on modeling both types of users according to four main types of characteristics, i.e. stylometry, personality, emotions and feed embeddings. Our system achieved an accuracy of 60% for the English dataset, while 72% for the Spanish one.
The Safety of Medications used to Treat Peripheral Neuropathic Pain, Part 2 (Opioids, Cannabinoids and Other Drugs): review of Double-Blind, Placebo-Controlled, Randomized Clinical Trials

ABSTRACT Introduction Peripheral neuropathic pain is a disabling condition for patients and a challenge for physicians. Although many drugs have been assessed in scientific studies, few have demonstrated clear clinical efficacy against neuropathic pain. Moreover, the paucity of data regarding their safety raises the question of the benefit-risk ratio when used in patients experiencing peripheral neuropathies. Areas covered We conducted a review of double-blind, placebo-controlled, randomized clinical trials to assess the safety of medications used to treat peripheral neuropathic pain. This second review was focused on opioids, cannabinoids, and other medications. The aim was to provide an overview of the treatment-emergent adverse events (TEAEs) (≥10%) and the serious adverse effects described in clinical trials. Expert opinion Opioids and cannabinoids had significantly more TEAEs than placebos. Locally administered analgesics, such as capsaicin, lidocaine, botulinum toxin A seemed to have the most acceptable safety with only local adverse effects. The results for NMDA antagonists were inconclusive since no safety report was available. Less than half of the studies included presented a good description of TEAEs that included a statistical comparison versus a placebo group. Major methodological improvements must be made to ameliorate the assessment of medication safety in future clinical trials.
Leveraging pathogen community distributions to understand outbreak and emergence potential

Understanding pathogen outbreak and emergence events has important implications to the management of infectious disease. Apart from preempting infectious disease events, there is considerable interest in determining why certain pathogens are consistently found in some regions, and why others spontaneously emerge or reemerge over time. Here, we use a trait-free approach which leverages information on the global community of human infectious diseases to estimate the potential for pathogen outbreak, emergence, and re-emergence events over time. Our approach uses pairwise dissimilarities among pathogen distributions between countries and country-level pathogen composition to quantify pathogen outbreak, emergence, and re-emergence potential as a function of time (e.g., number of years between training and prediction), pathogen type (e.g., virus), and transmission mode (e.g., vector-borne). We find that while outbreak and re-emergence potential are well captured by our simple model, prediction of emergence events remains elusive, and sudden global emergences like an influenza pandemic seem beyond the predictive capacity of the model. While our approach allows for dynamic predictability of outbreak and re-emergence events, data deficiencies and the stochastic nature of emergence events may preclude accurate prediction. Together, our results make a compelling case for incorporating a community ecological perspective into existing disease forecasting efforts.
Dietary fat intakes in Irish children: changes between 2005 and 2019

Abstract Objective: To examine current dietary fat intakes and compliance in Irish children and to examine changes in intakes from 2005 to 2019. Design: Analyses were based on data from the Irish National Children’s Food Survey (NCFS) and the NSFS II, two cross-sectional studies that collected detailed food and beverage intake data through 7-day and 4-day weighed food diaries, respectively. Setting: NCFS and NCFS II, Republic of Ireland. Participants: A nationally representative sample of 594 (NCFS) and 600 (NCFS II) children aged 5–12 years. Current intakes from the NCFS II were compared with those previously reported in the NCFS (www.iuna.net). Results: Current intakes of total fat, SFA, MUFA, PUFA and trans fat as a percentage of total energy are 33·3, 14·0, 13·6, 5·6 and 0·5 %, respectively. Total fat, SFA and trans fat intakes since 2005 remained largely stable over time with all displaying minor decreases of <1 %. Adherence to SFA recommendations remains inadequate, with only 7 % of the population complying. Insufficient compliance with PUFA (71 %) and EPA and DHA (DHA; 16 %) recommendations was also noted. Conclusion: Children in Ireland continue to meet the total fat and trans fat target goals. Adherence to MUFA and PUFA recommendations has also significantly improved. However, deviations for some fats remain, in particular SFA. These findings are useful for the development of dietary strategies to improve compliance with current recommendations.
Uni- and bilateral spectral loudness summation and binaural loudness summation with loudness matching and categorical loudness scaling

Abstract Objective Current hearing aid prescription rules assume that spectral loudness summation decreases with hearing impairment and that binaural loudness summation is independent of hearing loss and signal bandwidth. Previous studies have shown that these assumptions might be incorrect. Spectral loudness summation was measured and compared for loudness scaling and loudness matching. Design In this study, the effect of bandwidth on binaural summation was investigated by comparing loudness perception of low-pass filtered, high-pass filtered, and broadband pink noise at 35 Categorical Units for both unilateral and bilateral presentation. Study sample Sixteen hearing-impaired listeners. Results The results show that loudness differences between the three signals are different for bilateral presentation than for unilateral presentation. In specific, binaural loudness summation is larger for the low-pass filtered pink noise than for the high-pass filtered pink noise. Finally, individual variability in loudness perception near loudness discomfort level was found to be very large. Conclusions Loudness matching is offered as a fast and reliable method to measure individual loudness perception. As discomfort with loud sounds is one of the major problems encountered by hearing aid users, measurement of individual loudness perception could improve hearing aid fitting substantially.
Comparison of Phenolics and Phenolic Acid Profiles in Conjunction with Oxygen Radical Absorbing Capacity (ORAC) in Berries of Vaccinium arctostaphylos L. and V. myrtillus L.

Abstract Caucasian blueberry (Vaccinium arctostaphylos L.) and bilberry (V. myrtillus L.), both native to Turkey, were evaluated for their total phenolics (TP) and anthocyanin (TAC) contents. Individual compositions of free phenolic acids and phenolic acids liberated from ester and glycoside forms were analyzed using UPLC-MS/MS. Berry extracts of each species were separated into three different fractions (sugar/acid, polyphenolic and anthocyanin) by solid phase extraction (SPE). The anthocyanin fractions of each species had the highest level of TP and TAC contents and ORAC values. Each species contained 10 phenolic acids representing each fraction, but in different quantities. The phenolic acids liberated from the esters and glycoside forms were caffeic acid and p-coumaric acid. The fractions containing phenolic acids liberated from ester and glycoside forms had a higher antioxidant capacity than that from free phenolic acids. The data suggest that both berries have potential as good dietary sources of phenolic antioxidants.
Cardiovascular Safety of Nilotinib in Alzheimer Disease

We read with interest the article by Turner et al on the use of nilotinib for the treatment of mild-to-moderate Alzheimer disease (AD). In this phase 2 trial, nilotinib was found to reduce central nervous system amyloid burden, cerebrospinal fluid Aβ40 and Aβ42, hippocampal volume loss, and phospho-tau-181 associated with AD at 12-month follow-up. The authors reported the cardiac safety profile of nilotinib, and demonstrated no QTc prolongation, which can be associated with risk of sudden cardiac death. We caution that the risk and incidence of cardiovascular events (CVE) while on nilotinib may not have been fully accounted for in this report. In the Evaluating Nilotinib Efficacy and Safety in Clinical Trials–Newly Diagnosed Patients (ENESTnd) trial, which investigated the efficacy and safety of nilotinib in the treatment of chronic myeloid leukemia, there was a doseand duration-dependent association between nilotinib and CVE, defined as a composite of ischemic heart disease, ischemic cerebrovascular events, and peripheral vascular disease. This trial initially described no CVE at 12 months, yet the 5-year CVE incidence was 7.5% in patients receiving nilotinib 300mg twice daily and 13.4% with 400mg twice daily. Patients’ baseline Framingham cardiovascular risk score was found to be predictive for CVE. Furthermore, nilotinib was found to significantly increase low-density lipoprotein cholesterol and glycated hemoglobin to above clinical thresholds. Patients receiving nilotinib in the study by Turner et al had a mean age of 72 years and were predominantly female. Baseline cardiovascular risk factors, scores, and prevalence of known CVE prior to trial entry were not reported. Based on mean age of participants, it may be reasonable to assume a significant proportion of trial population may have moderate-tohigh cardiovascular risk. While the daily dose and duration of nilotinib used in this trial (150mg for 6 months followed by 300mg for 6 months) were lower than in ENESTnd trial, cardiovascular risk upon prolonged use in moderate/high cardiovascular risk patients remains unknown and should be considered in future trials. Finally, the authors suggested that these doses may be noncardiotoxic based on previously reported lack of plasma Abelson inhibition using similarly low doses of nilotinib. It is worth noting that nilotinib toxicity may result from both on-target and off-target kinase inhibition, hence may not be predicted by plasma Abelson inhibition alone. In summary, low-dose nilotinib may be a promising treatment for AD; however, assessment of cardiovascular risk and detailed description of acute and long-term CVE should be considered in future phase 3 trials.