Miracle-dz/UniFAR-FTUs huggingface dataset:
Dissecting the Genetics of Autism Spectrum Disorders: A Drosophila Perspective

Autism Spectrum Disorder (ASD) is a complex group of multi-factorial developmental disorders that leads to communication and behavioral defects. Genetic alterations have been identified in around 20% of ASD patients and the use of genetic models, such as Drosophila melanogaster, has been of paramount importance in deciphering the significance of these alterations. In fact, many of the ASD associated genes, such as FMR1, Neurexin, Neuroligins and SHANK encode for proteins that have conserved functions in neurons and during synapse development, both in humans and in the fruit fly. Drosophila is a prominent model in neuroscience due to the conserved genetic networks that control neurodevelopmental processes and to the ease of manipulating its genetics. In the present review we will describe recent advances in the field of ASD with a particular focus on the characterization of genes where the use of Drosophila has been fundamental to better understand their function.
Minimal Setting Stroke Unit in a Sub-Saharan African Public Hospital

Introduction: Sub-Saharan Africa (SSA) has the highest stroke prevalence along with a case fatality that amounts to 40%. We aimed to assess the effect of a minimal setting stroke unit in SSA Public hospital on stroke mortality and main medical complications. Materials and Methods: The study was set in Conakry, Guinea, Ignace Deen public referral hospital. Clinical characteristics, hospital mortality and main medical stroke complications rates (pneumonia, urinary tract infections, sores and venous thromboembolism) of admitted stroke patients after the installation of a minimal stroke unit equipped with heart rate, blood pressure and blood oxygen saturation monitoring and portable oxygen concentrator (POST) were compared to a similar number of stroke patients admitted before the stroke unit creation (PRE). Results: PRE (n = 318) and POST (n = 361) stroke, patients were comparable in term of age (61 ± 14 vs. 60 ± 14.8 years, p = 0.24), sex (56 vs. 50% males, p = 0.09), High blood pressure rate (76.7 vs. 79%, p = 0.44), stroke subtype (ischemic in 72 vs. 78% of cases, p = 0.05) and NIHSS (11 ± 4 vs. 11 ± 4, p = 0.85). Diabetes was more frequent in the PRE group (19 vs. 9%, p < 0.001). Mortality was significantly lower in the POST group (7.2 vs. 22.3%, p < 0.0001) as well as medical complications (4.1 vs. 27.7%, p < 0.001) and lower pneumonia rate (3.3 vs. 14.5%, p < 0.001). Conclusions: Minimally equipped stroke units significantly reduce stroke mortality and main medical complications in SSA.
Hydrogen and Propane Production From Butyric Acid Photoreforming Over Pt-TiO2

Photocatalysis is a promising technology from economic, energetic, and ecological points of view because it takes advantage of solar light. Hence, it is one of the investigated green routes to produce hydrogen from renewable energy resources. Butyric acid (BA) is largely present in wastewater and as an intermediate product in anaerobic digestion and therefore it is an inexpensive resource, which can be converted to valuable chemicals. In this work, photoreforming of butyric acid (BAPR) under UV light in aqueous suspensions of platinum-modified titanium dioxide-based catalysts is reported for the first time. Titania nanotubes (TNT) synthesized and calcined at different temperatures (300, 400, 500°C) and commercial TiO2 (P25), decorated with platinum nanoparticles, have been tested and characterized through different techniques including X-ray powder diffraction, UV-vis diffuse reflectance and photoluminescence spectroscopy, transmission electron microscopy, BET and porosimetry analysis. The main identified products of the BAPR were H2, propane, CO2 and several organic acids (e.g., pentanoic and 3-methylhexanoic acid). It has been found that the morphology and crystallinity of the photocatalysts affected dramatically their optical properties and, consequently, the reaction rate and the product distribution. Specifically, the highest conversion of BA (XBA) and selectivity toward H2 (SH2) was recorded with P25-Pt (XBA = 26.9%, SH2 = 47.2% after 8 h of irradiation). TNT-400-Pt showed the highest selectivity toward propane (SC3H8 = 16.1%) with XBA = 23.4% and SH2 = 36.2%. The activity results in conjunction with the characterization of the catalysts highlighted that the main factor affecting the activity in terms of XBA and generation of H2 was the crystallinity, and in particular the presence of rutile phase in TiO2, whereas SC3H8 appears to increase when the electron-holes recombination is lower.
Space and Memory (Far) Beyond the Hippocampus: Many Subcortical Structures Also Support Cognitive Mapping and Mnemonic Processing

Memory research remains focused on just a few brain structures—in particular, the hippocampal formation (the hippocampus and entorhinal cortex). Three key discoveries promote this continued focus: the striking demonstrations of enduring anterograde amnesia after bilateral hippocampal damage; the realization that synapses in the hippocampal formation are plastic e.g., when responding to short bursts of patterned stimulation (“long-term potentiation” or LTP); and the discovery of a panoply of spatially-tuned cells, principally surveyed in the hippocampal formation (place cells coding for position; head-direction cells, providing compass-like information; and grid cells, providing a metric for 3D space). Recent anatomical, behavioral, and electrophysiological work extends this picture to a growing network of subcortical brain structures, including the anterior thalamic nuclei, rostral midline thalamic nuclei, and the claustrum. There are, for example, spatially-tuned cells in all of these regions, including cells with properties similar to place cells of the hippocampus proper. These findings add new perspectives to what had been originally been proposed—but often overlooked—half a century ago: that damage to an extended network of structures connected to the hippocampal formation results in diencephalic amnesia. We suggest these new findings extend spatial signaling in the brain far beyond the hippocampal formation, with profound implications for theories of the neural bases of spatial and mnemonic functions.
The Relationship Between Math Anxiety and Math Performance: A Meta-Analytic Investigation

Math anxiety (MA) has been suggested to decrease the math performance of students. However, it remains unclear what factors moderate this relationship. The aim of this research was to explore the link between MA and math performance. Studies that explored the math anxiety-performance link, conducted from 2000 to 2019 (84 samples, N = 8680), were identified and statistically integrated with a meta-analysis method. The results indicated a robust negative math anxiety-performance link. Furthermore, regarding the analysis of moderator variables, this negative link was stronger in the studies that involved Asian students, but this link was the weakest in the studies that involved European students. Moreover, this negative link was stronger in the studies within a senior high school group, whereas it was the weakest in the studies within an elementary group. Finally, this negative link was strongest among studies that used a custom test and studies that assessed problem-solving skills. Potential explanations and implications for research and practice are discussed.
HERCing: Structural and Functional Relevance of the Large HERC Ubiquitin Ligases

Homologous to the E6AP carboxyl terminus (HECT) and regulator of chromosome condensation 1 (RCC1)-like domain-containing proteins (HERCs) belong to the superfamily of ubiquitin ligases. HERC proteins are divided into two subfamilies, Large and Small HERCs. Despite their similarities in terms of both structure and domains, these subfamilies are evolutionarily very distant and result from a convergence phenomenon rather than from a common origin. Large HERC genes, HERC1 and HERC2, are present in most metazoan taxa. They encode very large proteins (approximately 5,000 amino acid residues in a single polypeptide chain) that contain more than one RCC1-like domain as a structural characteristic. Accumulating evidences show that these unusually large proteins play key roles in a wide range of cellular functions which include neurodevelopment, DNA damage repair, and cell proliferation. To better understand the origin, evolution, and function of the Large HERC family, this minireview provides with an integrated overview of their structure and function and details their physiological implications. This study also highlights and discusses how dysregulation of these proteins is associated with severe human diseases such as neurological disorders and cancer.
Continuous Adaptive Evolution of a Fast-Growing Corynebacterium glutamicum Strain Independent of Protocatechuate

Corynebacterium glutamicum is a commonly applied host for the industrial production of amino acids. While valued for its robustness, it is somewhat inferior to competing strains such as Escherichia coli because of the relatively low growth rate of 0.40 h−1 in synthetic, industrial media. Accordingly, adaptive laboratory evolution (ALE) experiments were performed in continuous cultivation mode to select for a growth-improved host. To ensure industrial attractiveness, this ALE study aimed at a reduction of dependency on costly growth-boosting additives such as protocatechuate (PCA) or complex media supplements. Consequently, double selection pressures were installed consisting of a steady increase in growth rate demands and a parallel reduction of complex medium fractions. Selection yielded C. glutamicum EVO5 achieving 0.54 h−1 and 1.03 gGlc gCDW−1 h−1 in minimal medium without abovementioned supplements. Sequencing revealed 10 prominent mutations, three of them in key regulator genes.
Sedentary Thresholds for Accelerometry-Based Mean Amplitude Deviation and Electromyography Amplitude in 7–11 Years Old Children

We investigated the ability of energy expenditure, movement sensing, and muscle activity to discriminate sedentary and non-sedentary activities in children. Thirty-five 7–11-year-old children participated in the study. Simultaneous assessment of oxygen uptake (V̇O2), triaxial accelerometry, and thigh muscle electromyography (EMG) were performed during eight different sedentary and non-sedentary activities including lying down, sitting-, standing-, and walking-related activities, which were performed in a random order. Mean values of V̇O2, accelerometry, and EMG from the concurrent 2 min epochs during each activity were computed. Resting energy expenditure (REE) was measured during 30 min supine rest. Directly measured metabolic equivalent of tasks (METs, V̇O2 in activities/V̇O2 in REE) were calculated for each activity. Mean amplitude deviation (MAD) was computed for accelerometry. EMG was normalized for mean muscle activity during self-paced walking. The classification accuracy of METs, MAD, and EMG to discriminate sedentary activities from physical activities was investigated by receiver operating characteristic curves and optimal cut-offs based on maximal sensitivity and specificity. Mean (SD) REE was 5.0 ± 0.8 ml/kg/min. MET, MAD, and EMG values ranged from 1.0 to 4.9, 0.0020 to 0.4146 g, and 4.3 to 133.9% during lying down and walking at 6 km/h, respectively. Optimal cut-offs to discriminate sedentary activities from non-sedentary activities were 1.3 for METs (sensitivity = 82%, specificity = 88%), 0.0033 g for MAD (sensitivity = 80%, specificity = 91%), and 11.9% for EMG (sensitivity = 79%, specificity = 92%). In conclusion, this study provides applicable thresholds to differentiate sitting and standing and sedentary and non-sedentary activities based on METs, MAD, and EMG in young children.
Short- and Long-Term Social Effects of Parental Sex Roles in Zebra Finches

Parental care is among the most widespread and variable behavioural traits between and within species, associated often both with large fitness costs and benefits. Despite its fitness consequences and evolutionary significance, we know very little about the ontogeny of this behaviour, specifically, whether and how social experiences from parents contribute to the development of parental care. Here we used a split-family experimental design to produce uniparentally raised zebra finch nestlings that were provisioned either only by their mother or their father from shortly after hatching until independence. We investigated whether zebra finch nestlings pay attention to who takes care of them (short-term social effects) and whether parental sex roles, i.e. how much each parent provides to offspring, are socially learned and how these early social experiences influence negotiation rules of parental effort as adults (long-term social effects). We found pronounced short-term effects: uniparentally raised young socialized more with their ’caring‘ than with their ’non-caring‘ parent in a two-way choice test and begged more for food from them. When paired as adults based on their caring parent, some combinations of these uniparentally raised finches did not coordinate normally during incubation as first-time parents. By nestling provisioning (and their second breeding) even these pairs assumed normal distribution of parental effort and we therefore conclude that early social experiences influence parental sex roles and coordination, but these can be overridden by own social experiences with the mate when starting to breed.
Effects of Estradiol Therapy on Resting-State Functional Connectivity of Transgender Women After Gender-Affirming Related Gonadectomy

An extreme incongruence between sex and gender identity leads individuals with gender dysphoria (GD) to seek cross-sex hormone therapy (CSHT), and gender-affirming surgery (GAS). Although few studies have investigated the effects of CSHT on the brain prior to GAS, no studies in the extant literature have evaluated its impact during hypogonadism in post-GAS individuals. Here, we aimed to evaluate the effects of estradiol on resting-state functional connectivity (rs-FC) of the sensorimotor cortex (SMC) and basal ganglia following surgical hypogonadism. Eighteen post-GAS (male-to-female) participants underwent functional magnetic resonance imaging (fMRI) and neuropsychiatric and hormonal assessment at two time points (t1, hormonal washout; t2, CSHT reintroduction). Based on the literature, the thalamus was selected as a seed, while the SMC and the dorsolateral striatum were targets for seed-based functional connectivity (sbFC). A second sbFC investigation consisted of a whole-brain voxel exploratory analysis again using the thalamus as a seed. A final complementary data-driven approach using multivoxel pattern analysis (MVPA) was conducted to identify a potential seed for further sbFC analyses. An increase in the rs-FC between the left thalamus and the left SCM/putamen followed CSHT. MVPA identified a cluster within the subcallosal cortex (SubCalC) representing the highest variation in peak activation between time points. Setting the SubCalC as a seed, whole-brain analysis showed a decoupling between the SubCalC and the medial frontal cortex during CSHT. These results indicate that CSHT with estradiol post-GAS, modulates rs-FC in regions engaged in cognitive, emotional, and sensorimotor processes.
Die Auswirkungen der Digitalisierung auf das Geschäftsmodell der Genossenschaftsbanken

Zusammenfassung Die Digitalisierung führt aktuell zu erheblichen Veränderungen in der Finanzierungsbranche. Insbesondere Genossenschaftsbanken scheinen mit ihrem traditionellen, regional-orientierten Geschäftsmodell dem Digitalisierungstrend entgegenzustehen. Die vorliegende Arbeit analysiert das Geschäftsmodell von Genossenschaftsbanken auf Basis von Experteninterviews, um die Auswirkungen der Digitalisierung genauer zu untersuchen. Es wird deutlich, dass das Geschäftsmodell der Genossenschaftsbanken in all seinen Facetten betroffen ist und im Zuge der Digitalisierung angepasst werden muss. Abstract Digitisation currently results in substantial changes to the financing sector. Cooperative banks particularly seem to be opposed to this trend with their traditional, regional oriented business model. We analyse cooperative banks‘ business model based on expert interviews to examine effects of digitisation. We find that cooperative banks‘ business model is affected in all its facets and has to be adjusted to new conditions in the course of digitisation. Résumé La numérisation conduit actuellement à de considérables changements dans la branche du financement. Avec leur modèle commercial régional traditionnel, les banques coopératives semblent particulièrement aller à l’encontre de cette tendance à la numérisation. La présente étude analyse le modèle commercial des banques coopératives sur la base d’interviews d’experts pour rechercher exactement les conséquences de la numérisation sur le modèle commercial. Il est clair que le modèle commercial des banques coopératives est concerné sur toutes ses facettes et que, dans le cadre de la numérisation, il doit être adapté aux nouvelles conditions.
Domain Name System (DNS) Tunneling Detection using Structured Occurrence Nets (SONs)

Today, serious warnings regarding the increasing number of DNS tunnelling methods are on the rise. Attackers have used such techniques to steal data from millions of accounts. The existing literature has thoroughly demonstrated the extent of the damage which DNS tunnelling can achieve on any given DNS server. However, through SONs Petri net-based formalisms which portray the behaviour of complex evolving systems, such threats can be alleviated. As a concept, SONs are originally grounded in Occurrence Nets (ONs) and already yielded results in terms of successful cybercrime analysis. For instance, adding of alternates to SONs initially used in [10] was extended to in [15] in order to model and analyse system activities such as cybercrime or accidents, which may show contradictory or uncertain evidence in terms of actual activity. The current paper proposes the use of SON features with the purpose of detecting DNS tunnelling, in the event of an actual attack.
TALP-UPC at eHealth-KD Challenge 2019: A Joint Model with Contextual Embeddings for Clinical Information Extraction

Most eHealth entity recognition and relation extraction models tackle the identification of entities and relations with independent specialized models. In this article, we show how a single combined model can exploit the correlation between these two tasks to improve the evaluation score of both, while reducing training and execution time. Our model uses both traditional part-of-speech tagging and dependency-parsing of the documents and state-of-the-art pre-trained Contextual Embeddings as input features. Furthermore, Long-Short Term Memory units are used to model close relationships between words while convolution filters are applied for farther dependencies. Our model was able to get the highest score in all three tasks of IberLEF2019’s eHealth-KD competition[7]. This advantage was specially promising in the relation extraction tasks, in which it outperformed the second best model by a margin of 9.3% in F1 Score.
Automatic De-identification of Medical Texts in Spanish: the MEDDOCAN Track, Corpus, Guidelines, Methods and Evaluation of Results

There is an increasing interest in exploiting the content of electronic health records by means of natural language processing and text-mining technologies, as they can result in resources for improving patient health/safety, aid in clinical decision making, facilitate drug repurposing or precision medicine. To share, re-distribute and make clinical narratives accessible for text mining research purposes, it is key to fulfill legal conditions and address restrictions related data protection and patient privacy. Thus, clinical records cannot be shared directly ”as is”. A necessary precondition for accessing clinical records outside of hospitals is their de-identification or exhaustive removal/replacement of all mentioned privacy related protected health information phrases. Providing a proper evaluation scenario for automatic anonymization tools is key for approval of data redistribution. The construction of manually de-identified medical records is currently the main rate and cost-limiting step for secondary use applications of clinical data. This paper summarizes the settings, data and results of the first shared track on anonymization of medical documents in Spanish, the MEDDOCAN (Medical Document Anonymization) track. This track relied on a carefully constructed synthetic corpus of clinical case documents, the MEDDOCAN corpus, following annotation guidelines for sensitive data based on the analysis of the EU General Data Protection Regulation. A total of 18 teams (from the 51 registrations) submitted 63 runs for first sub-track 1 and 61 systems for the second sub-track. The top scoring systems were based on sophisticated deep learning approaches, representing strategies that can significantly reduce time and costs associated to accessing textual data containing privacy-related sensitive information. The results of this track might help in lowering the clinical data access hurdle for Spanish language technology developers, showing also potentials for similar settings using data in other languages or from different domains.
UO_UPV2 at HAHA 2019: BiGRU Neural Network Informed with Linguistic Features for Humor Recognition

Verbal humor is an illustrative example of how humans use creative language to produce funny content. We, as human being, access to humor or comicality with the purpose of projecting more complex meanings which, usually, represent a real challenge, not only for computers, but for humans as well. For that, understanding and recognizing humorous content automatically has been and continue being an important issue in Natural Language Processing (NLP) and even more in Cognitive Computing. In order to addressing this challenge, in this paper we describe our UO UPV2 system developed for participating in the second edition of the HAHA (Humor Analysis based on Human Annotation) task proposed at IberLEF 2019 Forum. Our starting point was the UO UPV system we participated in HAHA 2018 with some modification in its architecture. This year we explored other way to inform our Attention based Recurrent Neural Network model with linguistic knowledge. Experimental results show that our system achieves positive results ranked 7th out of 18 teams.
VSP at MEDDOCAN 2019 De-Identification of Medical Documents in Spanish with Recurrent Neural Networks

This work presents the participation in the MEDDOCAN Task of the VSP team with a neural model for the Named Entity Recognition of medical documents in Spanish. The Neural Network consists of a two-layer model that creates a feature vector for each word of the sentences. The first layer uses the character information of each word and the output is aggregated to the second layer together with its word embedding in order to create the feature vector of the word. Both layers are implemented with a bidirectional Recurrent Neural Network with LSTM cells. Moreover, a Conditional Random Field layer classifies the word vectors in one of the 29 types of Protected Health Information (PHI). The system obtains a performance of 86.01%, 87.03%, and 89,12% in F1 for the classification of the entity types, the sensitive span detection, and both tasks merged, respectively. The model shows very high and promising results being a basic approach without using pretrained word embeddings or any hand-crafted feature.