Miracle-dz/UniFAR-FTUs huggingface dataset:
Lessons Learnt from Linear Text Segmentation: a Fair Comparison of Architectural and Sentence Encoding Strategies for Successful Segmentation

Recent works on linear text segmentation have shown new state-of-the-art results nearly every year. Most times, however, these recent advances include a variety of different elements which makes it difficult to evaluate which individual components of the proposed methods bring about improvements for the task and, more generally, what actually works for linear text segmentation. Moreover, evaluating text segmentation is notoriously difficult and the use of a metric such as Pk, which is widely used in existing literature, presents specific problems that complicates a fair comparison between segmentation models. In this work, then, we draw from a number of existing works to assess which is the state-of-the-art in linear text segmentation, investigating what architectures and features work best for the task. For doing so, we present three models representative of a variety of approaches, we compare them to existing methods and we inspect elements composing them, so as to give a more complete picture of which technique is more successful and why that might be the case. At the same time, we highlight a specific feature of Pk which can bias the results and we report our results using different settings, so as to give future literature a more comprehensive set of baseline results for future developments. We then hope that this work can serve as a solid foundation to foster research in the area, overcoming task-specific difficulties such as evaluation setting and providing new state-of-the-art results.
Overview of the Shared Task on Hope Speech Detection for Equality, Diversity, and Inclusion

Hope serves as a powerful driving force that encourages individuals to persevere in the face of the unpredictable nature of human existence. It instills motivation within us to remain steadfast in our pursuit of important goals, regardless of the uncertainties that lie ahead. In today’s digital age, platforms such as Facebook, Twitter, Instagram, and YouTube have emerged as prominent social media outlets where people freely express their views and opinions. These platforms have also become crucial for marginalized individuals seeking online assistance and support[1][2][3]. The outbreak of the pandemic has exacerbated people’s fears around the world, as they grapple with the possibility of losing loved ones and the lack of access to essential services such as schools, hospitals, and mental health facilities.
On Operations in Automatic Text Simplification

This paper explores the literature of automatic text simplification (ATS) centered on the notion of operations. Operations are the processed of applying certain modifications to a given text in order to transform it. In ATS, the intent of the transformation is to simplify the text. This paper overviews and structures the domain by showing how operations are defined and how they are exploited. We extensively discuss the most recent works on this notion and perform preliminary experiments to automatize operations recognition with large language models (LLMs). Through our overview of the literature and the preliminary experiment with LLMs, this paper provides insights on the topic that can help lead to new directions in ATS research.
Evaluation of Distributional Semantic Models of Ancient Greek: Preliminary Results and a Road Map for Future Work

We evaluate four count-based and predictive distributional semantic models of Ancient Greek against AGREE, a composite benchmark of human judgements, to assess their ability to retrieve semantic relatedness. On the basis of the observations deriving from the analysis of the results, we design a procedure for a larger-scale intrinsic evaluation of count-based and predictive language models, including syntactic embeddings. We also propose possible ways of exploiting the different layers of the whole AGREE benchmark (including both human- and machine-generated data) and different evaluation metrics.
Generation and characterization of Sema6aΔcyt conditional knockout mice

The axon guidance molecule Semaphorin-6A (SEMA6A) plays a key role during nervous system development. SEMA6A, classically known as a ligand for Plexin-A2 and -A4, is a transmembrane protein that can also elicit signaling via its intracellular domain in vitro. However, the physiological relevance of this ‘reverse’ signaling route is largely unknown. We generated a new transgenic mouse model, Sema6aΔcytfl/fl, in which the cytosolic part of SEMA6A can be conditionally removed using Cre-recombination. Upon Sema6aΔcyt mutation, SEMA6A can only act as a ligand and reverse signaling is perturbed. Germline deletion of SEMA6A’s intracellular part results in developmental defects in axon pathfinding and neuron migration that partially phenocopy defects observed in full Sema6a knockout mice. These defects include disorganization of the anterior commissure, piriform cortex, lateral olfactory tract, thalamocortical and corticospinal white matter tracts, and defected neuron migration in the neocortex and cerebellum. Intriguingly, the hippocampal malformation described in Sema6a full knockout mice was not reproduced, suggesting a specific role for SEMA6A forward signaling in hippocampal development. Our results indicate that the intracellular domain of SEMA6A is essential for proper axon targeting and neuron migration, and provide the first proof of a SEMA6A reverse signaling pathway in vivo.
Coordinated differentiation of human intestinal organoids with functional enteric neurons and vasculature

Human intestinal organoids (HIOs) derived from human pluripotent stem cells co-differentiate both epithelial and mesenchymal lineages in vitro but lack important cell types such as neurons, endothelial cells, and smooth muscle. Here, we report an in vitro method to derive HIOs with epithelium, mesenchyme, enteric neuroglial populations, endothelial cells, and organized smooth muscle in a single differentiation, without the need for co-culture. When transplanted into a murine host, these populations expand and organize to support organoid maturation and function. Functional experiments demonstrate enteric nervous system function, with HIOs undergoing peristaltic-like contractions, suggesting the development of a functional neuromuscular unit. HIOs also form functional vasculature, demonstrated in vitro using microfluidic devices to introduce vascular-like flow, and in vivo following transplantation, where HIO endothelial cells anastomose with host vasculature. Collectively, we report an in vitro model of the human gut that simultaneously co-differentiates epithelial, stromal, endothelial, neural, and organized muscle populations.
The changing morphology of the ventricular walls of mouse and human with increasing gestation

That the highly trabeculated ventricular walls of the developing embryos transforms to the arrangement during the fetal stages, when the mural architecture is dominated by the thickness of the compact myocardium, has been explained by coalescence of trabeculations, often erroneously described as “compaction”. Recent data, however, supports differential rates of growth of the trabecular and compact layers as the major driver of change. Here, these processes were assessed quantitatively and morphologically using a larger dataset than has previously been available of mouse hearts from embryonic day 10.5 to postnatal day 3, supported by images from human hearts. The volume of the trabecular layer increased throughout development, in contrast to what would be expected had there been “compaction”. During the embryonic-fetal transition, fast growth of the compact layer diminished the proportion of trabeculations. Similarly, great expansion of the central cavity reduced the proportion that intertrabecular recesses make of the total cavity. Using the median value of left ventricular trabeculation, we provided illustrations for each gestational day so as to provide pictorial evidence of the changes. The illustrations confirmed a pronounced growth of the compact wall, and prominence of the central cavity. This corresponds, in morphological terms, to a reduction in the extent of the trabecular layer. Similar observations were made in the human hearts. We conclude that it is a period of comparatively slow growth of the trabecular layer, rather than so-called compaction, that is the major determinant of the changing morphology of the ventricular walls of both mouse and human.
Host influence on the eukaryotic virome of sympatric mosquitoes and abundance of diverse viruses with a broad host range

Mosquitoes harbor a large diversity of eukaryotic viruses. Those viromes probably influence mosquito physiology and the transmission of human pathogens. Nevertheless, their ecology remains largely unstudied. Here, we address two key questions in virome ecology. First, we assessed the influence of mosquito species on virome taxonomic diversity and relative abundance. Contrary to most previous studies, the potential effect of the habitat was explicitly included. Thousands of individuals of Culex poicilipes and Culex tritaeniorhynchus, two vectors of viral diseases, were concomitantly sampled in three habitats over two years. A total of 95 viral taxa from 25 families were identified with meta-transcriptomics, with 75% of taxa shared by both mosquitoes. Viromes significantly differed by mosquito species but not by habitat. Differences were largely due to changes in relative abundance of shared taxa. Then, we studied the diversity of viruses with a broad host range. We searched for viral taxa shared by the two Culex species and Aedes vexans, another disease vector, present in one of the habitats. Twenty-six out of the 163 viral taxa were found in the three mosquitoes. These taxa encompassed 14 families. A database analysis supported broad host ranges for many of those viruses, as well as a widespread geographical distribution. Thus, the viromes of mosquitoes from the same genera mainly differed in the relative abundance of shared taxa, whereas differences in viral diversity dominated between mosquito genera. Whether this new model of virome diversity and structure applies to other mosquito communities remains to be determined.
Total-evidence phylogenetic analysis resolves the evolutionary timescale of mantis shrimps (Stomatopoda) and provides insights into their molecular and morphological evolutionary rates

The crustacean order Stomatopoda comprises approximately 500 species of mantis shrimps. These marine predators, common in tropical and subtropical waters, possess sophisticated visual systems and specialized hunting appendages. In this study, we infer the evolutionary relationships within Stomatopoda using a combined data set of 77 morphological characters, complete mitochondrial genomes, and three nuclear markers. Our data set includes representatives from all seven stomatopod superfamilies, including the first sequence data from Erythrosquilloidea. Using a Bayesian relaxed molecular clock with fossil-based calibration priors, we estimate that crown-group unipeltatan stomatopods appeared ∼140 (95% credible interval 201–102) million years ago in the late Mesozoic. Additionally, our results support the hypothesis that specialized smashing and spearing appendages appeared early in the evolutionary history of Unipeltata. We found no evidence of a correlation between rates of morphological and molecular evolution across the phylogeny, but identified very high levels of among-lineage rate variation in the morphological characters. Our total-evidence analysis recovered evolutionary signals from both molecular and morphological data sets, demonstrating the merit in combining these sources of information for phylogenetic inference and evolutionary analysis.
Structural insights into the RNA maturation of the mitoribosome by GTPBP10

Mitochondria contain their own genetic information and a dedicated translation system to express it. The mitochondrial ribosome is assembled from mitochondrial-encoded RNA and nuclear-encoded ribosomal proteins. Assembly is coordinated in the mitochondrial matrix by biogenesis factors that transiently associate with the maturing particle. Here, we present a structural snapshot of a previously unknown large mitoribosomal subunit assembly intermediate containing 7 biogenesis factors including the GTPases GTPBP7 and GTPBP10. Our structure illustrates how GTPBP10 aids the folding of the ribosomal RNA during the biogenesis process, how this process is related to bacterial ribosome biogenesis, and why mitochondria require 2 biogenesis factors in contrast to only 1 in bacteria.
Mitotic Block and Epigenetic Repression Underlie Neurodevelopmental Defects and Neurobehavioral Deficits in Congenital Heart Disease

Poor neurodevelopment is often observed with congenital heart disease (CHD), especially with mutations in chromatin modifiers. Here analysis of mice with hypoplastic left heart syndrome (HLHS) arising from mutations in Sin3A associated chromatin modifier Sap130, and adhesion protein Pcdha9, revealed neurodevelopmental and neurobehavioral deficits reminiscent of those in HLHS patients. Microcephaly was associated with impaired cortical neurogenesis, mitotic block, and increased apoptosis. Transcriptional profiling indicated dysregulated neurogenesis by REST, altered CREB signaling regulating memory and synaptic plasticity, and impaired neurovascular coupling modulating cerebral blood flow. Many neurodevelopmental/neurobehavioral disease pathways were recovered, including autism and cognitive impairment. These same pathways emerged from genome-wide DNA methylation and Sap130 chromatin immunoprecipitation sequencing analyses, suggesting epigenetic perturbation. Mice with Pcdha9 mutation or forebrain-specific Sap130 deletion without CHD showed learning/memory deficits and autism-like behavior. These novel findings provide mechanistic insights indicating the adverse neurodevelopment in HLHS may involve cell autonomous/nonautonomous defects and epigenetic dysregulation and suggest new avenues for therapy.
Semana da Escola de Engenharia October 24 - 27, 2011 MYCOTOXIN DETECTION OF HARVESTED MAIZE KERNELS

Mycotoxins are known to cause serious health problems in animals. Some mycotoxins such as fumonisins, aflatoxins and ochratoxins, in particular, have also been associated with human health problems. Aflatoxins, produced by Aspergillus section Flavi species, and fumonisins, produced by Fusarium verticillioides, are prominent among the mycotoxins associated to maize economic losses (Zea mays L.) (Kumar et al. 2008). There are many factors, especially environmental conditions and agricultural practices, involved in the production of mycotoxins (Chulze, 2010). The aim of this work was to detect whether mycotoxins were present in post-harvested maize. Ninety five maize samples collected from different agroclimatic regions of Portugal (Beira Litoral, Ribatejo, Alto Alentejo) were analyzed by HPLC for mycotoxin contamination. Mycotoxins were detected in 67% the samples. Sixty four percent of the samples were positive for FB1 and FB2. Only 8% of the samples were positive for aflatoxins (LOD of 0.1µg/Kg). Neither OTA (LOD of 0.04µg/Kg) nor CPA (LOD of 10µg/Kg) was detected in any sample.
Photoplethysmogram Based Cognitive Load Recognition Using Lstm

Physiological data are nowadays frequently used to recognize the affective state of subjects while performing different tasks. Measuring cognitive load using simple device plays an important role in everyday life such as intelligent human-computer interaction, physical health monitoring, and mental health monitoring. However, due to the nature of the experiments involving subjects, the obtained data base is often low, making it difficult to train deep learning methods from scratch. In this paper, We conducted a method to recognize the cognitive load based on the Photoplethysmogram(PPG) data and the application of Long Short Term Memory (LSTM). We tested this method on the PPG data from an experiment where 19 subjects were involved in arithmetic calculation tasks of two different cognitive load levels. The method successfully achieve btter accuracy of recognition compared with the traditional machine learning classifiers with features artificially extracted from the image and pre-trained CNN method, 92.3% binary classification accuracy was reached and about 3.8% binary classification accuracy was improved.
A Multi-Scale Attention-Based Network for Grape Disease Identification

Disease diagnosis is an important aspect to ensure the yield and quality of grapes. To timely and effectively prevent the loss from plant diseases, automatic identification of plant diseases is necessary. In this work, the ISE-Multi-ResNet network is proposed to identify grape diseases. Specifically, the residual block is used as the main feature extraction network, and the improved squeeze-and-excitation block is used as the attention mechanism to strengthen important features and weaken unnecessary features. Furthermore, multi-scale parallel convolution is introduced to the proposed network to extract features at different scales to improve identification accuracy. A public dataset is used to verify the proposed network, and experimental results show that the test accuracy achieves 98.39%. Compared with other approaches, the proposed network demonstrates superior performance for grape disease identification.
A Method of Visual Presentation of Data Schemas

We describe and demonstrate a method of automated creation of refined visualizations of Linked data endpoint schemas, based on their pre-computed structure information. The visualization uses UML class diagram style structure with classes, associations, and attributes, as well as subclass structure. Due to the pre-computed nature of the data schemas, visualization can avoid repeating the subclass properties and links at a superclass level and present parts of larger data schemas in a compact and conceivable way.
Research on Mental Disease Diagnosis Method Based on PMFS

Currently, the diagnosis of mental illnesses such as Alzheimer's disease, Schizophrenia, and Depression heavily relies on questionnaire surveys and the experience of doctors, resulting in a high rate of missed and misdiagnosed cases. In order to address this issue, a psychiatric disease diagnosis model based on parallel multi-layer feature selection (PMFS) is proposed. Firstly, based on the feature's inherent information, redundancy between features, and correlation between features and the learner, three-layer feature selection is performed in parallel using the Variance Thresholding, Max-Relevance and Min-Redundancy(mRMR), and Support Vector Machine-Recursive Feature Elimination(SVM-RFE), respectively, resulting in three feature subsets. Then, a voting score is assigned to these three subsets, and features with two or more votes are retained as the final feature set. Finally, the features in the set are taken as the input of the classifier, which is trained and tested to achieve the purpose of early diagnosis of mental illnesses. Experimental results demonstrate that compared with the SVM and RF classification models without using the PMFS algorithm, the PMFS-SVM and PMFS-RF models show better performance in terms of accuracy, sensitivity, recall, F1, and AUC.
NDUFAF6 Promotes Breast Cancer Development as a Novel Marker for Diagnosis

Numerous new cases of breast cancer are diagnosed among women each year, rendering breast cancer the most common and rapidly expanding form of cancer in females globally. NDUFAF6 encodes a protein that localizes to mitochondria and contains a predicted phytoene synthase domain. Mutations in NDUFAF6 are associated with complex I enzymatic deficiency. This study explored the role of NDUFAF6 in breast cancer development and prognosis using informatic analysis. Through the online website TIMER, we evaluated the transcription profile of NDUFAF6 across pan-cancer and breast cancer respectively. We investigated that NDUFAF6 mRNA was overexpressed in breast cancer and other 18 cancers. NDUFAF6 expression also related to the subtype, pathological stage and prognosis of breast cancer. The GSEA showed NDUFAF6 correlated with cell cycle and tumor cell adhesion molecules. NDUFAF6 expression may associate with the proliferation and migration ability of breast cancer cells. Subsequently, the association between the NDUFAF6 expression level and immune cell infiltration was analyzed using the XIANTAO and TIMER tools. The results revealed a negative correlation between NDUFAF6 and most immune infiltrating cells. This study indicated that NDUFAF6 may role in the progression of breast cancer and potentially been one of the markers for diagnosis.
Transfer Learning based Efficient Schizophrenia Classification on Electroencephalogram (EEG) Signals: A Cross-Dataset Study

Although EEG classification for schizophrenia has shown promising results on individual datasets, the cross-dataset generalizability of such classification remains unknown. This study aimed to assess this generalizability through transfer learning at segment and individual levels, by employing the spectral convolutional neural network (CNN-S) on two distinct EEG datasets for schizophrenia classification. While direct cross-decoding only obtained baseline transfer accuracies of 54.72% ± 2.77% and 47.78% ± 3.62% at the segment and individual levels, the fine-tuned CNN-S achieved average cross-dataset transfer accuracies of 76.46% ± 1.17% and 56.71% ± 5.76, respectively. To improve the limited generalizability at the individual level, we applied transfer component analysis (TCA), a domain adaptation approach, to the two datasets, leading to an average cross-dataset transfer accuracy of 62.12% ± 4.86%. By combining fine-tuning and TCA, the study obtained an average cross-dataset transfer accuracy of 69.15% ± 4.09% at the individual level. Overall, transfer learning proves useful for cross-dataset EEG schizophrenia classification.
Aspergillus bronchitis without signiﬁcant immunocompromise

Aspergillus bronchitis is poorly understood and described. We extracted clinical data from more than 400 referred patients with persistent chest symptoms who did not fulﬁll criteria for allergic, chronic, or invasive aspergillosis. Symptomatic patients with a positive culture or real-time PCR for Aspergillus spp. were reviewed. Seventeen patients fulﬁlled the selected criteria. Fourteen were women, with a mean age of 57 years (range 39–76). Sixteen of the patients had productive cough, eight had voluminous tenacious sputum, and seven had recurrent chest infections. Eight patients had Medical Research Council dyspnea scores of 4–5; 12 had bronchiectasis; and 13 patients grew A. fumigatus , 3 A. niger, and 1 A. terreus . Twelve of the 17 patients (71%) had elevated Aspergillus IgG (47–137 mg/L, mean 89.2) and 5 (29%) had elevated Aspergillus precipitins. Six of 12 (50%) had a major response to antifungal therapyandﬁveof12(42%)patientsrelapsed,requiringlong-termtherapy. Aspergillus bronchitisisadiscreteclinical entity in patients with structural lung disease but who are not signiﬁcantly immunocompromised. It is distinct from asymptomatic fungal colonization and other forms of aspergillosis, and may respond to antifungal therapy.
A Benchmark for Rough Sketch Cleanup

The recent flurry of sketch vectorization, simplification, and cleanup algorithms could be used to bridge this gap. However, they differ wildly in the assumptions they make on the input and output sketches. We present the first benchmark to evaluate and focus sketch cleanup research. Our dataset consists of 281 sketches obtained in the wild and a curated subset of 101 sketches. For this curated subset along with 40 sketches from previous work, we commissioned manual vectorizations and multiple ground truth cleaned versions by professional artists. The sketches span artistic and technical categories and were created by a variety of artists with different styles. Most sketches