Miracle-dz/UniFAR-FTUs huggingface dataset:
GAML-BERT: Improving BERT Early Exiting by Gradient Aligned Mutual Learning

In this work, we propose a novel framework, Gradient Aligned Mutual Learning BERT (GAML-BERT), for improving the early exiting of BERT. GAML-BERT’s contributions are two-fold. We conduct a set of pilot experiments, which shows that mutual knowledge distillation between a shallow exit and a deep exit leads to better performances for both. From this observation, we use mutual learning to improve BERT’s early exiting performances, that is, we ask each exit of a multi-exit BERT to distill knowledge from each other. Second, we propose GA, a novel training method that aligns the gradients from knowledge distillation to cross-entropy losses. Extensive experiments are conducted on the GLUE benchmark, which shows that our GAML-BERT can significantly outperform the state-of-the-art (SOTA) BERT early exiting methods.
Utilizing Relative Event Time to Enhance Event-Event Temporal Relation Extraction

Event time is one of the most important features for event-event temporal relation extraction. However, explicit event time information in text is sparse. For example, only about 20% of event mentions in TimeBank-Dense have event-time links. In this paper, we propose a joint model for event-event temporal relation classification and an auxiliary task, relative event time prediction, which predicts the event time as real numbers. We adopt the Stack-Propagation framework to incorporate predicted relative event time for temporal relation classification and keep the differentiability. Our experiments on MATRES dataset show that our model can significantly improve the RoBERTa-based baseline and achieve state-of-the-art performance.
Come hither or go away? Recognising pre-electoral coalition signals in the news

In this paper, we introduce the task of political coalition signal prediction from text, that is, the task of recognizing from the news coverage leading up to an election the (un)willingness of political parties to form a government coalition. We decompose our problem into two related, but distinct tasks: (i) predicting whether a reported statement from a politician or a journalist refers to a potential coalition and (ii) predicting the polarity of the signal – namely, whether the speaker is in favour of or against the coalition. For this, we explore the benefits of multi-task learning and investigate which setup and task formulation is best suited for each sub-task. We evaluate our approach, based on hand-coded newspaper articles, covering elections in three countries (Ireland, Germany, Austria) and two languages (English, German). Our results show that the multi-task learning approach can further improve results over a strong monolingual transfer learning baseline.
Modeling Document-Level Context for Event Detection via Important Context Selection

The task of Event Detection (ED) in Information Extraction aims to recognize and classify trigger words of events in text. The recent progress has featured advanced transformer-based language models (e.g., BERT) as a critical component in state-of-the-art models for ED. However, the length limit for input texts is a barrier for such ED models as they cannot encode long-range document-level context that has been shown to be beneficial for ED. To address this issue, we propose a novel method to model document-level context for ED that dynamically selects relevant sentences in the document for the event prediction of the target sentence. The target sentence will be then augmented with the selected sentences and consumed entirely by transformer-based language models for improved representation learning for ED. To this end, the REINFORCE algorithm is employed to train the relevant sentence selection for ED. Several information types are then introduced to form the reward function for the training process, including ED performance, sentence similarity, and discourse relations. Our extensive experiments on multiple benchmark datasets reveal the effectiveness of the proposed model, leading to new state-of-the-art performance.
CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization

One challenge in evaluating visual question answering (VQA) models in the cross-dataset adaptation setting is that the distribution shifts are multi-modal, making it difficult to identify if it is the shifts in visual or language features that play a key role. In this paper, we propose a semi-automatic framework for generating disentangled shifts by introducing a controllable visual question-answer generation (VQAG) module that is capable of generating highly-relevant and diverse question-answer pairs with the desired dataset style. We use it to create CrossVQA, a collection of test splits for assessing VQA generalization based on the VQA2, VizWiz, and Open Images datasets. We provide an analysis of our generated datasets and demonstrate its utility by using them to evaluate several state-of-the-art VQA systems. One important finding is that the visual shifts in cross-dataset VQA matter more than the language shifts. More broadly, we present a scalable framework for systematically evaluating the machine with little human intervention.
Analysis of the Mediating Effect of Risk Perception on the Relationship Between Time Perception and Mental Health of College Students During the COVID-19 Epidemic

Background: COVID-19 has had a wide impact on the mental health of college students. This study aims to explore the relationship between time perception, risk perception, and the mental health of college students during COVID-19 through a questionnaire survey. Subjects: One thousand two hundred and eighteen college students, 449 male and 769 female, who studied online during the COVID-19 epidemic were selected. Methods: Time Perception Scale, Risk Perception Scale, and SCL-90 were used to investigate the relationship using correlation analysis. Results: During the COVID-19 period, mental health problems of college students were widespread, and 65.93% of college students reported moderate to severe mental health problems. The correlation analysis showed that risk perception, time perception, and the mental health of college students were significantly related. Risk perception played a partial mediating role between present enjoyment and mental health, and risk perception played a partial mediating role between future time perception and mental health. Conclusion: In the case of sudden public crises, we should pay close attention to the mental health of college students, adjust their attitude toward the present and the future, and pay attention to their perception of risk so as to improve their mental health level under crisis.
The Past, Present, and Future: A Discussion of Cadaver Use in Medical and Veterinary Education

Cadaver usage in medical training, although controversial, has persisted over centuries. In veterinary education various methods have been proposed to either improve cadaver preservation, reduce cadaver use, or to replace cadavers entirely, but to date few have gained popularity. This manuscript seeks to: (i) describe the history of cadavers in medical and veterinary education; (ii) compare available cadaveric preservation methods; (iii) reflect on applications of cadaver use in the educational setting; (iv) discuss alternatives to traditional cadaver use; and (v) consider the perceptions of the stakeholders who use them.
Effects of Buffer Size and Shape on the Association of Neighborhood SES and Adult Fruit and Vegetable Consumption

Introduction: Neighborhood environment factors are relevant for dietary behaviors, but associations between home neighborhood context and disease prevention behaviors vary depending on the definition of neighborhood. The present study uses a publicly available dataset to examine whether associations between neighborhood socioeconomic status (NSES) and fruit/vegetable (FV) consumption vary when NSES is defined by different neighborhood sizes and shapes. Methods: We analyzed data from 1,736 adults with data in GeoFLASHE, a geospatial extension of the National Cancer Institute's Family Life, Activity, Sun, Health, and Eating Study (FLASHE). We examined correlations of NSES values across neighborhood buffer shapes (circular or street network) and sizes (ranging from 400 to 1,200 m) and ran weighted simple and multivariable regressions modeling frequency of FV consumption by NSES for each neighborhood definition. Regressions were also stratified by gender. Results: NSES measures were highly correlated across various neighborhood buffer definitions. In models adjusted for socio-demographics, circular buffers of all sizes and street buffers 750 m and larger were significantly associated with FV consumption frequency for women only. Conclusion: NSES may be particularly relevant for women's FV consumption, and further research can examine whether these associations are explained by access to food stores, food shopping behavior, and/or psychosocial variables. Although different NSES buffers are highly correlated, researchers should conceptually determine spatial areas a priori.
Comprehensive Pan-Cancer Analysis of the Prognostic and Immunological Roles of the METTL3/lncRNA-SNHG1/miRNA-140-3p/UBE2C Axis

Growing evidence has demonstrated that UBE2C plays a critical role in cancer progression, but there is no study focusing on the prognosis, upstream regulation mechanism, and immunological roles of UBE2C across diverse tumor types. In this study, we found that UBE2C was elevated in this human pan-cancer analysis, and high expression of UBE2C was correlated with poor prognosis. In addition, UBE2C expression was markedly associated with tumor mutation burden (TMB), microsatellite instability (MSI), immune cell infiltration, and diverse drug sensitivities. Finally, we showed that the METTL3/SNHG1/miRNA-140-3p axis could potentially regulate UBE2C expression. N(6)-Methyladenosine (m6A) modifications improved the stability of methylated SNHG1 transcripts by decreasing the rate of RNA degradation, which lead to upregulation of SNHG1 in non-small cell lung cancer (NSCLC). In vitro functional experiments showed that SNHG1, as a competing endogenous RNA, sponges miR-140-3p to increase UBE2C expression in NSCLC cell lines. Our study elucidates the clinical importance and regulatory mechanism of the METTL3/SNHG1/miRNA-140-3p/UBE2C axis in NSCLC and provides a prognostic indicator, as well as a promising therapeutic target for patients with NSCLC.
New Insights About the Behavioral Ecology of the Coelacanth Latimeria chalumnae Video Recorded in the Absence of Humans Off South Africa

South African coelacanths, Latimeria chalumnae, were intensively studied using submersibles in the Comoros Islands before recent progress in deep-diving techniques led to the discovery of coelacanths living at shallower depths off Sodwana Bay, South Africa, which were then studied by divers in close encounters or from underwater vehicles. However, all previous observations were made under intense human influence, so the “natural” behaviors of coelacanths have never been observed. Here we sought to record the natural behaviors of coelacanths by minimizing anthropogenic influences using trimix-gas diving and remote recording techniques. We thus set fixed camera and current/temperature recorders at 98 and 113 m to monitor the behaviors of fishes and oceanographic parameters over a 6-day period. Time-lapse video observations succeeded to record one coelacanth that entered the cave during the coldest-water period, two sand tiger sharks, and many other smaller fishes entering a cave. An extensive analysis of the footage led to an interesting discovery that the first dorsal fin angle of the coelacanth corelated with the presence-or-absence of a large shark that frequently passed through the cave. When no shark was present, the coelacanth’s dorsal fin was folded ∼3/4 of the time, but when the shark entered the cave, its dorsal fin was unfolded > 95% of the time, while no such reactions were observed with other observed fishes. The erected coelacanth first dorsal fin posture is an important part of the iconic symbol of these ancient fish, but it may be reflecting stressful situations such as responses to potential predators. Our observation clearly showed that the dorsal fin is in a folded position during a steady relaxed state of the fish and it can be unfolded in response to external stimuli. Use of non-biased observation systems is strongly recommended when observing the natural behavior of coelacanths. Graphical Abstract
Dimethyl Fumarate Alleviates NLRP3 Inflammasome Activation in Microglia and Sickness Behavior in LPS-Challenged Mice

NLRP3 inflammasome activation contributes to several pathogenic conditions, including lipopolysaccharide (LPS)-induced sickness behavior characterized by reduced mobility and depressive behaviors. Dimethyl fumarate (DMF) is an immunomodulatory and anti-oxidative molecule commonly used for the symptomatic treatment of multiple sclerosis and psoriasis. In this study, we investigated the potential use of DMF against microglial NLRP3 inflammasome activation both in vitro and in vivo. For in vitro studies, LPS- and ATP-stimulated N9 microglial cells were used to induce NLRP3 inflammasome activation. DMF’s effects on inflammasome markers, pyroptotic cell death, ROS formation, and Nrf2/NF-κB pathways were assessed. For in vivo studies, 12–14 weeks-old male BALB/c mice were treated with LPS, DMF + LPS and ML385 + DMF + LPS. Behavioral tests including open field, forced swim test, and tail suspension test were carried out to see changes in lipopolysaccharide-induced sickness behavior. Furthermore, NLRP3 and Caspase-1 expression in isolated microglia were determined by immunostaining. Here we demonstrated that DMF ameliorated LPS and ATP-induced NLRP3 inflammasome activation by reducing IL-1β, IL-18, caspase-1, and NLRP3 levels, reactive oxygen species formation and damage, and inhibiting pyroptotic cell death in N9 murine microglia via Nrf2/NF-κB pathways. DMF also improved LPS-induced sickness behavior in male mice and decreased caspase-1/NLRP3 levels via Nrf2 activation. Additionally, we showed that DMF pretreatment decreased miR-146a and miR-155 both in vivo and in vitro. Our results proved the effectiveness of DMF on the amelioration of microglial NLRP3 inflammasome activation. We anticipate that this study will provide the foundation consideration for further studies aiming to suppress NLRP3 inflammasome activation associated with in many diseases and a better understanding of its underlying mechanisms.
The Potential Value of Texture Analysis Based on Dynamic Contrast-Enhanced MR Images in the Grading of Breast Phyllode Tumors

Purpose To explore the value of texture analysis (TA) based on dynamic contrast-enhanced MR (DCE-MR) images in the differential diagnosis of benign phyllode tumors (BPTs) and borderline/malignant phyllode tumors (BMPTs). Methods A total of 47 patients with histologically proven phyllode tumors (PTs) from November 2012 to March 2020, including 26 benign BPTs and 21 BMPTs, were enrolled in this retrospective study. The whole-tumor texture features based on DCE-MR images were calculated, and conventional imaging findings were evaluated according to the Breast Imaging Reporting and Data System (BI-RADS). The differences in the texture features and imaging findings between BPTs and BMPTs were compared; the variates with statistical significance were entered into logistic regression analysis. The receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of models from image-based analysis, TA, and the combination of these two approaches. Results Regarding texture features, three features of the histogram, two features of the gray-level co-occurrence matrix (GLCM), and three features of the run-length matrix (RLM) showed significant differences between the two groups (all p < 0.05). Regarding imaging findings, however, only cystic wall morphology showed significant differences between the two groups (p = 0.014). The areas under the ROC curve (AUCs) of image-based analysis, TA, and the combination of these two approaches were 0.687 (95% CI, 0.518–0.825, p = 0.014), 0.886 (95% CI, 0.760–0.960, p < 0.0001), and 0.894 (95% CI, 0.754–0.970, p < 0.0001), respectively. Conclusion TA based on DCE-MR images has potential in differentiating BPTs and BMPTs.
The Brainstem-Informed Autism Framework: Early Life Neurobehavioral Markers

Autism spectrum disorders (ASD) have long-term implications on functioning at multiple levels. In this perspective, we offer a brainstem-informed autism framework (BIAF) that traces the protracted neurobehavioral manifestations of ASD to early life brainstem dysfunctions. Early life brainstem-mediated markers involving functions of autonomic/arousal regulation, sleep-wake homeostasis, and sensorimotor integration are delineated. Their possible contributions to the early identification of susceptible infants are discussed. We suggest that the BIAF expands our multidimensional understanding of ASD by focusing on the early involvement of brainstem systems. Importantly, we propose an integrated BIAF screener that brings about the prospect of a sensitive and reliable early life diagnostic scheme for weighing the risk for ASD. The BIAF screener could provide clinicians substantial gains in the future and may carve customized interventions long before the current DSM ASD phenotype is manifested using dyadic co-regulation of brainstem-informed autism markers.
Analysis of Risk Factors and Establishment of a Prediction Model for Endoscopic Primary Bile Reflux: A Single-Center Retrospective Study

Background: Endoscopic primary bile reflux is one of the main diagnostic criteria for bile reflux gastritis (BRG). Presently, the risk factors and prediction models of endoscopic primary bile reflux (EPBR) in gastropathy patients who cannot or will not undergo endoscopy due to contraindications are not clear. Thus, this study aimed to evaluate the risk factors of EPBR and to establish and verify a prediction model. Methods: A series of 844 patients (564 subjects with EPBR and 280 control subjects) were retrospectively selected for this study and divided into a training set (n = 591) and a validation set (n = 253) according to the usual ratio of 70:30% for the subsequent internal validation of the logistic regression model for EPBR. Fifteen parameters that might affect the occurrence of EPBR were collected. Subsequently, univariate and stepwise logistic regression analyses were introduced to reveal the risk factors and the multivariate prediction model. An R package was dedicated to the corresponding internal validation of the EPBR model. Results: The univariate analysis showed that gender, age, smoking, Helicobacter pylori (H. pylori) infection status, metabolic syndrome (MS), non-steroidal anti-inflammatory drugs (NSAIDs) use history, and previous medical histories of chronic liver diseases, cholelithiasis, and erosive gastritis were statistically significant between the two groups (P < 0.05). Multivariate regression described that being a male [OR (95%confidence interval (CI)) = 2.29 (1.50–3.50), P < 0.001], age≥45 years old [OR (95% CI) = 4.24 (2.59–6.96), P < 0.001], H. pylori infection status [OR (95% CI) = 2.34 (1.37–4.01), P = 0.002], MS [OR (95% CI) = 3.14 (1.77–5.54), P < 0.001], NSAIDs use history [OR (95% CI) = 1.87 (1.03–3.40), P = 0.04], cholelithiasis history [OR (95% CI) = 3.95 (2.18–7.18), P < 0.001] and erosive gastritis history [OR (95% CI) = 6.77 (3.73–12.29), P < 0.001] were the risk factors for the occurrence of EPBR. Based on the results of these risk factors, an EPBR prediction model with an adequate calibration and excellent discrimination was established [area under the curve (AUC): 0.839, 95% CI = 0.806–0.872]. Conclusions: Being a male, age ≥ 45 years old, H. pylori infection, histories of MS, NSAIDs use, cholelithiasis, and erosive gastritis appear to be the risk factors for EPBR, and our favorable prediction model might be an option for the prediction of EPBR.
Size-Resolved Community Structure of Bacteria and Fungi Transported by Dust in the Middle East

The atmosphere plays an important role in transporting microorganisms on a global scale, yet the processes affecting the composition of the airborne microbiome, the aerobiome, are not fully outlined. Here we present the community compositions of bacteria and fungi obtained by DNA amplicon-sequencing of aerosol samples collected in a size-resolved manner during nine consecutive days in central Israel. The campaign captured dust events originating from the Sahara and the Arabian deserts, as well as days without dust (“clear days”). We found that the source of the aerosol was the main variable contributing to the composition of both fungal and bacterial communities. Significant differences were also observed between communities representing particles of different sizes. We show evidence for the significant transport of bacteria as cell-aggregates and/or via bacterial attachment to particles during dust events. Our findings further point to the mixing of local and transported bacterial communities, observed mostly in particles smaller than 0.6 μm in diameter, representing bacterial single cells. Fungal communities showed the highest dependence on the source of the aerosols, along with significant daily variability, and without significant mixing between sources, possibly due to their larger aerodynamic size and shorter atmospheric residence times. These results, obtained under highly varied atmospheric conditions, provide significant assurances to previously raised hypotheses and could set the course for future studies on aerobiome composition.
Introducing a Novel, Broad Host Range Temperate Phage Family Infecting Rhizobium leguminosarum and Beyond

Temperate phages play important roles in bacterial communities but have been largely overlooked, particularly in non-pathogenic bacteria. In rhizobia the presence of temperate phages has the potential to have significant ecological impacts but few examples have been described. Here we characterize a novel group of 5 Rhizobium leguminosarum prophages, capable of sustaining infections across a broad host range within their host genus. Genome comparisons identified further putative prophages infecting multiple Rhizobium species isolated globally, revealing a wider family of 10 temperate phages including one previously described lytic phage, RHEph01, which appears to have lost the ability to form lysogens. Phylogenetic discordance between prophage and host phylogenies suggests a history of active mobilization between Rhizobium lineages. Genome comparisons revealed conservation of gene content and order, with the notable exception of an approximately 5 kb region of hypervariability, containing almost exclusively hypothetical genes. Additionally, several horizontally acquired genes are present across the group, including a putative antirepressor present only in the RHEph01 genome, which may explain its apparent inability to form lysogens. In summary, both phenotypic and genomic comparisons between members of this group of phages reveals a clade of viruses with a long history of mobilization within and between Rhizobium species.