Miracle-dz/UniFAR-FTUs huggingface dataset:
Building a Robust Text Classifier on a Test-Time Budget

We propose a generic and interpretable learning framework for building robust text classification model that achieves accuracy comparable to full models under test-time budget constraints. Our approach learns a selector to identify words that are relevant to the prediction tasks and passes them to the classifier for processing. The selector is trained jointly with the classifier and directly learns to incorporate with the classifier. We further propose a data aggregation scheme to improve the robustness of the classifier. Our learning framework is general and can be incorporated with any type of text classification model. On real-world data, we show that the proposed approach improves the performance of a given classifier and speeds up the model with a mere loss in accuracy performance.
Generating Text through Adversarial Training Using Skip-Thought Vectors

GANs have been shown to perform exceedingly well on tasks pertaining to image generation and style transfer. In the field of language modelling, word embeddings such as GLoVe and word2vec are state-of-the-art methods for applying neural network models on textual data. Attempts have been made to utilize GANs with word embeddings for text generation. This study presents an approach to text generation using Skip-Thought sentence embeddings with GANs based on gradient penalty functions and f-measures. The proposed architecture aims to reproduce writing style in the generated text by modelling the way of expression at a sentence level across all the works of an author. Extensive experiments were run in different embedding settings on a variety of tasks including conditional text generation and language generation. The model outperforms baseline text generation networks across several automated evaluation metrics like BLEU-n, METEOR and ROUGE. Further, wide applicability and effectiveness in real life tasks are demonstrated through human judgement scores.
Distinct 3D Structural Patterns of Lamin A/C Expression in Hodgkin and Reed-Sternberg Cells

Classical Hodgkin’s lymphoma (cHL) is a B-Cell lymphoma comprised of mononuclear Hodgkin cells (H) and bi- to multi-nucleated Reed-Sternberg (RS) cells. Previous studies revealed that H and RS cells express lamin A/C, a component of the lamina of the nuclear matrix. Since no information was available about the three-dimensional (3D) expression patterns of lamin A/C in H and RS cells, we analyzed the 3D spatial organization of lamin in such cells, using 3D fluorescent microscopy. H and RS cells from cHL derived cell lines stained positive for lamin A/C, in contrast to peripheral blood lymphocytes (PBLs), in which the lamin A/C protein was not detected or weak, although its presence could be transiently increased with lymphocyte activation by lipopolysaccharide (LPS). Most importantly, in H and RS cells, the regular homogeneous and spherically shaped lamin A/C pattern, identified in activated lymphocytes, was absent. Instead, in H and RS cells, lamin staining showed internal lamin A/C structures, subdividing the nuclei into two or more smaller compartments. Analysis of pre-treatment cHL patients’ samples replicated the lamin patterns identified in cHL cell lines. We conclude that the investigation of lamin A/C protein could be a useful tool for understanding nuclear remodeling in cHL.
Prediction Is a Balancing Act: Importance of Sampling Methods to Balance Sensitivity and Specificity of Predictive Models Based on Imbalanced Chemical Data Sets

Increase in the number of new chemicals synthesized in past decades has resulted in constant growth in the development and application of computational models for prediction of activity as well as safety profiles of the chemicals. Most of the time, such computational models and its application must deal with imbalanced chemical data. It is indeed a challenge to construct a classifier using imbalanced data set. In this study, we analyzed and validated the importance of different sampling methods over non-sampling method, to achieve a well-balanced sensitivity and specificity of a machine learning model trained on imbalanced chemical data. Additionally, this study has achieved an accuracy of 93.00%, an AUC of 0.94, F1 measure of 0.90, sensitivity of 96.00% and specificity of 91.00% using SMOTE sampling and Random Forest classifier for the prediction of Drug Induced Liver Injury (DILI). Our results suggest that, irrespective of data set used, sampling methods can have major influence on reducing the gap between sensitivity and specificity of a model. This study demonstrates the efficacy of different sampling methods for class imbalanced problem using binary chemical data sets.
Gender-Based Risk and Protective Factors for Psychological Distress in the Midterm Recovery Period Following the Great East Japan Earthquake

ABSTRACT Objectives Women and men might experience psychological distress differently during a disaster. This study investigated gender differences in the factors associated with psychological distress among working-age people 1 to 2 years after the Great East Japan Earthquake. Methods A cross-sectional household survey of victims who remained living in their homes was conducted between May and December 2012 in Ishinomaki City, Japan. Psychological distress was defined as a Kessler Psychological Distress Scale ≥5, and gender differences were examined using a logistic regression analysis. Results Data were obtained from 2593 individuals, and 1537 participants were included in the analyses. Psychological distress was observed in 28.0% of the participants. Living in a household without a salaried income and a low frequency of leaving the house were associated with psychological distress among women. Young age, lack of occupation and no informational support were associated with psychological distress among men. Income change due to the disaster and health complaints were associated with psychological distress in both genders. Conclusions For women, stable household income and frequently leaving the house can be protective factors. For men, intervention focusing on young people, occupational support, and informational support may be useful. Income change after the disaster and health complaints may be risk factors in both genders. (Disaster Med Public Health Preparedness. 2019;13:487-496)
Impact of pH and feeding system on black soldier fly (Hermetia illucens, L; Diptera: Stratiomyidae) larval development

Black soldier fly (BSF) is a generalist species able to reduce large quantities of organic substrates and is thus considered as an interesting solution for waste management. Moreover, as BSF larvae accumulate high quantities of nutrients during their growth, they are valued because of their potential to produce products such as protein meal or fat for livestock feeds. Abiotic factors can influence larva growth, and a more detailed knowledge and control of these parameters can lead to the development of mass BSF breeding for the production of innovative products for animal feeds. As little information is available on the effects of the pH of substrates and feeding systems, the aim of this study was to evaluate the impact of these two factors on the activities of BSF larvae, prepupae, and adults. An experiment was performed with two fixed factors: i) pH (4.0; 6.1; 7.5; 9.5) and ii) feeding system (batch feeding system (TFS) or daily feeding system (DFS)). The pH treatments impacted larval weight on the first, third, and fifth day, but not at the end of the trial. Larval activity increased pH values from the fourth day onward, with final values of around 8.9–9.4 in all the treatments. The weight of the prepupae ranged from between 0.094 and 0.100 g. The final weight of the larvae and pupae, sex ratio, ingested food, larval mortality, percentage of emergence, and time to reach the pupa stadium were all affected by the feeding system. DFS showed the heaviest final larval weight (0.149 g), but required a longer time (11.3 d) than TFS to reach the prepupa stadium. The findings of this research could be useful for the mass production of BSF. Evaluation of an appropriate feeding system and initial pH value of the substrate are important parameters to reduce the time and to increase the weight in the production of larvae.
Demographic and genetic approaches to study dispersal in wild animal populations: A methodological review

Dispersal is a central process in ecology and evolution. At the individual level, the three stages of the dispersal process (i.e., emigration, transience and immigration) are affected by complex interactions between phenotypes and environmental factors. Condition‐ and context‐dependent dispersal have far‐reaching consequences, both for the demography and the genetic structuring of natural populations and for adaptive processes. From an applied point of view, dispersal also deeply affects the spatial dynamics of populations and their ability to respond to land‐use changes, habitat degradation and climate change. For these reasons, dispersal has received considerable attention from ecologists and evolutionary biologists. Demographic and genetic methods allow quantifying non‐effective (i.e., followed or not by a successful reproduction) and effective (i.e., with a successful reproduction) dispersal and to investigate how individual and environmental factors affect the different stages of the dispersal process. Over the past decade, demographic and genetic methods designed to quantify dispersal have rapidly evolved but interactions between researchers from the two fields are limited. We here review recent developments in both demographic and genetic methods to study dispersal in wild animal populations. We present their strengths and limits, as well as their applicability depending on study objectives and population characteristics. We propose a unified framework allowing researchers to combine methods and select the more suitable tools to address a broad range of important topics about the ecology and evolution of dispersal and its consequences on animal population dynamics and genetics.
Drug-Eluting Balloons versus Second-Generation Drug-Eluting Stents for Treating In-Stent Restenosis in Coronary Heart Disease after PCI: A Meta-Analysis

Background In-stent restenosis (ISR) remains a common problem following percutaneous coronary intervention (PCI). However, the best treatment strategy remains uncertain. There is some controversy over the efficacy of drug-eluting balloons (DEBs) and second-generation drug-eluting stents (DESs) for treating ISR. Methods A meta-analysis was used to compare the efficacy of the DEB and second-generation DES in the treatment of ISR. The primary endpoint is the incidence of target lesion revascularization (TLR). The secondary endpoint is the occurrence of target vessel revascularization (TVR), myocardial infarction (MI), all-cause death (ACM), cardiac death (CD), major adverse cardiac events (MACEs), minimum luminal diameter (MLD), late luminal loss (LLL), binary restenosis (BR), and percent diameter stenosis (DS%). Results A total of 12 studies (4 randomized controlled trials and 8 observational studies) including 2020 patients with a follow-up of 6–25 months were included in the present study. There was a significant difference in the MLD between the two groups during follow-up (P=0.007, RR = 0.23, and 95% CI: 0.06–0.4 mm). There was no significant difference in LLL, BR, or DS% and the overall incidence of MACEs between the two groups. Subgroup analysis showed no significant difference in the incidence of primary and secondary endpoints when considering RCTs or observational studies only. Conclusions The efficacy of the DEB and second-generation DES in the treatment of ISR is comparable. However, our results need further verification through multicenter randomized controlled trials.
Metformin as a Therapeutic Target in Endometrial Cancers

Endometrial cancer is the most common gynecologic malignancy in developed countries. Its increasing incidence is thought to be related in part to the rise of metabolic syndrome, which has been shown to be a risk factor for the development of hyperestrogenic and hyperinsulinemic states. This has consequently lead to an increase in other hormone-responsive cancers as well e.g., breast and ovarian cancer. The correlation between obesity, hyperglycemia, and endometrial cancer has highlighted the important role of metabolism in cancer establishment and persistence. Tumor-mediated reprogramming of the microenvironment and macroenvironment can range from induction of cytokines and growth factors to stimulation of surrounding stromal cells to produce energy-rich catabolites, fueling the growth, and survival of cancer cells. Such mechanisms raise the prospect of the metabolic microenvironment itself as a viable target for treatment of malignancies. Metformin is a biguanide drug that is a first-line treatment for type 2 diabetes that has beneficial effects on various markers of the metabolic syndrome. Many studies suggest that metformin shows potential as an adjuvant treatment for uterine and other cancers. Here, we review the evidence for metformin as a treatment for cancers of the endometrium. We discuss the available clinical data and the molecular mechanisms by which it may exert its effects, with a focus on how it may alter the tumor microenvironment. The pleiotropic effects of metformin on cellular energy production and usage as well as intercellular and hormone-based interactions make it a promising candidate for reprogramming of the cancer ecosystem. This, along with other treatments aimed at targeting tumor metabolic pathways, may lead to novel treatment strategies for endometrial cancer.
Dysregulation of MicroRNAs and Target Genes Networks in Peripheral Blood of Patients With Sporadic Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neurodegenerative disease. While genetics and other factors contribute to ALS pathogenesis, critical knowledge is still missing and validated biomarkers for monitoring the disease activity have not yet been identified. To address those aspects we carried out this study with the primary aim of identifying possible miRNAs/mRNAs dysregulation associated with the sporadic form of the disease (sALS). Additionally, we explored miRNAs as modulating factors of the observed clinical features. Study included 56 sALS and 20 healthy controls (HCs). We analyzed the peripheral blood samples of sALS patients and HCs with a high-throughput next-generation sequencing followed by an integrated bioinformatics/biostatistics analysis. Results showed that 38 miRNAs (let-7a-5p, let-7d-5p, let-7f-5p, let-7g-5p, let-7i-5p, miR-103a-3p, miR-106b-3p, miR-128-3p, miR-130a-3p, miR-130b-3p, miR-144-5p, miR-148a-3p, miR-148b-3p, miR-15a-5p, miR-15b-5p, miR-151a-5p, miR-151b, miR-16-5p, miR-182-5p, miR-183-5p, miR-186-5p, miR-22-3p, miR-221-3p, miR-223-3p, miR-23a-3p, miR-26a-5p, miR-26b-5p, miR-27b-3p, miR-28-3p, miR-30b-5p, miR-30c-5p, miR-342-3p, miR-425-5p, miR-451a, miR-532-5p, miR-550a-3p, miR-584-5p, miR-93-5p) were significantly downregulated in sALS. We also found that different miRNAs profiles characterized the bulbar/spinal onset and the progression rate. This observation supports the hypothesis that miRNAs may impact the phenotypic expression of the disease. Genes known to be associated with ALS (e.g., PARK7, C9orf72, ALS2, MATR3, SPG11, ATXN2) were confirmed to be dysregulated in our study. We also identified other potential candidate genes like LGALS3 (implicated in neuroinflammation) and PRKCD (activated in mitochondrial-induced apoptosis). Some of the downregulated genes are involved in molecular bindings to ions (i.e., metals, zinc, magnesium) and in ions-related functions. The genes that we found upregulated were involved in the immune response, oxidation–reduction, and apoptosis. These findings may have important implication for the monitoring, e.g., of sALS progression and therefore represent a significant advance in the elucidation of the disease’s underlying molecular mechanisms. The extensive multidisciplinary approach we applied in this study was critically important for its success, especially in complex disorders such as sALS, wherein access to genetic background is a major limitation.
Moderator Role of Looming Cognitive Style (LCS) in the Relationship Between Attentional Control and Anxiety: Difference Between Shifting and Focusing Dimensions

Abstract Attentional control (AC) that is composed of shifting and focusing dimensions had been suggested as a transdiagnostic risk factor, associated with development and maintenance of various psychological disorders. In comparison, Looming Cognitive Style (LCS) had been documented as a trait-based, disorders-specific characteristic that is linked to high levels of subjectively felt anxiety. The present study investigated whether individual differences in LCS moderated the association of shifting and focusing with anxiety. Participants were 402 individuals between ages 18 and 68 recruited through advertisements posted on various forums, e-mail groups, and social media websites. They filled out questionnaires assessing AC, LCS, anxiety, and depression online. Results of the moderation analyses indicated that at high levels of LCS, low attentional shifting ability was associated with more intense anxiety. A similar relationship with LCS was not observed for focusing. In conclusion, for individuals who have high LCS and low shifting ability, content of and distress coming from looming images is experienced in a more intense manner due to difficulty in shifting to another (perhaps less anxiety provoking) content more flexibly. The findings are providing support for the interactive–synergistic perspective, indicating that deficits in shifting capacity may potentiate negative impact of looming cognitions.
A Study of Reinforcement Learning for Neural Machine Translation

Recent studies have shown that reinforcement learning (RL) is an effective approach for improving the performance of neural machine translation (NMT) system. However, due to its instability, successfully RL training is challenging, especially in real-world systems where deep models and large datasets are leveraged. In this paper, taking several large-scale translation tasks as testbeds, we conduct a systematic study on how to train better NMT models using reinforcement learning. We provide a comprehensive comparison of several important factors (e.g., baseline reward, reward shaping) in RL training. Furthermore, to fill in the gap that it remains unclear whether RL is still beneficial when monolingual data is used, we propose a new method to leverage RL to further boost the performance of NMT systems trained with source/target monolingual data. By integrating all our findings, we obtain competitive results on WMT14 English-German, WMT17 English-Chinese, and WMT17 Chinese-English translation tasks, especially setting a state-of-the-art performance on WMT17 Chinese-English translation task.
Overall survival of stage IV non-small cell lung cancer patients treated with Viscum album L. in addition to chemotherapy, a real-world observational multicenter analysis

Background Stage IV non-small cell lung cancer (NSCLC) is associated with a five-year survival rate of around 1%. Treatment with Viscum album L. (VA) extracts has been shown to reduce chemotherapy (CTx)-related adverse events, decrease CTx dose reductions and improve quality of life in a number of cancers. Recent data suggest a beneficial effect of add-on treatment with Viscum album L. (VA, European mistletoe) on survival in cancer patients. The objective of this study was to evaluate the effect of VA in addition to chemotherapy on survival in stage IV NSCLC patients. Methods The observational study was conducted using data from the Network Oncology clinical registry which is an accredited conjoint clinical registry of German oncological hospitals, practitioners and out-patient centers.Patients were included if they had stage IV NSCLC at diagnosis, lived at least for four weeks post-diagnosis and received chemotherapeutic treatment. Patients with EGFR mutations as well as patients receiving tyrosine kinase inhibitors or immune checkpoint inhibitors were not included. Overall survival and impact on hazard in patients with chemotherapy (CTx) to patients receiving CTx plus VA were compared. To identify factors associated with survival and to address potential sources of bias a multivariate analyses using Cox proportional hazard model was performed. Results The median age of the population was 64.1 years with 55.7% male patients. The highest proportion of patients had adenocarcinoma (72.2%) and most of the patients were current or past smokers (70.9%). Of 158 stage IV NSCLC patients, 108 received CTx only and 50 additional VA. Median survival was 17.0 months in the CTx plus VA group (95%CI: 11.0–40.0) and was 8.0 months (95%CI: 7.0–11.0) in the CTx only group (χ2 = 7.2, p = .007). Overall survival was significantly prolonged in the VA group (HR 0.44, 95%CI: 0.26–0.74, p = .002). One-year and three-year overall survival rates were greater with CTx plus VA compared to CTX alone (1y: 60.2% vs. 35.5%; 3y: 25.7% vs. 14.2%). Conclusion Our findings suggest that concomitant VA is positively associated with survival in stage IV NSCLC patients treated with standard CTx. These findings complement pre-existing knowldedge of add-on VA’s clinical impact, however, results should be interpreted with caution in light of the study’s observational character.
Outcome after 52 Salto Ankle Prostheses Implanted by a Single Surgeon

While ankle arthrodesis was traditionally the gold standard method of treatment for disabling end-stage ankle arthritis, total ankle replacement (TAR) has been an acceptable alternative. The satisfaction rate of patients with TAR however differs. The purpose of our study is to investigate whether implant survival and results with special emphasis on the satisfaction rate of patients treated with a TAR implanted by a single surgeon were comparable to the literature. This was a retrospective cohort study in a teaching hospital. Data was collected from 52 patients who received a total ankle replacement (TAR) between 05/2002 and 06/2014. The mean follow-up time was 4.2 years (95% CI 3.3 – 5.0). Results showed a high satisfaction rate of 94% and 94% survival of the TAR after 5 years. We conclude that TAR with the Salto prosthesis is, in our hands, a reliable solution for end-stage ankle arthritis, with results comparable to the literature.
Analysis of Polymorphisms in Genes Differentially Expressed in the Enamel of Mice with Different Genetic Susceptibilities to Dental Fluorosis

Genes expressed during amelogenesis are candidates to increase the risk of dental fluorosis (DF). Thus, this study aimed to evaluate the association between polymorphisms in enamel development genes and susceptibility to DF in mice. Mice of both sexes, representing strains 129P3/J (n = 20; resistant to DF) and A/J (n = 20; susceptible to DF), were divided into 2 groups. Each strain received a diet with a low concentration of fluoride (F) and drinking water containing 0 or 50 mg/L of F for 6 weeks. Clinical evaluation and analysis of Vickers enamel microhardness of the incisors were performed. Livers were collected for genomic DNA extraction. Seventeen genetic polymorphisms in Amelx, Ambn, Ambn, Col14a1, Col1a1, Col5a2, Enam, Fam20a, Fam83h, Foxo1, Klk4, Mmp20, Serpinf1, Serpinh1, Smad3, Tuft1, and Wdr72 were genotyped by real-time PCR using Taqman chemistry. Overrepresentation of alleles and genotypes in DF was evaluated using the χ2 test with an alpha of 5%. The clinical aspects of the enamel and the surface enamel microhardness confirmed the DF condition. In the polymorphisms rs29569969, rs13482592, and rs13480057 in Ambn, Col14a1, and Mmp20, respectively, genotype and allele distributions were statistically significantly different between A/J and 129P3/J strains (p < 0.05). In conclusion, polymorphisms in Ambn, Col14a1, and Mmp20 are associated with the susceptibility to DF.