Miracle-dz/UniFAR-FTUs huggingface dataset:
Can the Computed Tomographic Aspect of Porto-Systemic Circulation in Cirrhotic Patients Be Associated with the Presence of Variceal Hemorrhage?

Background and objectives: Variceal bleeding is a serious complication caused by portal hypertension, frequently encountered among cirrhotic patients. The purpose of this study was to determine whether the aspect of the collateral, porto-systemic circulation, as detected by CT are associated with the presence variceal hemorrhage (VH). Materials and Methods: 81 cirrhotic patients who underwent a contrast-enhanced CT examination were retrospectively included in the study. Patients were divided into two groups: Cirrhotic patients with variceal hemorrhage during the hospital admission concomitant, with the CT examination (n = 33) and group 2-cirrhotic patients, without any variceal hemorrhage in their medical history (n = 48). The diameter of the left gastric vein, the presence or absence and dimensions of oesophageal and gastric varices, paraumbilical veins and splenorenal shunts were the indicators assessed on CT. Results: The univariate analysis showed a significant association between the presence of upper GI bleeding and the diameters of paraoesophageal veins, paragastric veins and left gastric vein respectively, all of these CT parameters being higher in patients with variceal bleeding. In the multivariate logistic regression analysis, only the diameter of the left gastric vein was independently associated with the presence of variceal hemorrhage (OR = 1.6 (95% CI: 1.17–2.19), p = 0.003). We found an optimal cut-off value of 3 mm for the diameter of the left gastric vein useful to discriminate among patients with variceal hemorrhage from the ones without it, with a good diagnostic performance (AUC = 0.78, Se = 97%, Sp = 45.8%, PPV = 55.2%, NPV = 95.7%). Conclusions: Our observations point out that an objective CT quantification of porto-systemic circulation can be correlated with the presence of variceal hemorrhage and the diameter of the left gastric vein can be a reliable parameter associated with this condition.
Diversity of understudied archaeal and bacterial populations of Yellowstone National Park: from genes to genomes

Yellowstone National Park (YNP) thermal springs have been a crucial resource for the discovery and characterization of microbial biodiversity. The use of cultivationindependent methods has documented many new phyla of uncultured Archaea and Bacteria within thermal springs. Here, I describe the phylogenetic diversity and distribution of Archaea within the YNP thermal spring ecosystem and the phylogenetic and physiologic characterization of novel, uncultured hyperthermophilic bacterial lineages from metagenomic data. In chapter two, I evaluated the efficacy of commonly used, 'universal' archaealspecific 16S rRNA gene PCR primers in detecting archaeal phylogenetic diversity. In chapter three, using the PCR primers that would provide the best representation of archaeal communities, I used high-throughput 454 pyrosequencing to analyze the phylogenetic diversity and distribution of Archaea and Bacteria among 33 YNP springs. The results indicated that Archaea were ubiquitously distributed across YNP springs and exhibited significant taxonomic diversity across springs but were overall less
The effect of pedigree error by misidentification of individual trees on genetic evaluation of a full-sib experiment

A simulation based on real data shows how increasing rates of individual tree misidentification result in increasing under- estimation of additive genetic variance and narrow-sense herit- ability as well as increasing overestimation of the dominance variance. The data used came from a Pinus sylvestris L. prog- eny trial with 202 full-sib families from 52 unrelated parents at about one-third of the rotation. When 1% of 4970 individual trees were misidentified, the estimates of additive variance and heritability decreased by an order of magnitude that cor- responded to the standard errors. The estimate of dominance variance approached that of additive variance when the error rate increased to 2%, after which further misidentification made the estimates diverge beyond the expected parameter space of the genetic model. The error effect was less pronounc- ed when selecting the best parents using approximate best linear unbiased predictors, but their predicted performance was increasingly underestimated as the error rate increased.
Multi-Granularity Interaction Network for Extractive and Abstractive Multi-Document Summarization

In this paper, we propose a multi-granularity interaction network for extractive and abstractive multi-document summarization, which jointly learn semantic representations for words, sentences, and documents. The word representations are used to generate an abstractive summary while the sentence representations are used to produce an extractive summary. We employ attention mechanisms to interact between different granularity of semantic representations, which helps to capture multi-granularity key information and improves the performance of both abstractive and extractive summarization. Experiment results show that our proposed model substantially outperforms all strong baseline methods and achieves the best results on the Multi-News dataset.
Curriculum Learning for Natural Language Understanding

With the great success of pre-trained language models, the pretrain-finetune paradigm now becomes the undoubtedly dominant solution for natural language understanding (NLU) tasks. At the fine-tune stage, target task data is usually introduced in a completely random order and treated equally. However, examples in NLU tasks can vary greatly in difficulty, and similar to human learning procedure, language models can benefit from an easy-to-difficult curriculum. Based on this idea, we propose our Curriculum Learning approach. By reviewing the trainset in a crossed way, we are able to distinguish easy examples from difficult ones, and arrange a curriculum for language models. Without any manual model architecture design or use of external data, our Curriculum Learning approach obtains significant and universal performance improvements on a wide range of NLU tasks.
Cytotaxonomic studies in Iberian, Balearic, North African, and Macaronesian species of Carex (Cyperaceae). II

Meiotic studies on 26 taxa, including two hybrids, of the genus Carex are presented. Results obtained with the hybrid between Carex remota and Carex paniculata ssp. lusitanica were remarkable, since they showed a great number of configurations and even different chromosome numbers in metaphase I. The karyology of the Carex muricata group in the SW of Europe was studied for the first time. I also performed the first studies on the karyology of two species belonging to section Carex in the SW of Europe, namely Carex hirta, which gave the highest chromosome number reported so far for the genus Carex (2n = 114), and Carex lasiocarpa Erhr. , for which I found a putative triploid whose chromosome number (2n = 78–85) was not constant in metaphase I. Agmatoploidy seems to be the most important process involved in the cytogenetic evolution of the species studied here. The idea of the existence of "fragile points" in the chromosomes is suggested to explain the formation of bivalents upon chromosome breakage. In addi.
CraftAssist Instruction Parsing: Semantic Parsing for a Voxel-World Assistant

We propose a semantic parsing dataset focused on instruction-driven communication with an agent in the game Minecraft. The dataset consists of 7K human utterances and their corresponding parses. Given proper world state, the parses can be interpreted and executed in game. We report the performance of baseline models, and analyze their successes and failures.
Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?

While pretrained models such as BERT have shown large gains across natural language understanding tasks, their performance can be improved by further training the model on a data-rich intermediate task, before fine-tuning it on a target task. However, it is still poorly understood when and why intermediate-task training is beneficial for a given target task. To investigate this, we perform a large-scale study on the pretrained RoBERTa model with 110 intermediate-target task combinations. We further evaluate all trained models with 25 probing tasks meant to reveal the specific skills that drive transfer. We observe that intermediate tasks requiring high-level inference and reasoning abilities tend to work best. We also observe that target task performance is strongly correlated with higher-level abilities such as coreference resolution. However, we fail to observe more granular correlations between probing and target task performance, highlighting the need for further work on broad-coverage probing benchmarks. We also observe evidence that the forgetting of knowledge learned during pretraining may limit our analysis, highlighting the need for further work on transfer learning methods in these settings.
On Importance Sampling-Based Evaluation of Latent Language Models

Language models that use additional latent structures (e.g., syntax trees, coreference chains, knowledge graph links) provide several advantages over traditional language models. However, likelihood-based evaluation of these models is often intractable as it requires marginalizing over the latent space. Existing works avoid this issue by using importance sampling. Although this approach has asymptotic guarantees, analysis is rarely conducted on the effect of decisions such as sample size and choice of proposal distribution on the reported estimates. In this paper, we carry out this analysis for three models: RNNG, EntityNLM, and KGLM. In addition, we elucidate subtle differences in how importance sampling is applied in these works that can have substantial effects on the final estimates, as well as provide theoretical results which reinforce the validity of this technique.
The Vaginal-PVPA: A Vaginal Mucosa-Mimicking In Vitro Permeation Tool for Evaluation of Mucoadhesive Formulations

Drug administration to the vaginal site has gained increasing attention in past decades, highlighting the need for reliable in vitro methods to assess the performance of novel formulations. To optimize formulations destined for the vaginal site, it is important to evaluate the drug retention within the vagina as well as its permeation across the mucosa, particularly in the presence of vaginal fluids. Herewith, the vaginal-PVPA (Phospholipid Vesicle-based Permeation Assay) in vitro permeability model was validated as a tool to evaluate the permeation of the anti-inflammatory drug ibuprofen from liposomal formulations (i.e., plain and chitosan-coated liposomes). Drug permeation was assessed in the presence and absence of mucus and simulated vaginal fluid (SVF) at pH conditions mimicking both the healthy vaginal premenopausal conditions and vaginal infection/pre-puberty/post-menopause state. The permeation of ibuprofen proved to depend on the type of formulation (i.e., chitosan-coated liposomes exhibited lower drug permeation), the mucoadhesive formulation properties and pH condition. This study highlights both the importance of mucus and SVF in the vaginal model to better understand and predict the in vivo performance of formulations destined for vaginal administration, and the suitability of the vaginal-PVPA model for such investigations.
Antifungal and Cytotoxic Evaluation of Photochemically Synthesized Heparin-Coated Gold and Silver Nanoparticles

Heparin-based silver nanoparticles (AgHep-NPs) and gold nanoparticles (AuHep-NPs) were produced by a photochemical method using silver nitrate and chloroauric acid as metal precursors and UV light at 254 nm. UV–Vis spectroscopy graphs showed absorption for AgHep-NPs and AuHep-NPs at 420 nm and 530 nm, respectively. TEM revealed a pseudospherical morphology and a small size, corresponding to 10–25 nm for AgHep-NPs and 1.5–7.5 nm for AuHep-NPs. Their antifungal activity against Candida albicans, Issatchenkia orientalis (Candida krusei), and Candida parapsilosis was assessed by the microdilution method. We show that AgHep-NPs were effective in decreasing fungus density, whereas AuHep-NPs were not. Additionally, the viability of human gingival fibroblasts was preserved by both nanoparticle types at a level above 80%, indicating a slight cytotoxicity. These results are potentially useful for applications of the described NPs mainly in dentistry and, to a lesser extent, in other biomedical areas.
Ceftriaxone inhibits stress‐induced bladder hyperalgesia and alters cerebral micturition and nociceptive circuits in the rat: A multidisciplinary approach to the study of urologic chronic pelvic pain syndrome research network study

Emotional stress plays a role in the exacerbation and development of interstitial cystitis/bladder pain syndrome (IC/BPS). Given the significant overlap of brain circuits involved in stress, anxiety, and micturition, and the documented role of glutamate in their regulation, we examined the effects of an increase in glutamate transport on central amplification of stress‐induced bladder hyperalgesia, a core feature of IC/BPS.
Improving Multimodal Named Entity Recognition via Entity Span Detection with Unified Multimodal Transformer

In this paper, we study Multimodal Named Entity Recognition (MNER) for social media posts. Existing approaches for MNER mainly suffer from two drawbacks: (1) despite generating word-aware visual representations, their word representations are insensitive to the visual context; (2) most of them ignore the bias brought by the visual context. To tackle the first issue, we propose a multimodal interaction module to obtain both image-aware word representations and word-aware visual representations. To alleviate the visual bias, we further propose to leverage purely text-based entity span detection as an auxiliary module, and design a Unified Multimodal Transformer to guide the final predictions with the entity span predictions. Experiments show that our unified approach achieves the new state-of-the-art performance on two benchmark datasets.
KARYOLOGICAL STUDIES IN SPOTTED DEER (Axis axis)

The cervidae family is of great interest among the mammalian families because of their dramatic variations in chromosome number. In this paper the karyological characterization of zoo based spotted deer has been attempted. The culture medium RPMI 1640 and pokeweed mitogen was used for the lymphocyte culture. The modal chromosome number 66 (2n) was found. The chromosomal profile of spotted deer showed the presence of 2 submetacentirc autosomes (Ist pair) and 62 acrocentric autosomes. The XX and XY chromosomal configuration was found in females and males respectively. The position of X chromosome was found between 2 nd and 3 rd pair of chromosomes. The ‘Y’ chromosome was the smallest and sub metacentric.
Fine-grained Interest Matching for Neural News Recommendation

Personalized news recommendation is a critical technology to improve users’ online news reading experience. The core of news recommendation is accurate matching between user’s interests and candidate news. The same user usually has diverse interests that are reflected in different news she has browsed. Meanwhile, important semantic features of news are implied in text segments of different granularities. Existing studies generally represent each user as a single vector and then match the candidate news vector, which may lose fine-grained information for recommendation. In this paper, we propose FIM, a Fine-grained Interest Matching method for neural news recommendation. Instead of aggregating user’s all historical browsed news into a unified vector, we hierarchically construct multi-level representations for each news via stacked dilated convolutions. Then we perform fine-grained matching between segment pairs of each browsed news and the candidate news at each semantic level. High-order salient signals are then identified by resembling the hierarchy of image recognition for final click prediction. Extensive experiments on a real-world dataset from MSN news validate the effectiveness of our model on news recommendation.
Adversarial and Domain-Aware BERT for Cross-Domain Sentiment Analysis

Cross-domain sentiment classification aims to address the lack of massive amounts of labeled data. It demands to predict sentiment polarity on a target domain utilizing a classifier learned from a source domain. In this paper, we investigate how to efficiently apply the pre-training language model BERT on the unsupervised domain adaptation. Due to the pre-training task and corpus, BERT is task-agnostic, which lacks domain awareness and can not distinguish the characteristic of source and target domain when transferring knowledge. To tackle these problems, we design a post-training procedure, which contains the target domain masked language model task and a novel domain-distinguish pre-training task. The post-training procedure will encourage BERT to be domain-aware and distill the domain-specific features in a self-supervised way. Based on this, we could then conduct the adversarial training to derive the enhanced domain-invariant features. Extensive experiments on Amazon dataset show that our model outperforms state-of-the-art methods by a large margin. The ablation study demonstrates that the remarkable improvement is not only from BERT but also from our method.
Appraisal of EUS-guided needle-based confocal laser endomicroscopy in the diagnosis of pancreatic lesions: A single Chinese center experience

Background and Objectives: In the recent years, EUS is one of the routine procedures in the diagnosis of pancreatic diseases. EUS-guided needle-based confocal laser endomicroscopy (nCLE) is a novel minimally invasive imaging technique in diagnosis of pancreatic diseases. The pilot researches provided us some preliminary findings and conclusions with small samples, low rate of pathological correspondence. The aim of this current study was to evaluate the diagnostic efficacy of EUS-guided nCLE in solid pancreatic lesions (SPLs) and pancreatic cystic lesions (PCLs) based on large samples. The date was obtained on nCLE imaging findings and high rate of correlation with pathology. Material and Methods: Patients enrolled in the study were underwent EUS-nCLE to achieve the nCLE images and diagnosis. Comparing with the final diagnosis, including surgical histopathological results or cyto-/histopathology through FNA, the efficacy and accuracy of nCLE in diagnosis in solid and cystic pancreatic lesions were evaluated. In other cases, clinical diagnoses were achieved based on the combination with clinical history, image findings and fluid analysis and cytology, by 3 independent committee members strongly agreed with a concordant diagnosis. Results: Totally 172 patients were enrolled into the study. The overall rate of final diagnosis was about 65% while 50% in cystic lesion. The mean sensitivity, specificity, negative predictive value, positive predictive value and accuracy of the nCLE in diagnosis of PDAC is 90.3%, 89.5%, 93.3%, 85.0% and 90.0% respectively. The efficacy and accuracy of pancreatic cystic lesions were very satisfying and some additional nCLE signs were found, including “black aggregates of cells, forming as gland-like structure, surrounding by fibro and vessels” in neuroendocrine tumors (NETs); “black columnar protrusions near vascular area” in the pseudopapillary solid tumor (SPT); macrophage in tuberculosis (TB) and small aggregate of black regular cells maybe corresponds to ovarian-like stroma in mucinous cystadenoma (MCN). In the study, 20 (11.6%) patients suffered complications, including symptomatic (5.2%) and asymptomatic (6.4%). Conclusions: nCLE observation could improve characterization of indeterminate cysts, or confirm the EUS impression, when cytological confirmation is missing. The technique may deliver information to better guide our clinical decisions.
How to perform EUS-based cholecystolithotomy

EUS-guided gallbladder drainage (EUS-GBD) is gradually emerging as an option for patients with cholecystitis. A stent-bridged endoscopic intervention in the gallbladder (GB) has been proposed. The formation of a fistulous tract after EUS-GBD facilitates the entry of the endoscope inside the GB to perform endoscopic lithotomy and polypectomy, which is an efficient and safe procedure. However, the technical aspects of this procedure in order to optimize the success rate have only been scarcely discussed. This paper discusses the EUS-GBD prepared for per-oral cholecystolithotomy, the stent indwelling time, the procedure, the devices of per-oral cholecystolithotomy and the follow-up. The recently published literature on this topic is also updated in this review.
Environmental Quality Perceptions and Health: A Cross-Sectional Study of Citizens of Kaunas, Lithuania

The perception of urban environmental quality is an important contributor when identifying local problems in sustainable development and environmental planning policy. This study examined the associations between environmental and social residential characteristics, physical activity, obesity, and hypertension in Kaunas city, Lithuania. This cross-sectional study analyzed 580 citizens’ demographic-, socioeconomic-, health-, and lifestyle-related factors, environmental health concerns, and environmental quality perceptions. Using Geographic Information Systems and the multivariate logistic regression, we found that the less physically active group more often presented lower than mean ratings of the quality of pathways and cycling routes (32.9% and 45.6%, p = 0.042) and only irregularly visited the natural environment. Obese participants presented poorer ratings of air pollution, the quality of pathways and cycling routes, their possibility to reach green spaces by walking, and the available relaxing areas. The environmental issues associated with hypertension were poor possibilities to reach green spaces by walking (OR 1.94, 95% CI 1.14–3.32) and the availability of relaxation areas (OR 2.30, 95% 1.34–3.95). The quality of the neighborhood and individual-level characteristics were the factors that influenced a higher prevalence of health problems at the district level. Our findings suggest that a public health policy to improve the physical and social environment of the neighborhood would have a potential to increase citizens’ physical activity and health.