Miracle-dz/UniFAR-FTUs huggingface dataset:
ntuer at SemEval-2019 Task 3: Emotion Classification with Word and Sentence Representations in RCNN

In this paper we present our model on the task of emotion detection in textual conversations in SemEval-2019. Our model extends the Recurrent Convolutional Neural Network (RCNN) by using external fine-tuned word representations and DeepMoji sentence representations. We also explored several other competitive pre-trained word and sentence representations including ELMo, BERT and InferSent but found inferior performance. In addition, we conducted extensive sensitivity analysis, which empirically shows that our model is relatively robust to hyper-parameters. Our model requires no handcrafted features or emotion lexicons but achieved good performance with a micro-F1 score of 0.7463.
Changes in vulnerability among older patients with cardiovascular disease in the first 90 days after hospital discharge: A secondary analysis of a cohort study

Objectives (1) To compare changes in vulnerability after hospital discharge among older patients with cardiovascular disease who were discharged home with self-care versus a home healthcare (HHC) referral and (2) to examine factors associated with changes in vulnerability in this period. Design Secondary analysis of longitudinal data from a cohort study. Participants and setting 834 older (≥65 years) patients hospitalised for acute coronary syndromes and/or acute decompensated heart failure who were discharged home with self-care (n=713) or an HHC referral (n=121). Outcome Vulnerability was measured using Vulnerable Elders Survey 13 (VES-13) at baseline (prior to hospital admission) and 30 days and/or 90 days after hospital discharge. Effects of HHC referral on postdischarge change in vulnerability were examined using three linear regression approaches, with potential confounding on HHC referral adjusted by propensity score matching. Results Overall, 44.4% of the participants were vulnerable at prehospitalisation baseline and 34.4% were vulnerable at 90 days after hospital discharge. Compared with self-care patients, HHC-referred patients were more vulnerable at baseline (66.9% vs 40.3%), had more increase (worsening) in VES-13 score change (B=−1.34(–2.07, –0.61), p<0.001) in the initial 30 days and more decrease (improvement) in VES-13 score change (B=0.83(0.20, 1.45), p=0.01) from 30 to 90 days after hospital discharge. Baseline vulnerability and the HHC referral attributed to 14%–16% of the variance in vulnerability change during the 90 postdischarge days, and 6% was attributed by patient age, race (African-American), depressive symptoms, and outpatient visits and hospitalisations in the past year. Conclusion After adjusting for preceding vulnerability and covariates, older hospitalised patients with cardiovascular disease referred to HHC had delayed recovery in vulnerability in first initial 30 days after hospital discharge and greater improvement in vulnerability from 30 to 90 days after hospital discharge. HHC seemed to facilitate improvement in vulnerability among older patients with cardiovascular disease from 30 to 90 days after hospital discharge.
The enigmatic thymic myoid cells – their 130 years of history, embryonic origin, function and clinical significance

Thymic myoid cells form a part of the cellular microenvironment of the thymic medulla in fish, amphibians, reptiles, birds, and mammals, including humans. In lower vertebrates they resemble skeletal muscle fibers at the level of light and electron microscopy, in humans they are less noticable even though they contain proteins typically found in the muscle tissue including desmin, actin, acetylcholine receptor, myosin, troponin or myogenic transcription factor. Despite the discovery of thymic myoid cells by German histologist Sigmund Mayer employed at the Charles-Ferdinand University (now Charles University) in Prague, Czech Republic, occurred exactly 130 years ago, as of today, these cells have been mentioned neither in most of the histology textbooks, nor in the histological nomenclature Terminologia Histologica. Thus, we find it appropriate to call these cells “enigmatic. ” In this narrative review, we focus on the historical background of the discovery of thymic myoid cells, and current opinions on their embryonic origin and functional significance during the maturation of T-lymphocytes within the thymus. Finally, we present the overview of the clinical importance of this cell population, including the notion of rare mediastinal rhabdomyomas and rhabdomyosarcomas probably originating from these cells. We also ponder over the possible connection between thymic myoid cells and the pathogenesis of autoimmune disease – myasthenia gravis.
Assessment of prostate cancer prognostic Gleason grade group using zonal‐specific features extracted from biparametric MRI using a KNN classifier

Abstract Purpose To automatically assess the aggressiveness of prostate cancer (PCa) lesions using zonal‐specific image features extracted from diffusion weighted imaging (DWI) and T2W MRI. Methods Region of interest was extracted from DWI (peripheral zone) and T2W MRI (transitional zone and anterior fibromuscular stroma) around the center of 112 PCa lesions from 99 patients. Image histogram and texture features, 38 in total, were used together with a k‐nearest neighbor classifier to classify lesions into their respective prognostic Grade Group (GG) (proposed by the International Society of Urological Pathology 2014 consensus conference). A semi‐exhaustive feature search was performed (1–6 features in each feature set) and validated using threefold stratified cross validation in a one‐versus‐rest classification setup. Results Classifying PCa lesions into GGs resulted in AUC of 0.87, 0.88, 0.96, 0.98, and 0.91 for GG1, GG2, GG1 + 2, GG3, and GG4 + 5 for the peripheral zone, respectively. The results for transitional zone and anterior fibromuscular stroma were AUC of 0.85, 0.89, 0.83, 0.94, and 0.86 for GG1, GG2, GG1 + 2, GG3, and GG4 + 5, respectively. CONCLUSION This study showed promising results with reasonable AUC values for classification of all GG indicating that zonal‐specific imaging features from DWI and T2W MRI can be used to differentiate between PCa lesions of various aggressiveness.
On the qubit routing problem

We introduce a new architecture-agnostic methodology for mapping abstract quantum circuits to realistic quantum computing devices with restricted qubit connectivity, as implemented by Cambridge Quantum Computing's t|ket> compiler. We present empirical results showing the effectiveness of this method in terms of reducing two-qubit gate depth and two-qubit gate count, compared to other implementations.
Diagnostic Parameters of Adenoviremia in Pediatric Stem Cell Transplant Recipients

Despite recent progress in the diagnostic risk assessment of human adenovirus (HAdV) infections in immunocompromised patients, clinical complications mediated by these viruses continue contributing to significant morbidity and mortality, particularly in the pediatric hematopoietic allogeneic stem cell transplant (HSCT) setting. Current data highlight the importance of monitoring stool samples to assess the risk of invasive HAdV infections in children undergoing HSCT. The advent of novel, more effective antiviral treatment options might permit successful virus control even at the stage of systemic infection, thus increasing the interest in optimized HAdV monitoring in peripheral blood (PB). We have screened over 300 pediatric HCST recipients by serial monitoring of stool and PB specimens, and identified 31 cases of invasive HAdV infection by quantitative pan-adenovirus RQ-PCR analysis of consecutive PB specimens. The diagnostic parameters assessed included HAdV peak levels (PL) and the time-averaged area under the curve (AAUC) of virus copy numbers. The predictive value for patient outcome reflected by non-relapse and HAdV-related mortality was determined. The patients were assigned to quartiles based on their PL and AAUC, and the readouts were highly correlated (p < 0.0001). Non-relapse mortality in patients by AAUC quartile (lowest to highest) was 26, 50, 75, and 86%, respectively, and AAUC was strongly correlated with non-relapse mortality (p < 0.0001), while the association between PL and non-relapse mortality was less pronounced (p = 0.013). HAdV-related mortality was absent or very low in patients within the two lower quartiles of both PL and AAUC, and increased to ≥70% in the upper two quartiles. Despite the significant correlation of PL and AAUC with patient outcome, it is necessary to consider that the risk of non-relapse mortality even within the lowest quartile was still relatively high, and it might be difficult therefore to translate the results into differential treatment approaches. By contrast, the correlation with HAdV-related mortality might permit the identification of a low-risk patient subset. Nevertheless, the well-established correlation of HAdV shedding into the stool and intestinal expansion of the virus with the risk of invasive infection will expectedly remain an essential diagnostic parameter in the pediatric HSCT setting.
Misuse of Discharge Antimicrobial Prescription in the Emergency Department: An Observational Study at a Tertiary Care Center

Abstract We conducted a restrospective cohort study of patients discharged from the emergency department at a tertiary care center with an antimicrobial prescription. More than half of the prescribed antimicrobials were misused and frequently inappropriate for various infectious diseases. In this study, we analyzed the physician-related and environment-related factors predicting misuse.
Deep Discriminative Representation Learning with Attention Map for Scene Classification

In recent years, convolutional neural networks (CNNs) have shown great success in the scene classification of computer vision images. Although these CNNs can achieve excellent classification accuracy, the discriminative ability of feature representations extracted from CNNs is still limited in distinguishing more complex remote sensing images. Therefore, we propose a unified feature fusion framework based on attention mechanism in this paper, which is called Deep Discriminative Representation Learning with Attention Map (DDRL-AM). Firstly, by applying Gradient-weighted Class Activation Mapping (Grad-CAM) algorithm, attention maps associated with the predicted results are generated in order to make CNNs focus on the most salient parts of the image. Secondly, a spatial feature transformer (SFT) is designed to extract discriminative features from attention maps. Then an innovative two-channel CNN architecture is proposed by the fusion of features extracted from attention maps and the RGB (red green blue) stream. A new objective function that considers both center and cross-entropy loss are optimized to decrease the influence of inter-class dispersion and within-class variance. In order to show its effectiveness in classifying remote sensing images, the proposed DDRL-AM method is evaluated on four public benchmark datasets. The experimental results demonstrate the competitive scene classification performance of the DDRL-AM approach. Moreover, the visualization of features extracted by the proposed DDRL-AM method can prove that the discriminative ability of features has been increased.
Use of wearable sensors for pregnancy health and environmental monitoring: Descriptive findings from the perspective of patients and providers

Background Wearable sensors and other smart technology may be especially beneficial in providing remote monitoring of sub-clinical changes in pregnancy health status. Yet, limited research has examined perceptions among pregnant patients and providers in incorporating smart technology into their daily routine and clinical practice. Objective The purpose of this study was to examine the perceptions of pregnant women and their providers at a rural health clinic on the use of wearable technology to monitor health and environmental exposures during pregnancy. Methods An anonymous 21-item e-survey was administered to family medicine or obstetrics and gynecology (n=28) providers at a rural health clinic; while a 21-item paper survey was administered to pregnant women (n=103) attending the clinic for prenatal care. Results Smartphone and digital technology use was high among patients and providers. Patients would consider wearing a mobile sensor during pregnancy, reported no privacy concerns, and felt comfortable sharing information from these devices with their physician. About seven out of 10 women expressed willingness to change their behavior during pregnancy in response to receiving personalized recommendations from a smartphone. While most providers did not currently use smart technologies in their medical practice, about half felt it will be used more often in the future to diagnose and remotely monitor patients. Patients ranked fetal heart rate and blood pressure as their top preference for health monitoring compared to physicians who ranked blood pressure and blood glucose. Patients and providers demonstrated similar preferences for environmental monitoring, but patients as a whole expressed more interests in tracking environmental measures compared to their providers. Conclusions Patients and providers responded positively to the use of wearable sensor technology in prenatal care. More research is needed to understand what factors might motivate provider use and implementation of wearable technology to improve the delivery of prenatal care.
Platform-Based Function Repertoire, Reputation, and Sales Performance of E-Marketplace Sellers

In today’s emerging and competitive e-marketplaces, sellers must take competitive action to improve their sales performance. E-marketplace platform operators offer sellers a portfolio of platform-based functions that are intended to enhance competitiveness. However, little is known about how these platform-based functions can be used at the repertoire level to improve the sales performance of e-marketplace sellers. Extending the competitive repertoire theory to the e-marketplace context and integrating it with the e-commerce literature on reputation, we posit that a seller could improve sales performance by using these functions as a repertoire, featuring such structural characteristics as large volume, high complexity, and heterogeneity. We also posit that the performance impact of this repertoire approach to function use varies depending on seller reputation, manifested as customer rating. We empirically examined the hypotheses with a unique longitudinal dataset consisting of 43,992 seller-week observations from Taobao, one of the largest e-marketplaces in the world. Our analyses yield a set of interesting findings that unveil more nuanced theoretical relationships between different structural characteristics of the platform-based function repertoire and sales performance under different levels of seller reputation. We elaborate on how these findings contribute to the e-marketplace literature in the information systems field and the competitive action research in the strategy field. We also discuss implications for practice and make suggestions for future work.
Exercise-induced laryngeal obstruction in athletes treated with inspiratory muscle training

Background Exercise-induced laryngeal obstruction (EILO) is common in athletes and presents with dyspnoea, chest tightness, inspiratory stridor and sometimes panic reactions. The evidence for conservative treatment is weak, but case reports suggest effects from inspiratory muscle training (IMT). We aimed to explore effects from IMT used in athletes with EILO. Method Twenty-eight athletes, mean age 16.4 years, diagnosed with EILO at our clinic, participated in a 6-week treatment programme, using a resistive flow-dependent IMT device (Respifit S). Four athletes competed at international level, 13 at national and 11 at regional levels. Video-recorded continuous transnasal flexible laryngoscopy was performed from rest to peak exercise (continuous laryngoscopy exercise (CLE) test) and scored before and 2–4 weeks after the training period. Ergospirometric variables were obtained from this CLE set-up. Lung function was measured according to guidelines. Symptom scores and demographic variables were obtained from a questionnaire. Results After the treatment period, symptoms had decreased in 22/28 (79%) participants. Mean overall CLE score had improved after treatment (p<0.001), with the scores becoming normal in five athletes but worse in two. Most of the improvement was explained by changes at the glottic laryngeal level (p=0.009). Ergospirometric variables revealed significantly higher peak minute ventilation explained by higher tidal volumes and were otherwise unchanged. Conclusion This explorative study underlines the heterogeneous treatment response of EILO and suggests that IMT may become an efficient conservative treatment tool in subgroups, possibly contributing to better control of the vocal folds. The signals from this study should be tested in future controlled interventional studies.
Who to Trust? Applying Trust to Social Commerce

ABSTRACT Organizations have recognized the revenue potential for social commerce (purchasing products via social networks), but such transactions only comprise a small percentage of revenue. Companies have yet to determine the factors that contribute to social commerce failure. In social networking, trust is established when two parties have a history of trustworthy interactions. Acknowledging that social commerce represents a fundamentally different purchasing environment than typical business transactions, we examine the role of trust in determining consumers’ decisions to engage in social commerce for their purchases. We apply trust transfer theory to the social commerce context to assess whether trust in known entities can be transferred to business transactions facilitated through a social network with unknown parties. Using a field survey, we found that trust in the Internet and trust in firms significantly influence consumers’ trust and ultimately their intention to engage in social commerce. Implications for research and practice are discussed.
ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing

Despite recent advances in natural language processing, many statistical models for processing text perform extremely poorly under domain shift. Processing biomedical and clinical text is a critically important application area of natural language processing, for which there are few robust, practical, publicly available models. This paper describes scispaCy, a new Python library and models for practical biomedical/scientific text processing, which heavily leverages the spaCy library. We detail the performance of two packages of models released in scispaCy and demonstrate their robustness on several tasks and datasets. Models and code are available at https://allenai.github. io/scispacy/.
Uplink NOMA transmissions in a cooperative relay network based on statistical channel state information

Non-orthogonal multiple access (NOMA) has recently attracted a lot of attention as a promising multiple access technology to be used in the fifth generation (5G) cellular networks. In this study, the authors investigate uplink NOMA transmissions in a cooperative cellular network in the presence of frequency selective multipath fading channels. Specifically, two users communicate with the base station simultaneously with existence of a half-duplex relay employing the decode-and-forward scheme to assist the far user. At the transmitting nodes, the power allocation factors are decided based on the statistical channel state information (CSI) rather than perfect CSI, while at the receiving nodes, the decoding order between the users is pre-specified and the effect of imperfect successive interference cancellation implementation is taken into account. Under Rayleigh fading channels, the authors derive the exact ergodic rate for the near user and the upper bound of the ergodic rate for the far user, and present an ad-hoc approach to determine the power allocation factors when the target data rates are given. Simulation results show that NOMA consistently outperforms orthogonal multiple access, however, the performance of uplink NOMA depends heavily on the proper choices of the power allocation factors and the relay location.
Hecke algebras and shellings of Bruhat intervals

© Foundation Compositio Mathematica, 1993, tous droits réservés. L’accès aux archives de la revue « Compositio Mathematica » (http: //http://www.compositio.nl/) implique l’accord avec les conditions générales d’utilisation (http://www.numdam.org/conditions). Toute utilisation commerciale ou impression systématique est constitutive d’une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright.
Lifetime Fitness in Wild Female Baboons: Trade-Offs and Individual Heterogeneity in Quality

Understanding the evolution of life histories requires information on how life histories vary among individuals and how such variation predicts individual fitness. Using complete life histories for females in a well-studied population of wild baboons, we tested two nonexclusive hypotheses about the relationships among survival, reproduction, and fitness: the quality hypothesis, which predicts positive correlations between life-history traits, mediated by variation in resource acquisition, and the trade-off hypothesis, which predicts negative correlations between life-history traits, mediated by trade-offs in resource allocation. In support of the quality hypothesis, we found that females with higher rates of offspring survival were themselves better at surviving. Further, after statistically controlling for variation in female quality, we found evidence for two types of trade-offs: females who produced surviving offspring at a slower rate had longer life spans than those who produced surviving offspring at a faster rate, and females who produced surviving offspring at a slower rate had a higher overall proportion of offspring survive infancy than females who produced surviving offspring at a faster rate. Importantly, these trade-offs were evident even when accounting for (i) the influence of offspring survival on maternal birth rate, (ii) the dependence of offspring survival on maternal survival, and (iii) potential age-related changes in birth rate and/or offspring survival. Our results shed light on why trade-offs are evident in some populations while variation in individual quality masks trade-offs in others.