Miracle-dz/UniFAR-FTUs huggingface dataset:
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation

We consider the off-policy estimation problem of estimating the expected reward of a target policy using samples collected by a different behavior policy. Importance sampling (IS) has been a key technique to derive (nearly) unbiased estimators, but is known to suffer from an excessively high variance in long-horizon problems. In the extreme case of in infinite-horizon problems, the variance of an IS-based estimator may even be unbounded. In this paper, we propose a new off-policy estimation method that applies IS directly on the stationary state-visitation distributions to avoid the exploding variance issue faced by existing estimators.Our key contribution is a novel approach to estimating the density ratio of two stationary distributions, with trajectories sampled from only the behavior distribution. We develop a mini-max loss function for the estimation problem, and derive a closed-form solution for the case of RKHS. We support our method with both theoretical and empirical analyses.
iTRAQ-Based Quantitative Proteome Revealed Metabolic Changes in Winter Turnip Rape (Brassica rapa L.) under Cold Stress

Winter turnip rape (Brassica rapa L.) is a large-scale winter-only oil crop cultivated in Northwest China. However, its cold-resistant molecular mechanism remains inadequate. Studying the cold adaptation mechanisms of winter turnip rape based on the proteomic technique of isobaric tags for relative and absolute quantification (iTRAQ) offers a solution to this problem. Under cold stress (−4 °C for eight hours), 51 and 94 differently accumulated proteins (DAPs) in Longyou 7 (cold-tolerant) and Tianyou 4 (cold-sensitive) were identified, respectively. These DAPs were classified into 38 gene ontology (GO) term categories, such as metabolic process, cellular process, catalytic activity, and binding. The 142 DAPs identified between the two cold-stressed cultivars were classified into 40 GO terms, including cellular process, metabolic process, cell, catalytic activity, and binding. Kyoto Encyclopedia of Genes and Genomes enrichment analysis indicated that the DAPs participated in 10 pathways. The abundance of most protein functions in ribosomes, carbon metabolism, photosynthesis, and energy metabolism including the citrate cycle, pentose phosphate pathway, and glyoxylate and dicarboxylate metabolism decreased, and the proteins that participate in photosynthesis–antenna and isoflavonoid biosynthesis increased in cold-stressed Longyou 7 compared with those in cold-stressed Tianyou 4. The expression pattern of genes encoding the 10 significant DAPs was consistent with the iTRAQ data. This study provides new information on the proteomic differences between the leaves of Longyou 7 and Tianyou 4 plants and explains the possible molecular mechanisms of cold-stress adaptation in B. rapa.
Cognitive performance of youth with primary generalized anxiety disorder versus primary obsessive–compulsive disorder

Despite gains made in the study of childhood anxiety, differential diagnosis remains challenging because of indistinct boundaries between disorders and high comorbidity. This is certainly true for generalized anxiety disorder (GAD) and obsessive–compulsive disorder (OCD) as they share multiple cognitive processes (e.g., rumination, intolerance of uncertainty, and increased attention to threat). Disentangling such cognitive characteristics and, subsequently, underlying mechanisms could serve to inform assessment and treatment practices, and improve prognoses.
Strength Analysis and Reliability Evaluation for Speed Reducers

This paper studies the structural stresses of differential drive (DD) and harmonic drive (HD) for design improvement of reducers. The designed principles of the two reducers are reported for function comparison. The critical components of the reducers are constructed for performing motion simulation and stress analysis. DD is designed based on differential displacement of the decelerated gear ring as well as HD on a flexible spline. Finite element method (FEM) is used to analyze the structural stresses including the dynamic properties of the reducers. The stresses including kinematic properties of the two reducers are compared to observe the properties of the designs. The analyzed results are applied to identify the allowable loads of the reducers in use. The reliabilities of the reducers in different loads are further calculated according to the variation of stress. The studied results are useful on engineering analysis and reliability evaluation for designing a speed reducer with high ratios.
Process evaluation of the midwifery initiated oral health‐dental service program: perceptions of pregnant women

BACKGROUND Pregnant women in Australia seldom seek dental care and are unaware of its importance. To address these gaps the midwifery-initiated oral health dental service (MIOH-DS) program was comprehensive trialled and found effective. The aim of this study was to undertake a process evaluation of the MIOH-DS using the perspectives of pregnant women who participated in the trial. METHODS A qualitative research design was utilized, whereby content analysis was undertaken on data from 11 semi-structured interviews with women who participated in the program. RESULTS All participants were receptive of the MIOH-DS intervention, and found it to be an acceptable intervention that met their needs, and encouraged future positive oral health practices and health-seeking behaviours. They expressed that midwives were an appropriate professional to conduct oral health assessments, education and referrals to affordable dental services. Although some participants were initially apprehensive towards receiving treatment during pregnancy, dental staff members were able to appropriately educate and reassure them during treatment. CONCLUSIONS The MIOH-DS represents a promising and acceptable intervention strategy for pregnant women to promote their oral health. Findings merit further investigation on whether positive outcomes achieved can be sustained when implemented in other national or international settings similar to the study setting.
European eel (Anguilla anguilla) plasma biochemistry alerts about propanil stress.

Propanil stress response in the eel (Anguilla anguilla) was examined. Eels were exposed to 3.16 mg/L for 72 hr and allowed to recover for 96 hr. Plasma levels of cortisol, lactate dehydrogenase (LDH), alkaline phosphatase (AP), aspartate aminotransferase (AST), cholesterol, triglycerides, glucose, ammonium, lactate, albumin, and total proteins as well as electrolytes (chloride, sodium, potassium, calcium and phosphorus) were determined. As a consequence of exposure, cortisol, AP, AST, and LDH increased. A hyperglycemic condition, together with hyperlactemia, hypoalbuminemia, hypoproteinemia, hypercholesterolemia and hypertriglycemia was registered. Ammonium increased during exposure concomitantly to hyponatremia, hypochloremia, hypocalcemia, hypophosphatemia, and hypokatremia. During recovery, chloride, sodium, potassium, ammonium, albumin and LDH normalized. At the end of the experiment, fish still exhibited hyperglycemia and hyperlactemia. Hypercalcemia was observed. Cholesterol, triglycerides, AP, and AST did not recuperate. These findings are important for assessing potential risks for areas where fish are grown near intensive herbicide use (i.e., paddy fields).
ℓ1 Regularization of Word Embeddings for Multi-Word Expression Identification

In this paper we compare the effects of applying various state-of-the-art word representation strategies in the task of multi-word expression (MWE) identification. In particular, we analyze the strengths and weaknesses of the usage of `1-regularized sparse word embeddings for identifying MWEs. Our earlier study demonstrated the effectiveness of regularized word embeddings in other sequence labeling tasks, i.e. part-of-speech tagging and named entity recognition, but it has not yet been rigorously evaluated for the identification of MWEs yet.
No Plasmatic Proteomic Signature at Clinical Disease Onset Associated With 11 Year Clinical, Cognitive and MRI Outcomes in Relapsing-Remitting Multiple Sclerosis Patients

Background: The clinical course of relapsing-remitting multiple sclerosis (RRMS) is highly heterogeneous and prognostic biomarkers at time of diagnosis are lacking. Objective: We investigated the predictive value of the plasma proteome at time of diagnosis in RRMS patients. Methods: The plasma proteome was interrogated using a novel aptamer-based proteomics platform, which allows to measure the levels of a predefined set of 1310 proteins. Results: In 67 clinically and radiologically well characterized RRMS patients, we found no association between the plasma proteome at diagnosis and clinical, cognitive or MRI outcomes after 11 years. Conclusions: Proteomics studies on cerebrospinal fluid may be better suited to identify prognostic biomarkers in early RRMS.
Chocola: integrating futures, actors, and transactions

Developers often combine different concurrency models in a single program, in each part of the program using the model that fits best. Many programming languages, such as Clojure, Scala, and Haskell, cater to this need by supporting different concurrency models. However, they are often combined in an ad hoc way and the semantics of the combination is not always well defined. This paper studies the combination of three concurrency models: futures, actors, and transactions. We show that a naive combination of these models invalidates the guarantees they normally provide, thereby breaking the assumptions of developers. Hence, we present Chocola: a unified framework of futures, actors, and transactions that maintains the guarantees of all models wherever possible, even when they are combined. We present the semantics of this model and its implementation in Clojure, and have evaluated its performance and expressivity using three benchmark applications.
From Question to Text

Understanding unstructured texts is an essential skill for human beings as it enables knowledge acquisition. Although understanding unstructured texts is easy for we human beings with good education, it is a great challenge for machines. Recently, with the rapid development of artificial intelligence techniques, researchers put efforts to teach machines to understand texts and justify the educated machines by letting them solve the questions upon the given unstructured texts, inspired by the reading comprehension test as we humans do. However, feature effectiveness with respect to different questions significantly hinders the performance of answer selection, because different questions may focus on various aspects of the given text and answer candidates. To solve this problem, we propose a question-oriented feature attention (QFA) mechanism, which learns to weight different engineering features according to the given question, so that important features with respect to the specific question is emphasized accordingly. Experiments on MCTest dataset have well-validated the effectiveness of the proposed method. Additionally, the proposed QFA is applicable to various IR tasks, such as question answering and answer selection. We have verified the applicability on a crawled community-based question-answering dataset.
Fully automatic structure from motion with a spline-based environment representation

While the common environment representation in structure from motion is given by a sparse point cloud, the community has also investigated the use of lines to better enforce the inherent regularities in man-made surroundings. Following the potential of this idea, the present paper introduces a more flexible higher-order extension of points that provides a general model for structural edges in the environment, no matter if straight or curved. Our model relies on linked Bezier curves, the geometric intuition of which proves great benefits during parameter initialization and regularization. We present the first fully automatic pipeline that is able to generate spline-based representations without any human supervision. Besides a full graphical formulation of the problem, we introduce both geometric and photometric cues as well as higher-level concepts such overall curve visibility and viewing angle restrictions to automatically manage the correspondences in the graph. Results prove that curve-based structure from motion with splines is able to outperform state-of-the-art sparse feature-based methods, as well as to model curved edges in the environment.
Research on Image Segmentation of Digital Rubbings Based on OTSU Threshold & Genetic Algorithm

This paper studies the binarization method of rubbings' image by analyzing the characteristics. Firstly, the segmentation results of iterative threshold segmentation and adaptive segmentation are given. It is shown that the general segmentation effect is not suitable for some images. Then, the segmentation principle of OTSU and genetic algorithm are given, and the segmentation results are verified by experiments. The experimental result shows that compared with the OTSU algorithm, the image segmentation method based on genetic algorithm can not only separate the target from the background effectively, but also filter out the large amount of image when segments the inscription image which is dim and it is indistinguishable between the target and background. At the same time, it retains the edge of the text strokes, as much as possible to restore the original image of rubbings face.
Robots Learn Social Skills: End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots

Co-speech gestures enhance interaction experiences between humans as well as between humans and robots. Most existing robots use rule-based speech-gesture association, but this requires human labor and prior knowledge of experts to be implemented. We present a learning-based co-speech gesture generation that is learned from 52 h of TED talks. The proposed end-to-end neural network model consists of an encoder for speech text understanding and a decoder to generate a sequence of gestures. The model successfully produces various gestures including iconic, metaphoric, deictic, and beat gestures. In a subjective evaluation, participants reported that the gestures were human-like and matched the speech content. We also demonstrate a co-speech gesture with a NAO robot working in real time.
Delay-Dependent Stability in Uncalibrated Image-Based Dynamic Visual Servoing Robotic System

This paper addresses the stability problem of uncalibrated image-based visual servoing robotic systems. Both the visual feedback delay and the uncalibrated visual parameters can be the sources of instability for visual servoing robotic systems. To eliminate the negative effects caused by kinematic uncertainties and delays, we propose an adaptive controller including the delay-affected Jacobian matrix and design an adaptive law accordingly. Besides, the delay-dependent stability conditions are provided to show the relationship between the system stability and the delayed time in order to obtain less conservative results. A Lyapunov-Krasovskii functional is constructed, and a rigorously mathematic proof is given. Finally, the simulation results are presented to show the effectiveness of the proposed control scheme.
A Unified Neural Network Model for Geolocating Twitter Users

Locations of social media users are important to many applications such as rapid disaster response, targeted advertisement, and news recommendation. However, many users do not share their exact geographical coordinates due to reasons such as privacy concerns. The lack of explicit location information has motivated a growing body of research in recent years looking at different automatic ways of determining the user’s primary location. In this paper, we propose a unified user geolocation method which relies on a fusion of neural networks. Our joint model incorporates different types of available information including tweet text, user network, and metadata to predict users’ locations. Moreover, we utilize a bidirectional LSTM network augmented with an attention mechanism to identify the most location indicative words in textual content of tweets. The experiments demonstrate that our approach achieves state-of-the-art performance over two Twitter benchmark geolocation datasets. We also conduct an ablation study to evaluate the contribution of each type of information in user geolocation performance.
A CARD9 Founder Mutation Disrupts NF-κB Signaling by Inhibiting BCL10 and MALT1 Recruitment and Signalosome Formation

Background: Inherited CARD9 deficiency constitutes a primary immunodeficiency predisposing uniquely to chronic and invasive fungal infections. Certain mutations are shown to negatively impact CARD9 protein expression and/or NF-κB activation, but the underlying biochemical mechanism remains to be fully understood. Objectives: To investigate a possible founder origin of a known CARD9 R70W mutation in five families of Turkish origin. To explore the biochemical mechanism of immunodeficiency by R70W CARD9. Methods: We performed haplotype analysis using microsatellite markers and SNPs. We designed a model system exploiting a gain-of-function (GOF) CARD9 L213LI mutant that triggers constitutive NF-κB activation, analogous to an oncogenic CARD11 mutant, to study NF-κB signaling and signalosome formation. We performed reporter assays, immunoprecipitation and confocal imaging on HEK cells overexpressing different CARD9 variants. Results: We identified a common haplotype, thus providing evidence for a common Turkish founder. CARD9 R70W failed to activate NF-κB and abrogated NF-κB activation by WT CARD9 and by GOF CARD9. Notably, R70W CARD9 also exerted negative effects on NF-κB activation by CARD10, CARD11, and CARD14. Consistent with the NF-κB results, the R70W mutation prevented GOF CARD9 to pull down the signalosome partner proteins BCL10 and MALT1. This reflected into drastic reduction of BCL10 filamentous assemblies in a cellular context. Indeed, structural analysis revealed that position R70 in CARD9 maps at the putative interface between successive CARD domains in CARD9 filaments. Conclusions: The R70W mutation in CARD9 prevents NF-κB activation by inhibiting productive interactions with downstream BCL10 and MALT1, necessary for assembly of the filamentous CARD9-BCL10-MALT1 signalosome.
Phylogeography and Population Structure of the Mediterranean Corn Borer, Sesamia nonagrioides (Lepidoptera: Noctuidae), Across Its Geographic Range

Abstract Sesamia nonagrioides (Lefèbvre) (Lepidoptera: Noctuidae), is a widespread insect pest in Africa, the Middle East, and Europe. However, its pest status varies across its distribution range. It is a major pest of maize in Europe and of sugarcane in Iran. In Africa, it is a major pest of maize in West Africa but not considered as a pest in East Africa. Recent surveys conducted in 2015 recorded S. nonagrioides to be a major pest of sugarcane in Ethiopia and reported the species for the first time in Botswana, outside its known geographic range. The genetic relationship of these records with the previously recorded population of S. nonagrioides was investigated using the cytochrome oxidase subunit I region of the mitochondrial genome. In total, 113 individuals across the geographic range of the species were analyzed and 63 haplotypes were identified. Phylogenetic analysis separated the populations into two clades with no distinct geographic distribution pattern. The genetic differentiation was also not associated with host plants and geographic distances. Results of the molecular analysis revealed the long-time establishment of S. nonagrioides population in Botswana and identified the newly recorded sugarcane population from Ethiopia as part of the wild host population in the country. The phylogeographic patterns observed among population of S. nonagrioides have probably been shaped by Pleistocene's climatic oscillations and geographic range expansions from different refugia with secondary contact and admixture. Possible reasons for the host-plant expansion by the Ethiopian population are discussed.
Simultaneous Dominating Set for Spanning Tree Factorings

For a connected graph $G$ we call a set $\mathcal{F}$ a spanning tree factoring of $G$ if it contains all spanning trees of $G$. A subset $S\subseteq V(G)$ is a simultaneous dominating set of $G$ if it is a dominating set in every spanning tree in $\mathcal{F}$. We consider the problem of finding a minimum size simultaneous dominating set for spanning tree factorings. We show that the decision version of this problem is NP-complete by pointing out its close relation to the vertex cover problem. We present an exact algorithm to solve this problem and show how to solve it in polynomial time on some graph classes like bipartite or chordal graphs. Moreover, we derive a $2$-approximation algorithm for this problem.
A quantitative research on clinical parameters of gingival contour for anterior teeth esthetic analysis and design

OBJECTIVES To provide reference for computer-aided esthetic analysis and design of the maxillary anterior teeth. MATERIALS AND METHODS Intraoral scanner was used to obtain the maxillary three-dimensional digital models of subjects with healthy periodontal tissue. In SpaceClaim, the occlusal plane was established as the horizontal reference plane to measure the positional relation between the gingival zenith (GZ) of the maxillary anterior teeth, the angle formed between the gingival line and the maxillary midline (GLA), the distance between the GZ of the lateral incisor and gingival line (LID), and the distance between the GZ and the vertical bisected middle surface along the long axis of the clinical crown (VBMS). RESULTS The GLA was 92.7 ± 3.2°. The GZ of the canine, lateral incisor, and left central incisor were located to the GZ of the right central incisor coronally at 0.68 ± 0.91, 0.65 ± 0.66 mm, and apically at 0.12 ± 0.42 mm, respectively. The LID was 0.65 ± 0.92 mm. The GZ of the canine, lateral incisor, and central incisor were located distally to the VBMS at 0.00 ± 0.06, 0.27 ± 0.19, and 0.73 ± 0.21 mm, respectively. CONCLUSION The GZ at different tooth position are in different heights. The direction and degree of the GZ deviation from the VBMS are also related to tooth position. CLINICAL SIGNIFICANCE The clinical parameters of the gingival contour obtained in this research can be used for patients with unsound contour of periodontal soft tissue to do the anterior teeth esthetic analysis. Besides, it can also be used to determine the proper position between the GZs of the maxillary anterior teeth in anterior teeth esthetic design.
Anti-Cancerous Potential of Polyphenol-Loaded Polymeric Nanotherapeutics

Recent evidence has extensively demonstrated the anticancer potential of nutraceuticals, including plant polyphenols. Polymeric nanocarrier systems have played an important role in improving the physicochemical and pharmacological properties of polyphenols, thus ameliorating their therapeutic effectiveness. This article summarizes the benefits and shortcomings of various polymeric systems developed for the delivery of polyphenols in cancer therapy and reveals some ideas for future work.
An empirical evaluation of imbalanced data strategies from a practitioner's point of view

This research tested the following well known strategies to deal with binary imbalanced data on 82 different real life data sets (sampled to imbalance rates of 5%, 3%, 1%, and 0.1%): class weight, SMOTE, Underbagging, and a baseline (just the base classifier). As base classifiers we used SVM with RBF kernel, random forests, and gradient boosting machines and we measured the quality of the resulting classifier using 6 different metrics (Area under the curve, Accuracy, F-measure, G-mean, Matthew's correlation coefficient and Balanced accuracy). The best strategy strongly depends on the metric used to measure the quality of the classifier. For AUC and accuracy class weight and the baseline perform better; for F-measure and MCC, SMOTE performs better; and for G-mean and balanced accuracy, underbagging.