Miracle-dz/UniFAR-FTUs huggingface dataset:
Supervised Complementary Entity Recognition with Augmented Key-value Pairs of Knowledge

Extracting opinion targets is an important task in sentiment analysis on product reviews and complementary entities (products) are one important type of opinion targets that may work together with the reviewed product. In this paper, we address the problem of Complementary Entity Recognition (CER) as a supervised sequence labeling with the capability of expanding domain knowledge as key-value pairs from unlabeled reviews, by automatically learning and enhancing knowledge-based features. We use Conditional Random Field (CRF) as the base learner and augment CRF with knowledge-based features (called the Knowledge-based CRF or KCRF for short). We conduct experiments to show that KCRF effectively improves the performance of supervised CER task.
Tradeoff Between Delay and Physical Layer Security in Wireless Networks

Exchange of crucial and confidential information leads to the unprecedented attention on the security problem in wireless networks. Even though the security has been studied in a number of works, the joint optimization of the physical layer security and the end-to-end delay management, which requires a meticulous cross-layer design, has seldom been evaluated. In this paper, by combining the tools from stochastic geometry and queueing theory, we analyze the tradeoff between the delay and the security performance in large wireless networks. We further propose a simple transmission mechanism which splits a message into two packets and evaluate its effect on the mean delay and the secrecy outage probability. Our numerical results reveal that the security performance is better for larger path loss exponent when the density of legitimate nodes is large, and it is reverse when the density is small. Moreover, it is observed that by introducing the simple mechanism of message split, the security performance is greatly improved in the backlogged scenario and slightly improved in the dynamic scenario when the density of legitimate transmitters is large. In summary, this paper provides an understanding and a rule-of-thumb for the practical design of wireless networks where both the delay and the security are key concerns.
Peripheral and prefrontal stress system markers and risk of relapse in alcoholism

Previous research has shown that hyperactivation in ventral medial prefrontal cortex (VmPFC) and rostral anterior cingulate cortex (rACC) and high cortisol to corticotrophin ratio (cort:ACTH ratio) during neutral‐relaxed states predict relapse in alcohol‐dependent (AD) patients. Other studies have shown that VmPFC/rACC deactivation and blunted cortisol release to stress and alcohol cues are predictive of time to relapse and relapse severity. However, no previous study has assessed the relationship between these markers of central and peripheral nervous system dysfunction in AD participants and their potential joint effects on relapse risk. Forty early abstinent, treatment engaged AD patients underwent a laboratory experiment with exposure to neutral, alcohol and stress cues and a separate functional magnetic resonance imaging scan with similar cue exposure. Neutral‐relaxed state cort:ACTH ratio was significantly associated with VmPFC hyperreactivity to neutral‐relaxing cues, and also with hypoactivation in response to alcohol and stress cues in AD patients. Basal heart rate, neutral cort:ACTH ratio and neutral VmPFC hyperreactivty were each associated with risk of relapse. However, abnormal VmPFC activation and elevated cort:ACTH ratio overlap in predicting risk for relapse, and dysfunctional VmPFC response was the sole significant predictor of odds of relapse in a joint model of relapse risk. These findings suggest that the cort:ACTH ratio may serve as a peripheral marker of VmPFC brain dysfunction, while aberrant VmPFC responses need further evaluation as a potential biomarker of alcohol relapse risk in clinical outcome studies.
Games with a Purpose

Through online games, people can collectively solve large-scale computational problems. Such games constitute a general mechanism for using brain power to solve open problems. In fact, designing such a game is much like designing an algorithm - it must be proven correct, its efficiency can be analyzed, a more efficient version can supersede a less efficient one, and so on. "Games with a purpose" have a vast range of applications in areas as diverse as security, computer vision, Internet accessibility, adult content filtering, and Internet search. Any game designed to address these and other problems must ensure that game play results in a correct solution and, at the same time, is enjoyable. People will play such games to be entertained, not to solve a problem - no matter how laudable the objective
Abnormalities in hippocampal volume of glioma patients prior to radiotherapy

Abstract Background: Radiation-induced cognitive impairment may be mediated by hippocampal damage, but the structural integrity of this region in tumor patients at baseline is unclear. Hippocampal volumes of 31 glioma patients prior to receiving radiotherapy were compared to a group of 34 healthy controls. Materials and methods: Left and right hippocampi on T1-weighted pre-contrast magnetic resonance images were automatically segmented using Freesurfer, and visually inspected for segmentation errors. Normalized hippocampal volume for each subject was calculated as the sum of left and right hippocampal volumes divided by the estimated total intracranial volume. The normalized amygdala volume was similarly analyzed as a reference structure. Results: A Wilcoxon rank-sum test showed a significant difference in normalized hippocampal volumes between patients and controls (mean value 0.499 vs. 0.524, p = .01). No statistically significant difference was found for the amygdala. A post-hoc analysis revealed a significant difference in normalized hippocampal volumes between patients who had experienced seizures (mean value: 0.480, p < .05) and controls. No difference was noted between patients without seizures (mean value: 0.513) and controls. Conclusions: Hippocampi of glioma patients prior to radiotherapy were significantly smaller than those of age-matched controls. Group differences were larger in patients with tumor-associated seizures. This may be secondary to other processes such as tumor biology and inflammation.
Acute pulmonary edema and unstable coronary disease

Submit Manuscript | http://medcraveonline.com mortality was 14.1% [2]. Among the modalities of acute cardiac insufficiency, it occupies the second place in hospital cost, the cardiogenic shock is the first one [3]. Breathless is the main symptom of HF and in APE is usually very intense. The differential diagnosis of dyspnea in the emergency room is broad, but the main diseases to be excluded due to the severity and risk of death are HF, acute coronary syndrome (ACS) and pulmonary embolism [4].
Augmenting Librispeech with French Translations: A Multimodal Corpus for Direct Speech Translation Evaluation

Recent works in spoken language translation (SLT) have attempted to build end-to-end speech-to-text translation without using source language transcription during learning or decoding. However, while large quantities of parallel texts (such as Europarl, OpenSubtitles) are available for training machine translation systems, there are no large (100h) and open source parallel corpora that include speech in a source language aligned to text in a target language. This paper tries to fill this gap by augmenting an existing (monolingual) corpus: LibriSpeech. This corpus, used for automatic speech recognition, is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned. After gathering French e-books corresponding to the English audio-books from LibriSpeech, we align speech segments at the sentence level with their respective translations and obtain 236h of usable parallel data. This paper presents the details of the processing as well as a manual evaluation conducted on a small subset of the corpus. This evaluation shows that the automatic alignments scores are reasonably correlated with the human judgments of the bilingual alignment quality. We believe that this corpus (which is made available online) is useful for replicable experiments in direct speech translation or more general spoken language translation experiments.
Computing Average Passive Forces in Sarcomeres in Length-Ramp Simulations

Passive forces in sarcomeres are mainly related to the giant protein titin. Titin’s extensible region consists of spring-like elements acting in series. In skeletal muscles these elements are the PEVK segment, two distinct immunoglobulin (Ig) domain regions (proximal and distal), and a N2A portion. While distal Ig domains are thought to form inextensible end filaments in intact sarcomeres, proximal Ig domains unfold in a force- and time-dependent manner. In length-ramp experiments of single titin strands, sequential unfolding of Ig domains leads to a typical saw-tooth pattern in force-elongation curves which can be simulated by Monte Carlo simulations. In sarcomeres, where more than a thousand titin strands are arranged in parallel, numerous Monte Carlo simulations are required to estimate the resultant force of all titin filaments based on the non-uniform titin elongations. To simplify calculations, the stochastic model of passive forces is often replaced by linear or non-linear deterministic and phenomenological functions. However, new theories of muscle contraction are based on the hypothesized binding of titin to the actin filament upon activation, and thereby on a prominent role of the structural properties of titin. Therefore, these theories necessitate a detailed analysis of titin forces in length-ramp experiments. In our study we present a simple and efficient alternative to Monte Carlo simulations. Based on a structural titin model, we calculate the exact probability distributions of unfolded Ig domains under length-ramp conditions needed for rigorous analysis of expected forces, distribution of unfolding forces, etc. Due to the generality of our model, the approach is applicable to a wide range of stochastic protein unfolding problems.
Type A/Type B Alcoholism Predicts Differential Response to Topiramate in a Smoking Cessation Trial in Dually Diagnosed Men.

OBJECTIVE Babor's A/B typology characterizes alcohol-dependence subtypes, which differ across multiple defining variables; however, differences in cigarette smoking and cessation between these subtypes have not been previously investigated. Topiramate reduces heavy drinking and has separately been found to help non-alcohol-dependent individuals quit smoking. This study tested the hypothesis that topiramate's effects on smoking would be moderated by alcohol-dependence subtype, and explored craving as a mediator of this response. METHOD One hundred twenty-nine abstinent alcohol-dependent outpatient male smokers participated in this 12-week, randomized controlled trial comparing topiramate (maximum dosage 200 mg/day) with placebo, both with brief counseling, for smoking cessation. Participants were followed for 24 weeks following end of treatment. RESULTS Of the 125 participants with sufficient subtyping data, k-means cluster analysis categorized 52 (42%) as Type A alcoholics and 73 (58%) as Type B. Types A and B did not differ on baseline smoking characteristics, urges to smoke, or smoking consequence scores. Longitudinal mixed-effects regression indicated that the effect of treatment on smoking was moderated by the Type × Time interaction. Specifically, during the nontreatment follow-up phase, Type B's treated with topiramate had relative suppressed levels of smoking compared with placebo-treated Type B's. This moderating effect of the Type × Time interaction was mediated by intention to smoke and craving related to relief of negative affect. CONCLUSIONS Type B alcoholics demonstrated suppressed levels of smoking in response to topiramate treatment as compared with placebo, but only during the nontreatment follow-up phase. This effect was mediated, in part, through intention to smoke and craving to smoke to relieve negative affect. Our findings extend other studies demonstrating a differential medication response by alcoholism subtype.
Pseudo-Recursal: Solving the Catastrophic Forgetting Problem in Deep Neural Networks

In general, neural networks are not currently capable of learning tasks in a sequential fashion. When a novel, unrelated task is learnt by a neural network, it substantially forgets how to solve previously learnt tasks. One of the original solutions to this problem is pseudo-rehearsal, which involves learning the new task while rehearsing generated items representative of the previous task/s. This is very effective for simple tasks. However, pseudo-rehearsal has not yet been successfully applied to very complex tasks because in these tasks it is difficult to generate representative items. We accomplish pseudo-rehearsal by using a Generative Adversarial Network to generate items so that our deep network can learn to sequentially classify the CIFAR-10, SVHN and MNIST datasets. After training on all tasks, our network loses only 1.67% absolute accuracy on CIFAR-10 and gains 0.24% absolute accuracy on SVHN. Our model's performance is a substantial improvement compared to the current state of the art solution.
Evaluation of Wearable Haptic Systems for the Fingers in Augmented Reality Applications

Although Augmented Reality (AR) has been around for almost five decades, only recently we have witnessed AR systems and applications entering in our everyday life. Representative examples of this technological revolution are the smartphone games “Pokémon GO” and “Ingress” or the Google Translate real-time sign interpretation app. Even if AR applications are already quite compelling and widespread, users are still not able to physically interact with the computer-generated reality. In this respect, wearable haptics can provide the compelling illusion of touching the superimposed virtual objects without constraining the motion or the workspace of the user. In this paper, we present the experimental evaluation of two wearable haptic interfaces for the fingers in three AR scenarios, enrolling 38 participants. In the first experiment, subjects were requested to write on a virtual board using a real chalk. The haptic devices provided the interaction forces between the chalk and the board. In the second experiment, subjects were asked to pick and place virtual and real objects. The haptic devices provided the interaction forces due to the weight of the virtual objects. In the third experiment, subjects were asked to balance a virtual sphere on a real cardboard. The haptic devices provided the interaction forces due to the weight of the virtual sphere rolling on the cardboard. Providing haptic feedback through the considered wearable device significantly improved the performance of all the considered tasks. Moreover, subjects significantly preferred conditions providing wearable haptic feedback.
Toward Character Role Assignment for Natural Language Stories

In this paper we propose a method for automatically assigning narrative roles to characters in stories. To achieve this goal our proposal is to combine natural language processing techniques with domain knowledge extracted from Propp's morphology of the folktale. We use a matrix that encodes the narrative domain knowledge representing the interactions between character roles.
Let's be honest: An optimal no-regret framework for zero-sum games

We revisit the problem of solving two-player zero-sum games in the decentralized setting. We propose a simple algorithmic framework that simultaneously achieves the best rates for honest regret as well as adversarial regret, and in addition resolves the open problem of removing the logarithmic terms in convergence to the value of the game. We achieve this goal in three steps. First, we provide a novel analysis of the optimistic mirror descent (OMD), showing that it can be modified to guarantee fast convergence for both honest regret and value of the game, when the players are playing collaboratively. Second, we propose a new algorithm, dubbed as robust optimistic mirror descent (ROMD), which attains optimal adversarial regret without knowing the time horizon beforehand. Finally, we propose a simple signaling scheme, which enables us to bridge OMD and ROMD to achieve the best of both worlds. Numerical examples are presented to support our theoretical claims and show that our non-adaptive ROMD algorithm can be competitive to OMD with adaptive step-size selection.
Hardening Deep Neural Networks via Adversarial Model Cascades

Deep neural networks (DNNs) are vulnerable to malicious inputs crafted by an adversary to produce erroneous outputs. Works on securing neural networks against adversarial examples achieve high empirical robustness on simple datasets such as MNIST. However, these techniques are inadequate when empirically tested on complex data sets such as CIFAR-10 and SVHN. Further, existing techniques are designed to target specific attacks and fail to generalize across attacks. We propose Adversarial Model Cascades (AMC) as a way to tackle the above inadequacies. Our approach trains a cascade of models sequentially where each model is optimized to be robust towards a mixture of multiple attacks. Ultimately, it yields a single model which is secure against a wide range of attacks; namely FGSM, Elastic, Virtual Adversarial Perturbations and Madry. On an average, AMC increases the model’s empirical robustness against various attacks simultaneously, by a significant margin (of 6.225% for MNIST, 5.075% for SVHN and 2.65% for CIFAR-10 ). At the same time, the model’s performance on non-adversarial inputs is comparable to the state-of-the-art models.
Automatic Test Generation from Coupled UML Models using Input Partitions

In this paper, we deal with model-based automatic test generation. We show how to use coupled models consisting of UML state machines, class diagrams, and OCL expressions to automatically derive partitions of input ranges for boundary testing. We present a test generation algorithm, describe an implementation of this algorithm, and compare this implementation to Rhapsody’s ATG.
Instrumenting cloud caches for online workload monitoring: the case of online miss rate curve estimation in memcached

Fast and efficient algorithms to estimate miss rate curves have recently been proposed, yet these have not been incorporated into cloud caches. Numerous applications that could benefit from these techniques are relying on less useful cache metrics or incomplete information. We study how to instrument cloud caches to obtain online miss rate curves (MRCs). Our approach leverages state-of-the-art algorithms and data structures, thus incurring in negligible overhead. We also propose an alternative design that makes it easier to change the MRC estimation algorithm, as well as plug-in other monitoring techniques. We implemented our designs in one of the top cloud caches: Memcached. We show via experimentation, that our implementation is efficient. Finally, we discuss how our solution can be used to improve the management of cloud caches; in particular, our code can be used by caching middleware to auto-adapt to changes in workload and maximize performance.
Several classifiers for intruder detection applications

The goal of this work is to present some possible intruder detection systems and the influence of impulse-like signals upon the overall classification accuracy. Two different scenarios are used: in the first scenario five sound classes are considered (last class belong to impulsive sounds — gunshots), while in the second scenario we dropped out the impulsive sound class. More classifiers are used in both scenarios and different number of features are considered. An improvement in the classification accuracy is obtained within the second scenario. The highest accuracy for the first scenario is for J48 classifier using 51 features, while for the second scenario the highest accuracy is attained for Simple Logistic classifier wit 101 features.
Genetics of growth and reproduction in the turkey. I. Genetic and non-genetic variation in body weight and body measruements.

Abstract SEVERAL estimates of heritability of body weight have been made for turkeys of various ages. Most of these estimates have been made using selected populations (El-Ibiary and Jull, 1948; Abplanalp and Kosin, 1952; Bumgardner and Shaffner, 1954; MacLaury et al., 1954; Goodman et al., 1954; McCartney, 1955; Johnson and Asmundson, 1957a; and Cook et al., 1962). The unweighted averages of these estimates were . 40, . 42, . 43 and . 36, respectively, for birds in the age groups 0 to 8, 9 to 16, 17 to 24, and greater than 24 weeks. McCartney (1961) estimated the heritability of body weight at 8, 16, and 24 weeks of age by full sib analysis in a randombred control population. These estimates averaged . 68, . 61, and . 62, respectively, at the three ages. Abplanalp et al. (1963) observed realized heritabilities of . 43 and . 62 for 8 and 24 week body weights, respectively. Estimates of the heritability of .
Polymeric micelles for potentiated antiulcer and anticancer activities of naringin

Naringin is one of the most interesting phytopharmaceuticals that has been widely investigated for various biological actions. Yet, its low water solubility, limited permeability, and suboptimal bioavailability limited its use. Therefore, in this study, polymeric micelles of naringin based on pluronic F68 (PF68) were developed, fully characterized, and optimized. The optimized formula was investigated regarding in vitro release, storage stability, and in vitro cytotoxicity vs different cell lines. Also, cytoprotection against ethanol-induced ulcer in rats and antitumor activity against Ehrlich ascites carcinoma in mice were investigated. Nanoscopic and nearly spherical 1:50 micelles with the mean diameter of 74.80±6.56 nm and narrow size distribution were obtained. These micelles showed the highest entrapment efficiency (EE%; 96.14±2.29). The micelles exhibited prolonged release up to 48 vs 10 h for free naringin. The stability of micelles was confirmed by insignificant changes in drug entrapment, particle size, and retention (%) (91.99±3.24). At lower dose than free naringin, effective cytoprotection of 1:50 micelles against ethanol-induced ulcer in rat model has been indicated by significant reduction in mucosal damage, gastric level of malondialdehyde, gastric expression of tumor necrosis factor-alpha, caspase-3, nuclear factor kappa-light-chain-enhancer of activated B cells, and interleukin-6 with the elevation of gastric reduced glutathione and superoxide dismutase when compared with the positive control group. As well, these micelles provoked pronounced antitumor activity assessed by potentiated in vitro cytotoxicity particularly against colorectal carcinoma cells and tumor growth inhibition when compared with free naringin. In conclusion, 1:50 naringin–PF68 micelles can be represented as a potential stable nanodrug delivery system with prolonged release and enhanced antiulcer as well as antitumor activities.