Miracle-dz/UniFAR-FTUs huggingface dataset:
Automating Political Bias Prediction

Every day media generate large amounts of text. An unbiased view on media reports requires an understanding of the political bias of media content. Assistive technology for estimating the political bias of texts can be helpful in this context. This study proposes a simple statistical learning approach to predict political bias from text. Standard text features extracted from speeches and manifestos of political parties are used to predict political bias in terms of political party affiliation and in terms of political views. Results indicate that political bias can be predicted with above chance accuracy. Mistakes of the model can be interpreted with respect to changes of policies of political actors. Two approaches are presented to make the results more interpretable: a) discriminative text features are related to the political orientation of a party and b) sentiment features of texts are correlated with a measure of political power. Political power appears to be strongly correlated with positive sentiment of a text. To highlight some potential use cases a web application shows how the model can be used for texts for which the political bias is not clear such as news articles.
Implementation of a passive control system for limiting cavitation around hydrofoils

The performance and the durability of hydraulic systems can be significantly compromised by cavitation. To the aim of delaying cavitation inside turbomachinery, a new passive cavitation control system is proposed in this work. The mentioned system has been applied to a NACA0009 hydrofoil, which accurately reproduces the flow field around real impeller blades. Basically, it consists of slots generating a connection between the suction and the pressure side of the foil. This connection results in a pressure rise close to the leading edge of the foil. Numerical simulations have been performed with the open-source CFD code OpenFOAM and the results have been compared to experimental data available in the literature. The simulations allow to investigate the flow field unsteadiness and the possible flow separation induced by the slots. The passive cavitation control system provides remarkable advantages, i.e., strong reduction of the vapour volume fraction (-93%) accompanied by a reasonable level of loss of performance (lift coefficient reduction equal to -25% and drag coefficient increase equal to +42%). This result is particularly interesting in consideration that the leading edge is only a small part of the entire vane of an impeller.
Superior Vena Cava Syndrome Associated with Right-to-Left Shunt through Systemic-to-Pulmonary Venous Collaterals

Superior vena cava (SVC) obstruction is associated with the gradual development of venous collaterals. We present a rare form of systemic-to-pulmonary subpleural collateral pathway that developed in the bridging subpleural pulmonary veins in a 54-year-old woman with complete SVC obstruction. This uncommon collateral pathway represents a rare form of acquired right-to-left shunt due to previous pleural adhesions with an increased risk of stroke due to right-to-left venous shunting, which requires lifelong anticoagulation.
Statistical timing analysis for intra-die process variations with spatial correlations

Process variations have become a critical issue in performance verification of high-performance designs. We present a new, statistical timing analysis method that accounts for inter- and intra-die process variations and their spatial correlations. Since statistical timing analysis has an exponential run time complexity, we propose a method whereby a statistical bound on the probability distribution function of the exact circuit delay is computed with linear run time. First, we develop a model for representing inter- and intra-die variations and their spatial correlations. Using this model, we then show how gate delays and arrival times can be represented as a sum of components, such that the correlation information between arrival times and gate delays is preserved. We then show how arrival times are propagated and merged in the circuit to obtain an arrival time distribution that is an upper bound on the distribution of the exact circuit delay. We prove the correctness of the bound and also show how the bound can be improved by propagating multiple arrival times. The proposed algorithms were implemented and tested on a set of benchmark circuits under several process variation scenarios. The results were compared with Monte Carlo simulation and show an accuracy of 3.32% on average over all test cases.
Estimation Algorithms of Popular Objects on Distributed Hash Table Using Local Lookup Logs

Peer-to-Peer (P2P) systems are getting great inter- ests for infrastructures of various network services. For many purposes, such as decreasing delays, load balancing, and stability, many replica placement schemes are proposed for P2P systems. But it is difficult to place a large amount of replicas by some reasons such as limitation of storage and increase of control messages. Thus it is important to judge which data object must be replicated. The popularity of data objects is key information to decide the number of replicas, but it is difficult to know the whole popularity in pure P2P systems. In this paper, estimation algorithms of popular objects using local lookup logs stored in each peer are proposed. Experimental results show how well the algorithms can estimate popular objects. I. INTRODUCTION However, popularity of all objects cannot be observed in P2P systems without a/some centralized control(s), which is called pure P2P systems. That is, estimation of whole popularity in P2P systems is difficult, but is very important as fundamental research to decide the optimal number of replicas. In this paper, we discuss estimation methods for popularity of all objects using lookup logs, each of which is recorded locally on each peer. Our proposal is based on Chord(4) as the representative example of a DHT. At first, an esti- mation algorithm on a single peer using its local lookup log is described. Then the modified algorithm considering the nonuniform probability distribution of lookups is shown. Because the content of lookup log stored in a peer relies greatly on both where the peer is located and where data objects are located, it is difficult to estimate the popularity of whole system using only one lookup log on a peer. Thus, an algorithm, which estimates the whole popularity by merging some results of local estimations, is proposed. In addition, a modified algorithm, which focuses on coocurrence of objects' lookup among peers, is considered. Experimental results show how well proposed algorithms can estimate popular objects using measures of precision, recall, and f-measure. Also, the effectiveness of two modi- fications to the base algorithms are verified. The remainder of this paper is organized as follows. Section II mentions related work. Section III briefly describes Chord and our assumption for our proposal. Section IV proposes estimation algorithms of popular objects using local lookup logs on peers. In Section V, experimental results are shown to evaluate our proposal. Finally, Section VI concludes this paper.
Review on Handling Characteristics of Road Vehicles

Handling characteristics of vehicles are closely related to driving safety. Handling characteristics of road vehicles refer to its response to steering commands and to environmental inputs, such as wind gust and road disturbances that affect its direction of motion. Many traffic accidents are caused by undesired and unexpected handling behavior of vehicle. Hence it is necessary to understand the handling characteristics of vehicle. In this paper detail study is carried out related to handling characteristics of vehicles.
The pragmatics of expressive content: Evidence from large corpora

We use large collections of online product reviews, in Chinese, English, German, and Japanese, to study the use conditions of expressives (swears, antihonorifics, intensives). The distributional evidence provides quantitative support for a pragmatic theory of these items that is based in speaker and hearer expectations.
Linear models for minimizing misclassification costs in bankruptcy prediction

This paper illustrates how a misclassification cost matrix can be incorporated into an evolutionary classification system for bankruptcy prediction. Most classification systems for predicting bankruptcy have attempted to minimize misclassifications. The minimizing misclassification approach assumes that Type I and Type II error costs for misclassifications are equal. There is evidence that these costs are not equal and incorporating costs into the classification systems can lead to better and more desirable results. In this paper, we use the principles of evolution to develop and test a genetic algorithm (GA) based approach that incorporates the asymmetric Type I and Type II error costs. Using simulated and real-life bankruptcy data, we compare the results of our proposed approach with three linear approaches: statistical linear discriminant analysis (LDA), a goal programming approach, and a GA-based classification approach that does not incorporate the asymmetric misclassification costs. Our results indicate that the proposed approach, incorporating Type I and Type II error costs, results in lower misclassification costs when compared to LDA and GA approaches that do not incorporate misclassification costs. Copyright © 2001 John Wiley & Sons, Ltd.
Rapid, Efficient Detection and Drug Susceptibility Testing of Mycobacterium tuberculosis in Sputum by Microscopic Observation of Broth Cultures

ABSTRACT Inexpensive, rapid, and reliable methods of detecting infection by and drug susceptibility of Mycobacterium tuberculosis (MTB) are crucial to the control of tuberculosis. The novel microscopic observation broth-drug susceptibility assay (MODS) detects early growth of MTB in liquid medium, allowing more timely diagnosis and drug susceptibility testing. Sputum samples from hospitalized patients in Peru were analyzed by using stains, culture, and PCR. Sensitivity of MODS (92%) compared favorably with the most sensitive of the other culture methods (93%). Sputum samples positive for tuberculosis were tested for susceptibility to isoniazid and rifampin with the microwell alamar blue assay (MABA) and MODS. In 89% of cases, there was concordance between MODS and MABA. Of the diagnostic and susceptibility testing methods used, MODS yielded results most rapidly (median, 9.0 and 9.5 days, respectively). MODS is a rapid, inexpensive, sensitive, and specific method for MTB detection and susceptibility testing; it is particularly appropriate for use in developing countries burdened by significant infection rates and increasing numbers of multiple-drug-resistant cases.
MassTRIX: mass translator into pathways

Recent technical advances in mass spectrometry (MS) have brought the field of metabolomics to a point where large numbers of metabolites from numerous prokaryotic and eukaryotic organisms can now be easily and precisely detected. The challenge today lies in the correct annotation of these metabolites on the basis of their accurate measured masses. Assignment of bulk chemical formula is generally possible, but without consideration of the biological and genomic context, concrete metabolite annotations remain difficult and uncertain. MassTRIX responds to this challenge by providing a hypothesis-driven approach to high precision MS data annotation. It presents the identified chemical compounds in their genomic context as differentially colored objects on KEGG pathway maps. Information on gene transcription or differences in the gene complement (e.g. samples from different bacterial strains) can be easily added. The user can thus interpret the metabolic state of the organism in the context of its potential and, in the case of submitted transcriptomics data, real enzymatic capacities. The MassTRIX web server is freely accessible at http://masstrix.org
Agonist-dependent Signaling by Group I Metabotropic Glutamate Receptors Is Regulated by Association with Lipid Domains*

Background: Lipid rafts regulate GPCR signaling. Results: MGluR1 recruitment to lipid rafts is facilitated by a cholesterol recognition/interaction amino acid consensus motif and enhances agonist-dependent signaling. Conclusion: Cholesterol within lipid rafts functions as an allosteric modulator of mGluR1 activity. Significance: Cholesterol altering drugs may provide a means to modulate mGluR activity in neuropsychiatric conditions, including fragile X syndrome. Group I metabotropic glutamate receptors (mGluRs), mGluR1 and mGluR5, play critical functions in forms of activity-dependent synaptic plasticity and synapse remodeling in physiological and pathological states. Importantly, in animal models of fragile X syndrome, group I mGluR activity is abnormally enhanced, a dysfunction that may partly underlie cognitive deficits in the condition. Lipid rafts are cholesterol- and sphingolipid-enriched membrane domains that are thought to form transient signaling platforms for ligand-activated receptors. Many G protein-coupled receptors, including group I mGluRs, are present in lipid rafts, but the mechanisms underlying recruitment to these membrane domains remain incompletely understood. Here, we show that mGluR1 recruitment to lipid rafts is enhanced by agonist binding and is supported at least in part by an intact cholesterol recognition/interaction amino acid consensus (CRAC) motif in the receptor. Substitutions of critical residues in the motif reduce mGluR1 association with lipid rafts and agonist-induced, mGluR1-dependent activation of extracellular-signal-activated kinase1/2 MAP kinase (ERK-MAPK). We find that alteration of membrane cholesterol content or perturbation of lipid rafts regulates agonist-dependent activation of ERK-MAPK by group I mGluRs, suggesting a potential function for cholesterol as a positive allosteric modulator of receptor function(s). Together, these findings suggest that drugs that alter membrane cholesterol levels or directed to the receptor-cholesterol interface could be employed to modulate abnormal group I mGluR activity in neuropsychiatric conditions, including fragile X syndrome.
Oogenesis: Chromatin and microtubule dynamics during meiotic prophase

Changes in the organization of germinal vesicle chromatin in mouse oocytes have been analyzed by fluorescence microscopy with respect to progressive stages of follicular development and the disposition of oocyte cytoplasmic microtubules. Four discrete patterns of chromatin organization exist in germinal vesicle (GV)‐stage oocytes isolated from the ovaries of 21–25‐day‐old gonadotropin‐primed mice. Analysis of ovarian cryosections stained with the DNA‐binding fluorochrome Hoechst 33258 indicates that sequential changes in GV chromatin occur duing folliculogenesis that result in the formation of a continuous perinucleolar chromatin sheath at the time of antrum formation. Specific alterations in the cytoplasmic microtubule complex of GV‐stage oocytes were observed that correlate with chromatin patterns. The extensive cytoplasmic microtubule complex seen in oocytes of preantral follicles initially localizes to perinuclear areas of the ooplasm. This is followed by a progressive reduction in cytoplasmic microtubules and the appearance of prominent microtubule‐organizing centers at the nuclear periphery. Coordinated nuclear and microtubular alterations also occur under in vitro conditions prior to progression of meiosis to prometaphase‐1. The results are discussed with respect to the ongoing differentiation of the oocyte nucleus and the microtubule cytoskeleton during folliculogenesis in preparation for the resumption of meiosis.
Fatigue and cognition: Pupillary responses to problem‐solving in early multiple sclerosis patients

In early multiple sclerosis (MS) patients, cognitive changes and fatigue are frequent and troublesome symptoms, probably related to both structural and functional brain changes. Whether there is a common cause of these symptoms in MS is unknown. In theory, an altered regulation of central neuropeptides can lead to changes in regulation of autonomic function, cognitive difficulties, and fatigue. Direct measurements of central neuropeptides are difficult to perform, but measurements of the eye pupil can be used as a reliable proxy of function.
Performance Analysis of ℓ1-synthesis with Coherent Frames

Signals with sparse frame representations comprise a much more realistic model of nature than that with orthonomal bases. Studies about the signal recovery associated with such sparsity models have been one of major focuses in compressed sensing. In such settings, one important and widely used signal recovery approach is known as $\ell_1$-synthesis (or Basis Pursuit). We present in this article a more effective performance analysis (than what are available) of this approach in which the dictionary $\Dbf$ may be highly, and even perfectly correlated. Under suitable conditions on the sensing matrix $\Phibf$, an error bound of the recovered signal $\hat{\fbf}$ (by the $\ell_1$-synthesis method) is established. Such an error bound is governed by the decaying property of $\tilde{\Dbf}_{\text{o}}^*\fbf$, where $\fbf$ is the true signal and $\tilde{\Dbf}_{\text{o}}$ denotes the optimal dual frame of $\Dbf$ in the sense that $\|\tilde{\Dbf}_{\text{o}}^*\hat{\fbf}\|_1$ produces the smallest $\|\tilde{\Dbf}^*\tilde{\fbf}\|_1$ in value among all dual frames $\tilde{\Dbf}$ of $\Dbf$ and all feasible signals $\tilde{\fbf}$. This new performance analysis departs from the usual description of the combo $\Phibf\Dbf$, and places the description on $\Phibf$. Examples are demonstrated to show that when the usual analysis fails to explain the working performance of the synthesis approach, the newly established results do.
Augmenting situation awareness via model-based control in rescue robots

In this work we describe a model-based approach to the executive control of a rescue rover. We show how this control architecture naturally supports human-robot interaction in the diverse activities needed in rescue and search. We illustrate the approach by considering human-robot interaction in the domain of the RoboCup rescue competition. We discuss the implementation and tests done both during RoboCup contests and in the laboratory, to show performances according to different working modalities such as fully operated, supervised, fully autonomous.
The channel‐forming toxin aerolysin neutralizes human immunodeficiency virus type 1

Aerolysin is a channel‐forming toxin secreted by Aeromonas spp. that binds to glycosyl phosphatidylinositol (GPI)‐anchored proteins, such as Thy‐1, on sensitive target cells. Receptor binding is followed first by oligomerization of the toxin and then by insertion of the oligomers into the membrane to form stable channels that disrupt the permeability barrier. Human immunodeficiency virus type 1 (HIV‐1) produced from T cells is known to incorporate Thy‐1 and other GPI‐anchored proteins into its membrane. Here, we show that aerolysin is capable of neutralizing HIV‐1 in a dose‐dependent manner and that neutralization depends upon the presence of these proteins in the viral envelope. Pretreatment with phosphatidylinositol‐specific phospholipase C to remove GPI‐anchored proteins greatly reduced HIV‐1 sensitivity to the toxin, and virus originating from a mutant cell line that lacks GPI‐anchored proteins was not neutralized. Aerolysin variants with single amino acid changes that prevent oligomerization or insertion of the toxin were unable to inactivate the virus, implying that channel formation is necessary for neutralization to occur. These findings represent the first evidence that a pathogenic human virus can be neutralized by a bacterial toxin.
DCU-Symantec at the WMT 2013 Quality Estimation Shared Task

We describe the two systems submitted by the DCU-Symantec team to Task 1.1. of the WMT 2013 Shared Task on Quality Estimation for Machine Translation. Task 1.1 involve estimating postediting effort for English-Spanish translation pairs in the news domain. The two systems use a wide variety of features, of which the most effective are the word-alignment, n-gram frequency, language model, POS-tag-based and pseudoreferences ones. Both systems perform at a similarly high level in the two tasks of scoring and ranking translations, although there is some evidence that the systems are over-fitting to the training data.
A greenfield approach to the future supply of multiple energy carriers

In this paper a model for the design of future multi-energy systems including electricity is presented. In this context a greenfield approach is applied, i.e. in a first step efficient portfolios for the supply of multiple energy carriers (e.g. electrical energy, heat, and chemical energy carriers) are calculated for a certain target year. In a second step, an optimal transition path from a portfolio given today to the desired optimal portfolio in the future is determined. The method presented in this paper is based on a single-period mean-variance portfolio model, which is adapted to be used for portfolios providing multiple energy carriers. Optimal transition paths are calculated applying a dynamic programming method that maximizes utility along the transition path. The proposed method is illustrated applying it to a combined heat and power portfolio consisting of a set of small-scale generation technologies.
Can Twitter Save Lives? A Broad-Scale Study on Visual Social Media Analytics for Public Safety

The use of social media monitoring for public safety is on the brink of commercialization and practical adoption. To close the gap between research and application, this paper presents results of a two-phase study on visual analytics of social media for public safety. For the first phase, we conducted a large field study, in which 29 practitioners from disaster response and critical infrastructure management were asked to investigate crisis intelligence tasks based on Twitter data recorded during the 2013 German Flood. To this end, the ScatterBlogs visual analytics system, a platform that provides reference implementations of tools and techniques popular in research, was given to them as an integrated toolbox. We reviewed the domain experts' individual performances with the system as well as their comments about the usefulness of techniques. In the second phase, we built on this feedback about ScatterBlogs in order to sketch out a system and create additional tools specifically adapted to the collected requirements. The performance of the old lab prototype is finally compared against the re-design in a controlled user study.
Detecting brain activations by constrained non-negative matrix factorization from task-related BOLD fMRI

Non-negative Matrix Factorization (NMF) has previously been shown to be a useful decomposition for multivariate data. In this paper, we introduce this new technique to the field of fMRI data analysis. In order to make the representation suitable for task-related brain activation detection, we imposed some additional constraints, and defined an improved contrast function. We deduced the update rules and proved the convergence of the algorithm. In the procedure, the number of factors was determined by visual assessment. We studied 8 healthy right-handed adult volunteers by a 3.0T GE Signa scanner. A block design motor paradigm (bilateral finger tapping) stimulated the blood oxygenation level-dependent (BOLD) response. Gradient Echo EPI sequence was utilized to acquire BOLD contrast functional images. With this constrained NMF (cNMF) we could obtain major activation components and the corresponding time courses, which showed high correlation with the reference function (r>0.7). The results showed that our method would be feasible for detection brain activations from task-related fMRI series.