Miracle-dz/UniFAR-FTUs huggingface dataset:
A cue-based hub-authority approach for multi-document text summarization

Multi-document extractive summarization relies on the concept of sentence centrality to identify the most important sentences in a document. Although some research has introduced the graph-based ranking algorithms such as PageRank and HITS into the text summarization, we propose a new approach under the hub-authority framework in this paper. Our approach combines the text content with some cues such as "cue phrase", "sentence length" and "first sentence" and explores the sub-topics in the multi-documents by bringing the features of these sub-topics into graph-based sentence ranking algorithms. We provide an evaluation of our method on DUC 2004 data. The results show that our approach is an effective graph-ranking schema in multi-document generic text summarization.
Finite-Element Analysis of Short-Circuit Electromagnetic Force in Power Transformer

Transient electromagnetic forces in radial and axial directions induce critical mechanical stress on windings and transformers. In this paper, short-circuit electromagnetic forces that are exerted on transformer windings are investigated. A 3-D transformer model is considered to calculate the transient electromagnetic forces. The magnetic vector potential, magnetic flux density, and electromagnetic forces due to the short-circuit transient currents applied to the power transformer are analyzed by a coupled electromechanical finite-element method. The results obtained are compared with the analytical results and show good agreement. The numerical modeling technique dealt with in this paper is expected to be useful in the design of power transformers.
Emergency landing for a quadrotor in case of a propeller failure: A PID based approach

A controller dealing with the failure of a quadrotor's motor is presented in this paper. Supposing that the failure has been already detected by the system, the quadrotor is modelled as a birotor with fixed propellers and it is controlled to follow a planned emergency landing trajectory. Theory shows that, in such a configuration, the aerial vehicle is allowed to reach any position in the Cartesian space dropping the possibility to control the yaw angle. Simulations are presented to confirm the presented methodology.
Using the web as corpus for linguistic research

In the last decade the working methods in Computational Linguistics have changed drastically. Fifteen years back, most research focused on selected example sentences. Nowadays the access to and exploitation of large text corpora is commonplace. This shift is reflected in a renaissance of work in Corpus Linguistics and documented in a number of pertinent books in recent years, e.g. the introductions by (Biber et al. 1998) and (Kennedy 1998) and the more methodologically oriented works on statistics and programming in Corpus Linguistics by (Oakes 1998) and (Mason 2000).
Neural networks controller for time-varying systems

This paper presents a new method for implementing controllers for linear time-varying systems using radial basis function neural networks. An adaptation algorithm for updating the weights of the neural network has been derived. Least mean square criterion has been used to derive the adaptation algorithm. Constraints on the magnitude and rate of change of the control signals have been considered. Simulation results are included to demonstrate the feasibility and the time-varying properties of the proposed controller.
Unit database pruning based on the cost degradation criterion for concatenative speech synthesis

A novel method of unit database pruning for concatenative speech synthesis is proposed. The proposed method uses sums of the unit preference criterion, which are calculated from cost degradation from the optimal sequence, instead of the appearance frequencies of units, which is used in the conventional method. Therefore, the proposed method is an extension of the conventional method. Since not only the optimal units but also the other candidate units can be taken into account for pruning, unit databases can be pruned with less experimental speech synthesis. The results of a unit selection experiment on 4-hour pruned unit databases built from the original 10.6-hour database indicate that the amount of the experimental speech synthesis can be reduced to 25% of that required for the conventional method without loss of the quality of synthetic speech in terms of average cost.
GrOnto: A Granular Ontology for Diversifying Search Results

Results diversification is an approach used in literature to cover the possible interpretations of the results produced by query evaluation. For diversifying search results we propose the GrOnto model. This model is based on a normalized granular view of an ontology: GrOnto allows to associate each result with the suited topical granules in order to categorize it based on the granular information.
Weakly Supervised Automatic Transcription of Mouthings for Gloss-Based Sign Language Corpora

In this work we propose a method to automatically annotate mouthings in sign language corpora, requiring no more than a simple gloss annotation and a source of weak supervision, such as automatic speech transcripts. For a long time, research on automatic recognition of sign language has focused on the manual components. However, a full understanding of sign language is not possible without exploring its remaining parameters. Mouthings provide important information to disambiguate homophones with respect to the manuals. Nevertheless most corpora for pattern recognition purposes are lacking any mouthing annotations. To our knowledge no previous work exists that automatically annotates mouthings in the context of sign language. Our method produces a frame error rate of 39% for a single signer on the alignment task.
Machine Learning Approach for Predicting The Performance of SpMV on GPU

Sparse Matrix-Vector Multiplication (SpMV) kernel dominates the computing cost in numerous scientific applications. Many implementations based on different sparse formats were proposed recently for optimizing this kernel on the GPU side. Since the performance of the SpMV varies significantly according to the sparsity characteristics of the input matrix and the hardware features, developing an accurate performance model for this kernel is a challenging task. The traditional approach of building such models by analytical modeling is difficult in practice and requires a thorough understanding of the interaction between the GPU hardware and the sparse code. In this paper, we propose to use a machine learning approach to predict the performance of the SpMV kernel using several sparse formats (COO, CSR, ELL, and HYB) on GPU. We used two popular machine learning algorithms, Support Vector Regression (SVR) and Multilayer Perceptron neural network (MLP). Our experimental results on two different GPUs (Fermi GTX 512 and Maxwell GTX 980 Ti) show that the SVR models deliver the best accuracy with average prediction error ranging between 7% and 14%. Keywords—Sparse Matrix-Vector multiplication (SpMV); GPU computing; Performance modeling; Support Vector Regression (SVR); Multilayer Perceptron (MLP).
Long-term safety and efficacy of deferasirox (Exjade®) for up to 5 years in transfusional iron-overloaded patients with sickle cell disease

To date, there is a lack of long‐term safety and efficacy data for iron chelation therapy in transfusion‐dependent patients with sickle cell disease (SCD). To evaluate the long‐term safety and efficacy of deferasirox (a once‐daily oral iron chelator), patients with SCD completing a 1‐year, Phase II, randomized, deferoxamine (DFO)‐controlled study entered a 4‐year extension, continuing to receive deferasirox, or switching from DFO to deferasirox. Average actual deferasirox dose was 19·4 ± 6·3 mg/kg per d. Of 185 patients who received at least one deferasirox dose, 33·5% completed the 5‐year study. The most common reasons for discontinuation were withdrawal of consent (23·8%), lost to follow‐up (9·2%) and adverse events (AEs) (7·6%). Investigator‐assessed drug‐related AEs were predominantly gastrointestinal [including nausea (14·6%), diarrhoea (10·8%)], mild‐to‐moderate and transient in nature. Creatinine clearance remained within the normal range throughout the study. Despite conservative initial dosing, serum ferritin levels in patients with ≥4 years deferasirox exposure significantly decreased by −591 μg/l (95% confidence intervals, −1411, −280 μg/l; P = 0·027; n = 67). Long‐term deferasirox treatment for up to 5 years had a clinically acceptable safety profile, including maintenance of normal renal function, in patients with SCD. Iron burden was substantially reduced with appropriate dosing in patients treated for at least 4 years.
Universal DDoS Mitigation Bypass

Today's commercial distributed denial of service (DDoS) mitigation technologies employ many different techniques for identifying DDoS traffic and blocking these threats. Common techniques range from basic malformed traffic checks, to traffic profiling and rate limiting, to traffic source verification and so on, with captive redirection utilizing JavaScriptor CAPTCHA-based authentications being the most effective by far. However, in our research weaknesses were found in a majority of these sort of techniques. We rolled all our exploits into a proof-of-concept attack tool, giving it near-perfect DDoS mitigation bypass capability against almost every existing commercial DDoS mitigation solutions. The ramifications are huge. For the vast majority of web sites, these mitigation solutions stand as the last line of defense. Breaching this defense can expose these web sites' backend to devastating damages. We have extensively surveyed DDoS mitigation technologies available on the market today, uncovering the countermeasure techniques they employ, how they work, and how to defeat each of them. Essentially, bypass is achieved through emulating legitimate traffic characteristics. Afterwards, our attack tool is introduced to demonstrate how all these exploits can be brought together to execute a "combo attack" to bypass all layers of protection in order to gain access to the backend. The effectiveness of this tool is illustrated via testing results against specific DDoS mitigation products and popular web sites known to be protected by specific technologies. To conclude our research, a next-gen mitigation technique is also proposed as a countermeasure against our attack methodology.
ECG segmentation and P-wave feature extraction: application to patients prone to atrial fibrillation

Presents an automatic analysis method of the P-wave, based on lead II of a 12 lead standard ECG, which will be applied to the detection of patients prone to atrial fibrillation (AF), one of the most frequent arrhythmias. It focuses first on the segmentation of the electrocardiogram P-wave, which is performed in two steps: first, detection of the QRS complexes, then association of a wavelet analysis method and a bidden Markov model to represent one beat of the signal. After segmentation, the P-wave is isolated and a set of parameters, which have the ability to detect patients prone to AF, is calculated from it. The detection efficiency is validated on an ECG database of 145 patients including a control group and a study group with documented AF. A discriminant analysis is applied and the results obtained show a specificity and a sensitivity between 65% and 70%.
Weasels, Hedges and Peacocks: Discourse-level Uncertainty in Wikipedia Articles

Uncertainty is an important linguistic phenomenon that is relevant in many areas of language processing. While earlier research mostly concentrated on the semantic aspects of uncertainty, here we focus on discourse- and pragmaticsrelated aspects of uncertainty. We present a classification of such linguistic phenomena and introduce a corpus of Wikipedia articles in which the presented types of discourse-level uncertainty ‐ weasel, hedge and peacock ‐ have been manually annotated. We also discuss some experimental results on discourse-level uncertainty detection.
Precise quantification of mixtures of bispecific IgG produced in single host cells by liquid chromatography-Orbitrap high-resolution mass spectrometry

ABSTRACT Bispecific IgG are heterotetramers comprising 2 pairs of heavy and light chains. Co-expression of the 4 component chains in a single host cell typically yields the desired bispecific IgG plus up to 9 additional incorrect chain pairings. Several protein engineering strategies have been reported to facilitate the heterodimerization of antibody heavy chains or cognate pairing of antibody heavy and light chains. These technologies have been used to direct the efficient assembly of bispecific IgG in single host cells and minimize unwanted chain pairings. When purifying bispecific IgGs, the identification and quantification of low levels of closely related IgG contaminants are substantial analytical challenges. Here we have developed a robust high-throughput method for quantitative analysis of bispecific IgG preparations using novel online liquid chromatography in conjunction with an extended mass range Orbitrap-based high-resolution mass spectrometer. A mathematical method was developed to estimate the yields of the 2 isobaric species, namely the desired bispecific IgG and the light chain-scrambled IgG. The analytical methods described herein are anticipated to be broadly applicable to the development of bispecific IgG as drugs and potentially to other complex next-generation biotherapeutics.
Fast X-Ray Transients and Gamma-Ray Bursts: Constraints on Beaming

The detection of X-ray afterglows of γ-ray burst (GRB) sources has enabled the optical discovery that GRBs are at cosmological distances, which confirms that the enormous luminosities required must produce a relativistically expanding fireball. It is not yet clear whether this expansion is quasi-spherical or beamed, or if the beaming differs between the prompt GRB and afterglow, although the differences for both source emission and population models are profound. We show that relative beaming (prompt vs. afterglow) may be constrained by analysis of the "fast transient" X-ray sources cataloged by Pye & McHardy from the Ariel 5 survey as well as several other surveys (e.g., HEAO 1 experiments A-1/A-2). After removing contamination from likely stellar transients, and scaling from X-ray/γ-ray fluence ratios recently derived from Ginga and BeppoSAX, approximately half of the sources were possible prompt emission or afterglows from GRBs with γ-ray fluence of ≳1.2 × 10−5 ergs cm−2. Since the rate of these candidate afterglow events, 0.15 day−1, is consistent with the BATSE log N-log S distribution, no difference in prompt versus afterglow beaming is required. However, more sensitive X-ray monitors or hard X-ray imaging surveys, with better temporal and spatial resolution, could provide strong constraints on GRBs and beaming.
Testing the Continuum of Delusional Beliefs

A key problem in studying a hypothesized spectrum of severity of delusional ideation is determining that ideas are unfounded. The first objective was to use virtual reality to validate groups of individuals with low, moderate, and high levels of unfounded persecutory ideation. The second objective was to investigate, drawing upon a cognitive model of persecutory delusions, whether clinical and nonclinical paranoia are associated with similar causal factors. Three groups (low paranoia, high nonclinical paranoia, persecutory delusions) of 30 participants were recruited. Levels of paranoia were tested using virtual reality. The groups were compared on assessments of anxiety, worry, interpersonal sensitivity, depression, anomalous perceptual experiences, reasoning, and history of traumatic events. Virtual reality was found to cause no side effects. Persecutory ideation in virtual reality significantly differed across the groups. For the clear majority of the theoretical factors there were dose–response relationships with levels of paranoia. This is consistent with the idea of a spectrum of paranoia in the general population. Persecutory ideation is clearly present outside of clinical groups and there is consistency across the paranoia spectrum in associations with important theoretical variables.
Transnational standard setting in accounting: Organizing expertise-based self-regulation in times of crises

Purpose - – The last four decades have seen the rise of the International Accounting Standards Board (IASB) as the core locus of transnational accounting regulation. Initial steps of associational cooperation were superseded by establishing a standard setting organization that heavily draws on consultation procedures. The purpose of this paper is to focus on recent changes in governance and accountability of IASB in the aftermath of the financial crisis. Emphasis is given to the organizational configuration, the ambivalence of consultation procedures and reactions to mounting criticism after the crisis. The paper proposes that IASB is the heart of a new transnational regulatory constellation in accounting. Design/methodology/approach - – The material and analysis presented in the paper derives from an extensive review of official reports, consultation documents and related responses and a range of additional information available on IASB's web page. Findings - – The paper analyzes how IASB uses legitimation strategies to defend its position as a transnational standard setter. From analysis of recent changes, the paper reveals a growing reliance on – and domination through – consultation procedures. The paper also shows the IASB’S swift action to counter substantial criticism emerging with the financial crisis. Practical implications - – By highlighting developments surrounding IASB, its governance structure and the emphasis on consultation, the paper establishes the importance for public policy of further study and debate the operation of IASB. It could also contribute to re-politicize accounting regulation at the transnational level. Originality/value - – IASB is an integral player in global financial governance processes and is only recently receiving substantial academic accounting research. This paper seeks to provide an introduction and critical account of the organization's development.
Analysis of the activation routes induced by different metal oxide nanoparticles on human lung epithelial cells

Nanoparticles (Nps) can induce toxicity in the lung by accidental or intentional exposure. The main objective of the study reported here was to characterize the effect that four metal oxide Nps (CeO2, TiO2, Al2O3 and ZnO) had at the cellular level on a human lung epithelial cell line. This goal was achieved by studying the capacity of the Nps to activate the main mitogen-activated protein kinases (MAPKs) and the nuclear factor NFκB. Only ZnO Nps were able to activate all of the MAPKs and the release of Zn2+ ions was the main cause of activation. ZnO and Al2O3 Nps activated the NFκB pathway and induced the release of inflammatory cytokines. CeO2 and TiO2 Nps were found to have safer profiles. The graphical abstract was obtained using Servier Medical Art.
Analysis of the relationship between urbanisation and energy consumption in China

Energy consumption increases with urbanisation. This paper developed evaluation indicators and calculations for energy consumption changes, and advances a new indicator, Energy Consumption Unit Geometric Average (ECUGA) elasticity coefficient and its calculation. The ECUGA elasticity coefficient can explore energy consumption changes and make comparisons among countries at different urbanisation stages. The general trend of energy consumption changes is summarised at different urbanisation stages based on values for 45 countries. For China, the ECUGA elasticity coefficient first increases and then decreases, with the peak of urbanisation at 40% to 50%. China's ECUGA elasticity coefficient for 1978–2005 and 2010–2050 differed from the general trend, with a decrease until urbanisation reached 40%, followed by a rapid increase at 40% to 50%, and then a decrease from 50% to 80%. Although the increase and decrease of China's ECUGA elasticity coefficient is faster than in other countries, the values are always lower than the average for these countries at corresponding urbanisation stages.
Stance Postural Strategies in Patients with Chronic Inflammatory Demyelinating Polyradiculoneuropathy

Introduction Polyneuropathy leads to postural instability and an increased risk of falling. We investigated how impaired motor impairment and proprioceptive input due to neuropathy influences postural strategies. Methods Platformless bisegmental posturography data were recorded in healthy subjects and patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP). Each subject stood on the floor, wore a head and a hip electromagnetic tracker. Sway amplitude and velocity were recorded and the mean direction difference (MDD) in the velocity vector between trackers was calculated as a flexibility index. Results Head and hip postural sway increased more in patients with CIDP than in healthy controls. MDD values reflecting hip strategies also increased more in patients than in controls. In the eyes closed condition MDD values in healthy subjects decreased but in patients remained unchanged. Discussion Sensori-motor impairment changes the balance between postural strategies that patients adopt to maintain upright quiet stance. Motor impairment leads to hip postural strategy overweight (eyes open), and prevents strategy re-balancing when the sensory context predominantly relies on proprioceptive input (eyes closed).
Impact of Serial Scaling of Multi-threaded Programs in Many-Core Era

Estimating the potential performance of parallel applications on the yet-to-be-designed future many cores is very speculative. The traditional laws used to predict performance of an application do not reflect on the various scaling behaviour of a multi-threaded (MT) application leading to optimistic estimation of performance in many core era. In this paper, we study the scaling behavior of MT applications as a function of input workload size and the number of cores. For some MT applications in the benchmark suites we analysed, our study shows that the serial fraction in the program increases with input workload size and can be a scalability-limiting factor. Similar to previous studies [5], we find that using a powerful core (heterogeneous architecture) to execute this serial part of the program can mitigate the impact of serial scaling and improve the overall performance of an application in many-core era.
Combining the tunneling and anomaly phenomena in deriving the gravitational anomaly

In the present work we have derived the gravitational anomaly from a fundamentally different perspective: it emerges due to the tunneling of particles (in the present case fermions) across the black hole horizon. The latter effect is in fact the Hawking radiation. We have used the analogy of an early idea17,18 of visualizing chiral gauge anomaly as an effect of spectral flow of the energy levels, from the negative energy Dirac sea, across zero energy level in the presence of gauge interactions. This was extended to conformal anomaly in Ref. 23. In the present work, we exploit the latter formalism in black hole physics where we interpret crossing the horizon of black hole (the zero energy level) as a spectral flow since it is also accompanied by a change of sign in the energy of the particle. Furthermore, Hawking radiation induces a shrinking of the radius of the horizon15,16 which reminds us of a similar rearrangement in the Fermi level generated by the spectral flow.17,18,21 Hence in our formulation the negative energy states below horizon play a similar role as the Dirac sea. We successfully recover the gravitational anomaly.