Miracle-dz/UniFAR-FTUs huggingface dataset:
Symbolic Machine Learning: A Different Answer to the Problem of the Acquisition of Lexical Knowledge from Corpora

One relevant way to structure the domain of lexical knowledge (e.g. relations between lexical units) acquisition from corpora is to oppose numerical versus symbolic techniques. Numerical approaches of acquisition exploit the frequential aspect of data, have been widely used, and produce portable systems, but poor explanations of their results. Symbolic approaches exploit the structural aspect of data. Among them, the symbolic machine learning (ML) techniques can infer efficient and expressive patterns of a target relation from examples of elements that verify this relation. These methods are however far less known, and the aim of this paper is to point out their interest through the description of one precise experiment. To remove their supervised characteristic, and instead of opposing them to numerical approaches, we finally show that it is possible to combine one symbolic ML technique to one numerical one, and keep advantages of both (meaningful patterns, efficient extraction, portability).
A spatio-temporal model for spontaneous thrombus formation in cerebral aneurysms

We propose a new numerical model to describe thrombus formation in cerebral aneurysms. This model combines CFD simulations with a set of bio-mechanical processes identified as being the most important to describe the phenomena at a large space and time scales. The hypotheses of the model are based on in vitro experiments and clinical observations. We document that we can reproduce very well the shape and volume of patient specific thrombus segmented in giant aneurysms.
Earnings Differentials and Returns to Education in China, 1995-2008

This paper estimates the returns to education of rural-urban migrants during the period of transition of China's economy between 1995 and 2008. Using data from CHIP and RUMiC, we find that rural migrants' earning differentials with urban residents are substantial and mainly depend on the type of occupation, industry, and employers' ownership, rather than the level of education completed. Returns to formal schooling for migrants remained stable at approximately 3% and 5% throughout the period, and differences across quantiles are generally statistically insignificant. Increasing gaps in the return to schooling by gender have instead emerged. These results raise questions about the incentives to invest in human capital for rural migrants and for the governments funding education in emigration regions.
Fake News as a Floating Signifier: Hegemony, Antagonism and the Politics of Falsehood

“Fake news” has emerged as a global buzzword. While prominent media outlets, such as The New York Times, CNN, and Buzzfeed News, have used the term to designate misleading information spread online, President Donald Trump has used the term as a negative designation of these very “mainstream media. ” In this article, we argue that the concept of “fake news” has become an important component in contemporary political struggles. We showcase how the term is utilised by different positions within the social space as means of discrediting, attacking and delegitimising political opponents. Excavating three central moments within the construction of “fake news,” we argue that the term has increasingly become a “floating signifier”: a signifier lodged in-between different hegemonic projects seeking to provide an image of how society is and ought to be structured. By approaching “fake news” from the viewpoint of discourse theory, the paper reframes the current stakes of the debate and contributes with new insights into the function and consequences of “fake news” as a novel political category.
Predictive Display from Computer Vision Models

In tele-manipulation, delays as small as a few tenths of a second can affect performance. Robot operators dissociate their control actions with what they see on delayed video and have to adopt slow move-and-wait strategies or may completely fail to perform high precision tasks. Predictive Display (PD) mitigates this problem by rendering visual feedback that reflects the operator’s motion immediately. Conventional PD is based on a-priori CAD models and calibrations. Using modern computer vision, we have implemented on-line model capture and tracking which allows the rendering of textured graphical PD. We validate different types of PD and compare them to using delayed video in an alignment task. Graphical PD was found comparable to a no-delay situation, while task completion on average took 48% longer with a relatively short 300 ms delay.
A Study on Relationship between Modularity and Diffusion Dynamics in Networks from Spectral Analysis Perspective

Modular structure is a typical structure that is observed in most of real networks. Diffusion dynamics in network is getting much attention because of dramatic increasing of the data flows via the www. The diffusion dynamics in network have been well analysed as probabilistic process, but the proposed frameworks still shows the difference from the real observations. In this paper, we analysed spectral properties of the networks and diffusion dynamics. Especially, we focus on studying the relationship between modularity and diffusion dynamics. Our analysis as well as simulation results show that the relative influences from the non-largest eigenvalues and the corresponding eigenvectors increase when modularity of network increases. These results have the implication that, although network dynamics have been often analysed with the approximation manner utilizing only the largest eigenvalue, the consideration of the other eigenvalues is necessary for the analysis of the network dynamics on real networks. We also investigated Node-level Eigenvalue Influence Index (NEII) which can quantify the relative influence from each eigenvalues on each node. This investigation indicates that the influence from each eigenvalue is confined within the modular structures in the network. These findings should be made consideration by researchers interested in diffusion dynamics analysis on real networks for deeper analysis.
Cloning speakers' articulation, shape and appearance

We briefly describe here the methodology we have developed at GIPSA for cloning speakers, i.e. capturing and m odeling speaker-specific control, shape and appearance models. We will mention here evaluation experiments that have been conducted to assess the perceptual benefit of visua l synthesis used in three different applications: lipsync/text- toaudiovisual synthesis, audiovisual conversion and t ongue reading.
Subgroups based on thermal and pressure pain thresholds in women with chronic whiplash display differences in clinical presentation – an explorative study

Purpose To investigate the presence of subgroups in chronic whiplash-associated disorders (WAD) based on pain thresholds for pressure (PPT), cold (CPT), and heat (HPT) and to compare these subgroups with respect to symptomatology, disability, and health aspects. Methods Two groups of female subjects – patients with chronic WAD (n = 28) and healthy controls (CON; n = 29) – were investigated. Quantitative sensory testing (QST) for thermal thresholds and algometry for PPT at four sites in the body (over the trapezius and tibialis anterior bilaterally) were determined. Habitual pain intensities, psychological strain, disability, and health aspects were registered using a questionnaire. Results A cluster analysis based on PPT, CPT, and HPT identified two subgroups of chronic WAD: one sensitive subgroup (s-WAD; n = 21), and one less sensitive subgroup (ls-WAD; n = 6). S-WAD displayed widespread hyperalgesia, whereas ls-WAD had localized hyperalgesia in the neck area, with tendencies to supernormal values in remote areas of the body. Generally, s-WAD had a significantly worse situation than the CON with respect to symptomatology, disability, and health aspects. The ls-WAD group was intermediary between s-WAD and CON in these aspects. Conclusion Different explanations, eg, severity of the pain condition per se, etiological factors, and pre-trauma differences in pain sensitivity, may exist for the differences in pain thresholds between the two subgroups. Future research should investigate the role of pain thresholds in the chronic stage to determine the efficacy of treatment interventions.
Continental break-up history of a deep magma-poor margin based on seismic reflection data (northeastern Gulf of Aden margin, offshore Oman)

Rifting between Arabia and Somalia started around 35 Ma followed by spreading at 17.6 Ma in the eastern part of the Gulf of Aden. The first-order segment between Alula-Fartak and Socotra-Hadbeen fracture zones is divided into three second-order segments with different structure and morphology. Seismic reflection data were collected during the Encens Cruise in 2006 on the northeastern margin. In this study, we present the results of Pre-Stack Depth Migration of the multichannel seismic data from the western segment, which allows us to propose a tectono-stratigraphic model of the evolution of this segment of the margin from rifting to the present day. The chronological interpretation of the sedimentary sequences is mapped out within relation to the onshore observations and existing dating. After a major development of syn-rift grabens and horsts, the deformation localized where the crust is the thinnest. This deformation occurred in the distal margin graben (DIM) at the northern boundary of the ocean-continent transition (OCT) represented by the OCT ridge. At the onset of the OCT formation differential uplift induced a submarine landslide on top of the deepest tilted block and the crustal deformation was restricted to the southern part of the DIM graben, where the continental break-up finally occurred. Initial seafloor spreading was followed by post-rift magmatic events (flows, sills and volcano-sedimentary wedge), whose timing is constrained by the analysis of the sedimentary cover of the OCT ridge, correlated with onshore stratigraphy. The OCT ridge may represent exhumed serpentinized mantle intruded by post-rift magmatic material, which modified the OCT after its emplacement.
Improving Context and Category Matching for Entity Search

Entity search is to retrieve a ranked list of named entities of target types to a given query. In this paper, we propose an approach of entity search by formalizing both context matching and category matching. In addition, we propose a result re-ranking strategy that can be easily adapted to achieve a hybrid of two context matching strategies. Experiments on the INEX 2009 entity ranking task show that the proposed approach achieves a significant improvement of the entity search performance (xinfAP from 0.27 to 0.39) over the existing solutions.
On the algebra of order extended abstract

Algebras whose carriers are partially ordered sets and operations are monotone and algebras whose carriers are complete partial orders and operations are continuous are studied. A quotient construction is provided for both types of algebras. The notion of a variety of algebras is defined and it is shown that the analogue of Birkhoff variety theorem holds for ordered algebras but not for continuous algebras. The results presented are a good first step towards a theory of ordered data types and a study of families of interpretations of schemas.
Inflammation Mediated Metastasis: Immune Induced Epithelial-To-Mesenchymal Transition in Inflammatory Breast Cancer Cells

Inflammatory breast cancer (IBC) is the most insidious form of locally advanced breast cancer; about a third of patients have distant metastasis at initial staging. Emerging evidence suggests that host factors in the tumor microenvironment may interact with underlying IBC cells to make them aggressive. It is unknown whether immune cells associated to the IBC microenvironment play a role in this scenario to transiently promote epithelial to mesenchymal transition (EMT) in these cells. We hypothesized that soluble factors secreted by activated immune cells can induce an EMT in IBC and thus promote metastasis. In a pilot study of 16 breast cancer patients, TNF-α production by peripheral blood T cells was correlated with the detection of circulating tumor cells expressing EMT markers. In a variety of IBC model cell lines, soluble factors from activated T cells induced expression of EMT-related genes, including FN1, VIM, TGM2, ZEB1. Interestingly, although IBC cells exhibited increased invasion and migration following exposure to immune factors, the expression of E-cadherin (CDH1), a cell adhesion molecule, increased uniquely in IBC cell lines but not in non-IBC cell lines. A combination of TNF-α, IL-6, and TGF-β was able to recapitulate EMT induction in IBC, and conditioned media preloaded with neutralizing antibodies against these factors exhibited decreased EMT. These data suggest that release of cytokines by activated immune cells may contribute to the aggressiveness of IBC and highlight these factors as potential target mediators of immune-IBC interaction.
Bridging the Gap between Global Routing and Detailed Routing: A Practical Congestion Model

To capture detailed routing congestion factors in sub-90nm technology nodes, we propose a practical congestion model embedded in 3-D global routing grid graph. Using a concept of pass-through capacity and demand, intra-gcell congestion contributed by fat vias, stacked vias, local nets and related design rules can be measured and optimized. Proposed congestion model is compatible with existing widely-used path search algorithms in global routing. Experimental results validate proposed model, and demonstrate that 42% less design rule violations and 46% shorter full-flow routing runtime, as well as 3% shorter wire length and 4% less via count in detailed routing results can be achieved using proposed congestion model in global routing stage.
Delay-Dependent Robust Stabilization for Uncertain Time-Delay Systems

The problem of delay-dependent robust stabilization for uncertain system with time-delay is considered. By means of the Lyapunov function and linear matrix inequalities (LMIs) technique, a delay-dependent sufficient condition is derived for the existence of a state feedback controller, which ensures asymptotic stability of the closed system for all admissible uncertainties. Unlike previous methods, the mathematical development avoids system transforming and bounding certain cross terms which often lead to conservatism. In terms of the solutions of LMIs, the robust stabilization controller is presented. Finally, an illustrative example is given to demonstrate the effectiveness of proposed method
Ionization-induced star formation - II. External irradiation of a turbulent molecular cloud

In this paper, we examine numerically the difference between triggered and revealed star formation. We present smoothed particle hydrodynamic (SPH) simulations of the impact on a turbulent 104 M⊙ molecular cloud of irradiation by an external source of ionizing photons. In particular, using a control model, we investigate the triggering of star formation within the cloud. We find that, although feedback has a dramatic effect on the morphology of our model cloud, its impact on star formation is relatively minor. We show that external irradiation has both positive and negative effects, accelerating the formation of some objects, delaying the formation of others and inducing the formation of some that would not otherwise have formed. Overall, the calculation in which feedback is included forms nearly twice as many objects over a period of ∼0.5 freefall times (∼2.4 Myr), resulting in a star formation efficiency approximately one-third higher (∼4 per cent as opposed to ∼3 per cent at this epoch) as in the control run in which feedback is absent. Unfortunately, there appear to be no observable characteristics which could be used to differentiate objects whose formation was triggered from those which were forming anyway and which were simply revealed by the effects of radiation, although this could be an effect of poor statistics.
Knowledge Extraction from RDF Data with Activation Patterns

RDF data can be analyzed with various query languages such as SPARQL. However, due to their nature these query languages do not support fuzzy queries that would allow us to extract a broad range of additional information. In this article we present a new method that transforms the information presented by subject-relationobject relations within RDF data into Activation Patterns. These patterns represent a common model that is the basis for a number of sophisticated analysis methods such as semantic relation analysis, semantic search queries, unsupervised clustering, supervised learning or anomaly detection. In this article, we explain the Activation Patterns concept and apply it to an RDF representation of the well known CIA World Factbook.
Cache‐Efficient Layouts of Bounding Volume Hierarchies

We present a novel algorithm to compute cache‐efficient layouts of bounding volume hierarchies (BVHs) of polygonal models. Our approach does not make any assumptions about the cache parameters or block sizes of the memory hierarchy. We introduce a new probabilistic model to predict the runtime access patterns of a BVH. Our layout computation algorithm utilizes parent‐child and spatial localities between the accessed nodes to reduce both the number of cache misses and the size of the working set. Our algorithm also works well for spatial partitioning hierarchies including kd‐trees. We use our algorithm to compute layouts of BVHs and spatial partitioning hierarchies of large models composed of millions of triangles. We compare our cache‐efficient layouts with other layouts in the context of collision detection and ray tracing. In our benchmarks, our layouts consistently show better performance over other layouts and improve the performance of these applications by 26%–300%without any modification of the underlying algorithms or runtime applications.
An Efficient Power-Aware Optimization for Task Scheduling on NoC-based Many-core System

With the development of the semiconductor industry, more processors can be integrated onto a single chip. Network-on-Chip (NoC) is an efficient solution for the interconnections on chip for many-core system with many processor cores on chip. However, enhancing performance with lower power consumption is still a challenge. The core issue is the mapping of applications to NoC. A common method is to find processes with high communication with each other and map them to neighborhoods. Thus, they can reduce the communication distance and avoid unnecessary energy cost. This work proposed an online scheduling method, which aims at the optimization of task scheduling algorithm with low communication energy consumption. The communication status of applications at run time is analyzed first. Then, the algorithm will compute the mapping method dynamically and implement the real-time scheduling online. Experimental results based on simulation show that the algorithm proposed in this review can achieve more than 30% communication energy saving with low complexity.
e - Document retrieval using rough-set theory

With the growing use of networked solutions and services in the Information Society, many citizen-oriented services are planned not only in utility or e-governance sectors, but also in other information-centric human applications. Conventional DBMS may have either two-tier or three-tier client/server architecture [19]. These are already being used on the Internet. Web Applications provide Network Interfaces to access information stored in one or more databases. The generic method of organizing and formatting these Network Interfaces is through the hyperlink documents, which are coded in languages like HTML or XML [3]. Further, the proliferation of Data Mining and Data Warehousing practices has necessitated the need for efficient e-Document retrieval, creating a requirement for robust Information Retrieval (IR) systems. In this paper we show that rough-set theory characterizes new and interesting viewpoint for electronics document (e-Documents) retrievals. We explore the characteristics of an e-Document and applicability of rough-set theory in detail.
Adenovirus-mediated transfer of the CFTR gene to lung of nonhuman primates: biological efficacy study.

We have evaluated the biological efficacy of E1-deleted adenoviruses in baboons for lung-directed gene therapy of cystic fibrosis (CF). The experimental design attempted to simulate a phase I clinical trial with animals receiving a single dose of virus to an isolated pulmonary segment. A total of 14 animals divided into four groups, each of which received escalating doses of virus, were used. Individual animals were necropsied 4 and 21 days after gene transfer and tissues were carefully surveyed for gene expression. Expression of the transgene was localized primarily to the area into which it was infused; the efficiency of recombinant gene expression and the abundance of transgene sequences were proportional to dose and both diminished with time. Transgene expression was found predominantly in alveolar cells with patches of expression in the proximal and distal airway. Analysis of adenoviral protein expression within transgene-expressing cells revealed infrequent expression of the E2a gene and no detectable expression of late genes (i.e., fiber protein). These results suggest that recombinant adenovirus can be used to transfer genes efficiently to the lung of nonhuman primates and that therapeutic strategies of cystic fibrosis may require repetitive administration with current vectors.
Applying Graph Databases to Cloud Management: An Exploration

Graph databases have become increasingly popular for a variety of uses ranging from modeling online code repositories to tracking software engineering dependencies. These areas use graph databases because many of their problems can be expressed in terms of graph traversals. Recent work has applied graph databases to virtualization management, noting that many IT questions can also be expressed as graph traversals. In this paper, we study another area in which graphs are valuable: reporting and auditing in cloud infrastructure. We first examine cloud infrastructure and map its data model to a graph. Building upon this model, we recast a number of reporting queries in terms of graph traversals. We then modify the model both for performance and for accommodating additional use cases related to cloud computing, including migration from private to hybrid clouds. Our results show that while a graph backend makes it straightforward to formulate certain kinds of queries, a naive mapping of graphs to a graph database can result in poor performance. Utilizing knowledge of the problem domain and restructuring the graph can provide dramatic gains in performance and make a graph database feasible for such queries.
The Key Technology Research of Intelligent Information Syndication

With the development of network, the online information has greatly enriched. It is increasingly difficult to obtain the desired information. The search engine can solve some problems, but far from satisfying people's needs. With the development of Web 2.0, RSS technology can solve some problems, greatly reducing spam, but as more and more channels appear, the user once again gets into the "information overload" situation. Therefore, in this paper, we use machine learning techniques and effective text classification techniques to solve the problem of information overload in a certain extent.