Miracle-dz/UniFAR-FTUs huggingface dataset:
Selective Sharing for Multilingual Dependency Parsing

We present a novel algorithm for multilingual dependency parsing that uses annotations from a diverse set of source languages to parse a new unannotated language. Our motivation is to broaden the advantages of multilingual learning to languages that exhibit significant differences from existing resource-rich languages. The algorithm learns which aspects of the source languages are relevant for the target language and ties model parameters accordingly. The model factorizes the process of generating a dependency tree into two steps: selection of syntactic dependents and their ordering. Being largely language-universal, the selection component is learned in a supervised fashion from all the training languages. In contrast, the ordering decisions are only influenced by languages with similar properties. We systematically model this cross-lingual sharing using typological features. In our experiments, the model consistently outperforms a state-of-the-art multi-lingual parser. The largest improvement is achieved on the non Indo-European languages yielding a gain of 14.4%.
Country-level correlates of cervical cancer mortality in Latin America and the Caribbean.

OBJECTIVE To identify country-level correlates of geographical variations in cervical cancer (CC) mortality in Latin America and the Caribbean (LAC). MATERIALS AND METHODS CC mortality rates for LAC countries (n=26) were examined in relation to country-specific socio-economic indicators (n=58) and Human Papilloma Virus (HPV) prevalence using linear regression models. RESULTS High mortality at ages <5 years, low per capita total expenditure on health, and low proportion of the population with access to sanitation were identified as the best independent predictors of CC mortality (R² =77%). In the subset of countries (n=10) with HPV prevalence estimates, these socio-economic indicators together with high-risk HPV prevalence explained almost all the between-country variability in CC mortality (R² =98%). CONCLUSION The findings suggest that continuing socioeconomic improvements in LAC countries will be associated with further reductions in CC mortality even in the absence of organised population-based screening and vaccination programmes.
[Effect of Pulsed Electromagnetic Fields on Osteogenic Differentiation and Wnt/β-catenin Signaling Pathway in Rat Bone Marrow Mesenchymal Stem Cells].

OBJECTIVE To investigate the effect of pulsed electromagnetic tields (FEMFs) on osteogemc differentiation and Wnt/β-catenin signaling pathway in rat bone marrow mesenchymal stem cells (BMSCs). METHODS Rat BMSCs were isolated and the passage 3 cells were divided into 3 groups. Cells were cultured in LG-DMEM complete medium for 1 d to ensure fully adherent. Then, change the medium. Cells were maintained in complete medium (Control group) or in osteo-induction medium (OM group). The cells in PEMFs group were cultured in complete medium and exposed to 8 Hz, 3. 8 mT PEMF stimulation for 40 min/d. The intervention lasted for 21 d. Cell proliferation activity was determined by using MTT. The effects of PEMF onosteogenic differentiation were assessed by ALP and Alizarin Red S staining. Various osteoblast-relevant genes and genes of Wnt/β-catenin signaling were analyzed by quantitative real-time RT-PCR. RESULTS We. found that OM could significantly promote the proliferation of BMSC at 7 d, 14 d, 21 d (P<0. 05), but the effect was not obviously found in PEMFs group. For osteogenic differentiation, the positive rates of ALP or Alizarin Red S staining were detected higher in PEMFs/ OM group (P < 0. 05). Quantitative RT-PCR revealed PEMFs or OM could increase mRNA levels of Wnt1, Wnt3a, LRP5, β-catenin, BMP-2, Runx2, ALP, OC at special time point (P<0. 05). Compared to OM group, PEMFs have a lower expression in each detection, but the trends were consistent. CONCLUSION PEMFs (8 Hz, 3. 8 mT) could induce the osteogenic differentiation of rat BMSCs via activating Wnt/β-catenin signaling pathway.
Securing Communication in a Peer-to-Peer Messaging Middleware

Traditionally, message oriented middlewares (MOM) are looked upon as either centralized systems (e.g. AMQP) or a rigidly distributed collection of machines, requiring significant configuration overhead for achieving the desired throughput under the needed security constraints. On the other end of the spectrum, peer-to-peer systems (P2P) in general achieve amazing scalability and fault tolerance, but due to their very nature, are susceptible to various attacks. Since all measures of security have considerable consequences on the system's capabilities, the securing of a peer-to-peer system requires a thorough analysis on the exact designated use-case and environment in which the network is required to operate in, as well as all the possible threats the system must be able to withstand. The paper proposes a security model that bridges the distribution concept of peer-to-peer systems with the necessities of MOMs by rigorously defining the operational environment, assumptions and requirements, on top of which a security protocol was implemented. Taking advantage of the specific use case of P2P MOMs, further optimizations are provided which provide the same security against the defined threat model, but result in significant gains with regard to the overall switching throughput of the network.
Inhibition of IgE Activity to Bind its High Affinity Receptor (FcεRIα) by Mouse Anti-IgE Cε3∼4 Monoclonal Antibody (QME5)

Using computer-guided homology modeling method, the 3-D structure of the Fv fragment of a functional anti-IgE antibody (MAE11) was constructed and the spatial structure of E24-MAE11 complex was modeled based on the crystal structure of IgE-Fc (abbr. E24) and molecular docking method. Then the identified epitope of IgE was determined theoretically, which showed the key role of IgE-Cɛ3 in interacting with both FcɛRIα and MAE11. By normal protocols, we immunized mice with purified protein E34 and screened six anti-E34 monoclonal antibodies. Purified antibodies could identify E34 by Western blot; furthermore, all of them could bind IgE by ELISA, in which QME5 seemed to be the best. Flow cytometry analysis displayed that only QME5 could bind membrane IgE and it could compete with membrane FcɛRIα to bind soluble IgE. Meanwhile, QME5 couldn’t bind FcɛRIα-attached IgE, which suggested no hypersensitivity in triggering the target cells (mast cells or basophils) by crosslinking or inducing the release of a variety of chemical mediators.
Hemostasis, Thrombosis, and Vascular Biology

A novel genetic leukocyte adhesion deficiency in subsecond triggering of integrin avidity by endothelial chemokines results in impaired leukocyte arrest on vascular endothelium under shear flow Leukocyte arrest on vascular endothe-lium under disruptive shear flow is a multistep process that requires in situ integrin activation on the leukocyte surface by endothelium-displayed chemoat-tractants, primarily chemokines. A genetic deficiency of leukocyte adhesion to endothelium associated with defective ␤2 integrin expression or function (LAD-1) has been described. We now report a novel severe genetic disorder in this mul-tistep process associated with functional defects in multiple leukocyte integrins, reflected in recurrent infections, profound leukocytosis, and a bleeding tendency. This syndrome is associated with an impaired ability of neutrophil and lym-phocyte ␤1 and ␤2 integrins to generate high avidity to their endothelial ligands and arrest cells on vascular endothelium in response to endothelial chemoattrac-tant signals. Patient leukocytes roll normally on endothelial selectins, express intact integrins and G protein–coupled chemokine receptors (GPCR), spread on integrin ligands, and migrate normally along a chemotactic gradient. Activation of ␤2 integrins in response to GPCR signals and intrinsic soluble ligand binding properties of the very late activation antigen-4 (VLA-4) integrin are also retained in patient leukocytes. Nevertheless , all integrins fail to generate firm adhesion to immobilized ligands in response to in situ GPCR-mediated activation by chemokines or chemoattractants, a result of a primary defect in integrin rearrangement at ligand-bearing contacts. This syndrome is the first example of a human integrin-activation deficiency associated with defective GPCR stimulation of integrin avidity at subsecond contacts , a key step in leukocyte arrest on vascular endothelium under shear flow.
A multi-agent based system with big data processing for enhanced supply chain agility

Purpose Decision support systems are becoming an indispensable tool for managing complex supply chains. The purpose of this paper is to develop a multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored. Design/methodology/approach For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled. Findings Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility. Research limitations/implications The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems. Practical implications The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis. Originality/value A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.
Gram: a graph data model and query languages

We present a model for data organized as graphs. Regular expressions over the types of the node and edge labels are used to qualify connected subgraphs. An algebraic language based on these regular expressions and supporting a restricted form of recursion is introduced. A natural application of this model and its query language is hypertext querying.
Nanoscale elastic–plastic deformation in clay-reinforced nanostructured materials: The response of phase and structural morphology

The study described here combines materials science and engineering and mathematical analysis to fundamentally obtain insights underlying nanoscale deformation in polymer nanocomposites. The objective was achieved by examining the surface deformation response of two polymer nanocomposite systems with significant differences in ductility during scratching with a nanoindenter. The model host systems are a ductile polyethylene and a less ductile polypropylene. The model reinforcement material is nanoclay. The two systems are unique nanostructured materials because the distance between the individual clay layers is comparable to their thickness and also to the polymer segments. Thus, it is a morphology that is truly dominated by nanoscale features. Furthermore, we have used pressure-induced crystallization approach to alter the structure of the investigated two systems and study nanoscale surface deformation response. Our hypothesis is that the susceptibility to scratch deformation of nanostructured materials compared to their respective unreinforced counterpart depends on the shift of von Mises stress from the surface to the sub-surface region, leading to reduction in the maximum tensile stress induced by the scratch. To test the hypothesis, we have addressed two important aspects influencing the mechanics of surface deformation response of nanostructured materials. They include: (a) the determining role of nanoparticles on physical and mechanical properties and (b) the primary effect of nanoparticles on the structure of the host matrix. In the test of hypothesis, we have elucidated the relationship between structure, physical, and mechanical properties on the mechanism of nanoscale deformation via careful electron microscopy of the deformed surface. The nanoscale deformation response of polypropylene with large spherulites and α-phase was characterized by ripple-type deformation tracks that formed by a stick–slip mechanism. However, with decrease in spherulite size and evolution of toughness enhancing γ-phase, induced by high crystallization pressure and nanoclay, ironing represented the primary mode of deformation. In contrast, the highly ductile polyethylene system experienced multiple or single ironing process. In summary, the surface deformation topography implied that the nanoscale deformation response was material specific. Furthermore, electron microscopy topography of scratch tracks confirmed that reinforcement of polymers with nanoclay is a viable route to decrease the susceptibility of polymeric materials to nanoscale deformation and can be discussed in terms of physical and mechanical properties of materials, notably refinement of structure, percentage crystallinity, and elastic recovery. It was also intriguing to note that during nanoscratching, elastic recovery was high, in the range 77–85%, implying that a large fraction of the scratch-deformed volume was recovered. Finally, the electron microscopy findings and mechanical properties are related to mathematical analysis.
Measuring Vertex Centrality in Co-occurrence Graphs for Online Social Tag Recommendation

We present a social tag recommendation model for collaborative bookmarking systems. This model receives as input a bookmark of a web page or scientific publication, and automatically suggests a set of social tags useful for annotating the bookmarked document. Analysing and processing the bookmark textual contents - document title, URL, abstract and descriptions - we extract a set of keywords, forming a query that is launched against an index, and retrieves a number of similar tagged bookmarks. Afterwards, we take the social tags of these bookmarks, and build their global co-occurrence sub-graph. The tags (vertices) of this reduced graph that have the highest vertex centrality constitute our recommendations, which are finally ranked based on TF-IDF and personalisation based techniques.
The Correlated Vehicle Routing Problem

This paper presents a variant vehicle routing problem (VRP) to tackle the routes assignment in a lumpy demand environment, where the required capacity is affected by demand variability and the correction between the demands assigned to the routes. The correlated VRP is defined by a TSP-based formulation to minimize the distance traveled and the number of vehicles. A genetic algorithm approach is developed for solving practical problems. The computational results reveal that the correlation between the demand of customers should be evaluated and taken into consideration in the vehicle routing assigning process, which can prevent leading to either additional over or under capacity during the planning period.
Chance Favors the Prepared Genome

ABSTRACT: Most descriptions of mutation have emphasized its negative consequences, and randomness with respect to biological function. This book seeks to balance the discussion by emphasizing mechanisms that both diversify the genome and increase the probability that a genome's descendants will survive. This chapter provides a framework for, and overview of, the diverse contributions to this book; these contributions will be stimulating companions, well into the 21st Century, as we work to comprehend the information contained in genomic databases. Genomes that encode “better” amino acid sequences are at a selective advantage. Genomes that generate diversity also are at an advantage to the extent that they can navigate efficiently through the space of possible sequence changes. a Biochemical systems that tend to increase the ratio of useful to destructive genetic change may harness preexisting information (horizontal gene transfer, DNA translocation and/or DNA duplication), focus the location, timing, and extent of genetic change, adjust the dynamic range of a gene's activity, and/or sample regulatory connections between sites distributed across the genome. Rejecting entirely random genetic variation as the substrate of genome evolution is not a refutation, but rather provides a deeper understanding, of the theory of natural selection of Darwin and Wallace. The fittest molecular strategies survive, along with descendants of the genomes that encode them.
Epidermal T Cells and Wound Healing

The murine epidermis contains resident T cells that express a canonical γδ TCR. These cells arise from fetal thymic precursors and use a TCR that is restricted to the skin in adult animals. These cells assume a dendritic morphology in normal skin and constitutively produce low levels of cytokines that contribute to epidermal homeostasis. When skin is wounded, an unknown Ag is expressed on damaged keratinocytes. Neighboring γδ T cells then round up and contribute to wound healing by local production of epithelial growth factors and inflammatory cytokines. In the absence of skin γδ T cells, wound healing is impaired. Similarly, epidermal T cells from patients with healing wounds are activated and secreting growth factors. Patients with nonhealing wounds have a defective epidermal T cell response. Information gained on the role of epidermal-resident T cells in the mouse may provide information for development of new therapeutic approaches to wound healing.
Exploiting intelligent decision supports for model-driven biomedical system analysis

Both linear modeling and nonlinear modeling provide special means to simplify problem-solving in science and engineering, which also represents a critical stage for intelligent decision support systems. Model-driven decision support systems have numerous real world applications, such as the feature extraction, image compression, pattern recognition, medical diagnosis and telecommunication. In this article, an intelligent decision support system has been exploited for biomedical system analysis. The PCA (Principal Component Analysis) and ICA (Independent Component Analysis) based linear and nonlinear models have been implemented onto the sample characterization of the biomedical systems for decision making, together with applications of neural networks training. The result indicates the effectiveness of the proposed approaches, where the merit and drawback are discussed between linear and nonlinear modeling. Numerical simulations have also been made.
Automated network feature weighting-based intrusion detection systems

A common problem for network intrusion detection systems is that there are many available features describing network traffic and feature values are highly irregular with burst nature. Some values such as octets transferred range several orders of magnitudes, from several bytes to million bytes. The role of network features depends on which pattern to be detected: normal or intrusive one. Intrusion detection rates would be better if we know which network features are more important for a particular pattern. We therefore propose an automated feature weighting method for network intrusion detection based on a fuzzy subspace approach. Experimental results show that the proposed weighting method can improve the detection rates.
Shear strength of steel fiber reinforced prestressed concrete beams

Due to the increasing evidence from previous research results, the 2008 ACI Building Code allows engineers to use steel fiber reinforced concrete (SFRC) to replace the conventional shear reinforcement (i.e. steel stirrups) even if the design shear force is greater than half of the concrete shear strength. Though the new ACI provisions, marked a significant transfer from research to practice, beams constructed of steel fiber reinforced concrete are required to have a minimum amount of steel fibers of 0.75% in volume (100 pounds per cubic yards) and compressive strength not greater than 6 ksi. The ACI provisions are primarily formulated on experimental studies on non-prestressed concrete beams and majority of them had a cylinder compressive strength less than 6 ksi. However, in a prestressed concrete beam, the beneficial effect from prestressing forces could further relax the minimum required fiber volume fraction thus make the use of SFRC more economical. Further, concrete compressive strengths much higher than 6 ksi are commonly used in prestressed concrete beams to reduce the creep related issues as well as to provide larger loading capacity. Therefore, the current ACI requirements will hinder the use of SFRC in structures with prestressed concrete members made of high strength concrete. This paper presents preliminary shear test results of large scale prestressed concrete beams constructed of steel fiber reinforced concrete.
Grid Load Balancing Using Ant Colony Optimization

An enhanced ant colony optimization technique for jobs and resources scheduling in grid computing is proposed in this paper. The proposed technique combines the techniques from Ant Colony System and Max – Min Ant System and focused on local pheromone trail update and trail limit. The agent concept is also integrated in this proposed technique for the purpose of updating the grid resource table. This facilitates in scheduling jobs to available resources efficiently which will enable jobs to be processed in minimum time and also balance all the resource in grid system.
Combat in Games

Author(s): Osborn, JC; Lederle-Ensign, D; Wardrip-Fruin, NG; Mateas, M | Abstract: While the game design and game studies communities have analyzed combat both in specific games and game genres, and while combat is clearly central to many types of games, there is no general account of combat that is portable across diverse games. We provide such an account in the form of criteria which are satisfied by games that players inter- pret as “having combat. ” These requirements are eventually fulfilled via operational logics, which tie the game’s observ- able behavior (including its instantial assets) to play expe- riences and cultural knowledge, creating what we refer to as a “combat model. ” In addition to establishing a com- prehensive model of combat, making it possible to discuss combat across game genres, this work is the first to describe how complex playable models are constructed from composi- tions of operational logics working in concert; we also define two families of logics which are novel in the literature. This broad model of combat has already proved useful in practice, yielding insights in the analysis of the art game Unmanned; it also promises exciting computational applications in areas such as game design support tools and general game playing.
A Physical Full-Resolution SAR Ship Detection Filter

Synthetic aperture radar (SAR) ship detection is an important application in the context of environment and security monitoring. It allows monitoring traffic, fisheries, and associating ships with oil discharge over wide areas with high spatial resolution almost independently from weather conditions and both day and night time. Since full-resolution SAR images are heavily affected by the presence of speckle, ship detection algorithms generally employ speckle reduced SAR images at the expense of a degradation of the spatial resolution. A new physical approach, which considers ships as dominant scatterers and, therefore, responsible for a strong and coherent backscattered signal, is here proposed. Based on this rationale, a new simple and very effective filtering technique, which is able to process full-resolution SAR images, has been conceived and implemented. Experiments, accomplished over C-band European Remote Sensing satellite (ERS) 1/2 single-look complex SAR images, show the effectiveness of the proposed approach.