Extracting Topics from Open Educational Resources

In recent years, Open Educational Resources (OERs) were earmarked as critical when mitigating the increasing need for education globally. Obviously, OERs have high-potential to satisfy learners in many different circumstances, as they are available in a wide range of contexts. However, the low-quality of OER metadata, in general, is one of the main reasons behind the lack of personalised services such as search and recommendation. As a result, the applicability of OERs remains limited. Nevertheless, OER metadata about covered topics (subjects) is essentially required by learners to build effective learning pathways towards their individual learning objectives. Therefore, in this paper, we report on a work in progress project proposing an OER topic extraction approach, applying text mining techniques, to generate high-quality OER metadata about topic distribution. This is done by: 1) collecting 123 lectures from Coursera and Khan Academy in the area of data science related skills, 2) applying Latent Dirichlet Allocation (LDA) on the collected resources in order to extract existing topics related to these skills, and 3) defining topic distributions covered by a particular OER. To evaluate our model, we used the data-set of educational resources from Youtube, and compared our topic distribution results with their manually defined target topics with the help of 3 experts in the area of data science. As a result, our model extracted topics with 79% of F1-score.Comment: Editted version of this paper has been accepted to be published in the proceedings of The European Conference on Technology-Enhanced Learning (EC-TEL) 2020 by Springer (Lecture Notes in Computer Science (LNCS) Series

Gatekeeping Twitter: Message diffusion in political hashtags

This article explores the structure of gatekeeping in Twitter by means of a statistical analysis of the political hashtags #FreeIran, #FreeVenezuela and #Jan25, each of which reached the top position in Twitter Trending Topics. We performed a statistical correlation analysis on nine variables of the dataset to evaluate if message replication in Twitter political hashtags was correlated with network topology. Our results suggest an alternative scenario to the dominant view regarding gatekeeping in Twitter political hashtags. Instead of depending on hubs that act as gatekeepers, we found that the intense activity of individuals with relatively few connections is capable of generating highly replicated messages that contributed to Trending Topics without relying on the activity of user hubs. The results support the thesis of social consensus through the influence of committed minorities, which states that a prevailing majority opinion in a population can be rapidly reversed by a small fraction of randomly distributed committed agents

Investigation of wave-driven hydroelastic interactions using numerical and physical modelling approaches

Wave-driven hydroelasticity is of great importance to a wide range of applications within offshore and coastal engineering. Harnessing the benefits of hydroelasticity or minimising its impacts, depending on the application, has recently led to substantial investment in research effort in this field. However, the complex and strongly-coupled nature of the problem generally make the impacts very case specific, highlighting the importance of accurate numerical tools for assessing the impact on a case-by-case basis. Therefore, this study aims to provide novel experimental data to assist with the development of a coupled numerical methodology for simulating fully nonlinear hydroelastic interactions with highly-flexible floating structures. Novel physical data from a laboratory campaign conducted at the University of Plymouth is presented, and used as a reference for assessing the capabilities of an existing coupled numerical approach. The numerical model is a partitioned approach based within the open-source computational fluid dynamics software OpenFOAM and consisting of a two-phase fluid solver; a linear solid model for small deformations solved via the block-coupled method; and strongly-coupled through the Dirichlet–Neumann method with dynamic Aitken under-relaxation. The numerical model is shown to capture well the wave-induced deformation, and the qualitative differences between structures of varying dimensions. However, the high computational cost limits the scope of this work to 2-D, and future work should focus on optimising the approach to allow for application in 3-D problems

Implication of the overlap representation for modelling generalized parton distributions

Based on a field theoretically inspired model of light-cone wave functions, we derive valence-like generalized parton distributions and their double distributions from the wave function overlap in the parton number conserved s-channel. The parton number changing contributions in the t-channel are restored from duality. In our construction constraints of positivity and polynomiality are simultaneously satisfied and it also implies a model dependent relation between generalized parton distributions and transverse momentum dependent parton distribution functions. The model predicts that the t-behavior of resulting hadronic amplitudes depends on the Bjorken variable x_Bj. We also propose an improved ansatz for double distributions that embeds this property.Comment: 15 pages, 8 eps figure

Constraints on chiral operators in N=2 SCFTs

Open Access, © The Authors. Article funded by SCOAP3. This article is distributed under the terms of the Creative Commons Attribution License ( CC-BY 4.0 ), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited

On the selection and design of proteins and peptide derivatives for the production of photoluminescent, red-emitting gold quantum clusters

Novel pathways of the synthesis of photoluminescent gold quantum clusters (AuQCs) using biomolecules as reactants provide biocompatible products for biological imaging techniques. In order to rationalize the rules for the preparation of red-emitting AuQCs in aqueous phase using proteins or peptides, the role of different organic structural units was investigated. Three systems were studied: proteins, peptides, and amino acid mixtures, respectively. We have found that cysteine and tyrosine are indispensable residues. The SH/S-S ratio in a single molecule is not a critical factor in the synthesis, but on the other hand, the stoichiometry of cysteine residues and the gold precursor is crucial. These observations indicate the importance of proper chemical behavior of all species in a wide size range extending from the atomic distances (in the AuI-S semi ring) to nanometer distances covering the larger sizes of proteins assuring the hierarchical structure of the whole self-assembled system

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues

Effects of fibre content and textile structure on dynamic-mechanical and shape-memory properties of ELO/flax biocomposites

Biocomposites were prepared using epoxidized linseed oil (ELO) and flax fibre reinforcements in different assemblies. ELO was cured by two different anhydrides to check how its thermomechanical properties can be influenced. As reinforcements nonwoven mat, twill weave and quasi-unidirectional textile fabrics with two different yarn finenesses were used. Their reinforcing effect was determined in dynamic mechanical analysis (DMA) in flexure. DMA served also to determine the glass transition temperature (Tg). Shape memory properties were derived from quasiunconstrained flexural tests performed near to the Tg of the ELO and its biocomposites. Flax reinforcement reduced the Tg that was attributed to off-stoichiometry owing to chemical reaction between the hydroxyl groups of flax and anhydride hardener. The shape memory parameters were moderate or low. They were affected by both textile content and type

Anesthetic Propofol Attenuates the Isoflurane-Induced Caspase-3 Activation and Aβ Oligomerization

Accumulation and deposition of β-amyloid protein (Aβ) are the hallmark features of Alzheimer's disease. The inhalation anesthetic isoflurane has been shown to induce caspase activation and increase Aβ accumulation. In addition, recent studies suggest that isoflurane may directly promote the formation of cytotoxic soluble Aβ oligomers, which are thought to be the key pathological species in AD. In contrast, propofol, the most commonly used intravenous anesthetic, has been reported to have neuroprotective effects. We therefore set out to compare the effects of isoflurane and propofol alone and in combination on caspase-3 activation and Aβ oligomerization in vitro and in vivo. Naïve and stably-transfected H4 human neuroglioma cells that express human amyloid precursor protein, the precursor for Aβ; neonatal mice; and conditioned cell culture media containing secreted human Aβ40 or Aβ42 were treated with isoflurane and/or propofol. Here we show for the first time that propofol can attenuate isoflurane-induced caspase-3 activation in cultured cells and in the brain tissues of neonatal mice. Furthermore, propofol-mediated caspase inhibition occurred when there were elevated levels of Aβ. Finally, isoflurane alone induces Aβ42, but not Aβ40, oligomerization, and propofol can inhibit the isoflurane-mediated oligomerization of Aβ42. These data suggest that propofol may mitigate the caspase-3 activation by attenuating the isoflurane-induced Aβ42 oligomerization. Our findings provide novel insights into the possible mechanisms of isoflurane-induced neurotoxicity that may aid in the development of strategies to minimize potential adverse effects associated with the administration of anesthetics to patients