Automated Word Puzzle Generation via Topic Dictionaries

We propose a general method for automated word puzzle generation. Contrary to previous approaches in this novel field, the presented method does not rely on highly structured datasets obtained with serious human annotation effort: it only needs an unstructured and unannotated corpus (i.e., document collection) as input. The method builds upon two additional pillars: (i) a topic model, which induces a topic dictionary from the input corpus (examples include e.g., latent semantic analysis, group-structured dictionaries or latent Dirichlet allocation), and (ii) a semantic similarity measure of word pairs. Our method can (i) generate automatically a large number of proper word puzzles of different types, including the odd one out, choose the related word and separate the topics puzzle. (ii) It can easily create domain-specific puzzles by replacing the corpus component. (iii) It is also capable of automatically generating puzzles with parameterizable levels of difficulty suitable for, e.g., beginners or intermediate learners.Comment: 4 page

Optimized Superconducting Nanowire Single Photon Detectors to Maximize Absorptance

Dispersion characteristics of four types of superconducting nanowire single photon detectors, nano-cavity-array- (NCA-), nano-cavity-deflector-array- (NCDA-), nano-cavity-double-deflector-array- (NCDDA-) and nano-cavity-trench-array- (NCTA-) integrated (I-A-SNSPDs) devices was optimized in three periodicity intervals commensurate with half-, three-quarter- and one SPP wavelength. The optimal configurations capable of maximizing NbN absorptance correspond to periodicity dependent tilting in S-orientation (90{\deg} azimuthal orientation). In NCAI-A-SNSPDs absorptance maxima are reached at the plasmonic Brewster angle (PBA) due to light tunneling. The absorptance maximum is attained in a wide plasmonic-pass-band in NCDAI_1/2*lambda-A, inside a flat-plasmonic-pass-band in NCDAI_3/4*lambda-A and inside a narrow plasmonic-band in NCDAI_lambda-A. In NCDDAI_1/2*lambda-A bands of strongly-coupled cavity and plasmonic modes cross, in NCDDAI_3/4*lambda-A an inverted-plasmonic-band-gap develops, while in NCDDAI_lambda-A a narrow plasmonic-pass-band appears inside an inverted-minigap. The absorptance maximum is achieved in NCTAI_1/2*lambda-A inside a plasmonic-pass-band, in NCTAI_3/4*lambda-A at inverted-plasmonic-band-gap center, while in NCTAI_lambda-A inside an inverted-minigap. The highest 95.05% absorptance is attained at perpendicular incidence onto NCTAI_lambda-A. Quarter-wavelength type cavity modes contribute to the near-field enhancement around NbN segments except in NCDAI_lambda-A and NCDDAI_3/4*lambda-A. The polarization contrast is moderate in NCAI-A-SNSPDs (~10^2), NCDAI- and NCDDAI-A-SNSPDs make possible to attain considerably large polarization contrast (~10^2-10^3 and ~10^3-10^4), while NCTAI-A-SNSPDs exhibit a weak polarization selectivity (~10-10^2).Comment: 26 pages, 8 figure

Enhancing diamond color center fluorescence via optimized plasmonic nanorod configuration

A novel numerical methodology has been developed, which makes possible to optimize arbitrary emitting dipole and plasmonic nano-resonator configuration with an arbitrary objective function. By selecting quantum efficiency as the objective function that has to be maximized at preselected Purcell factor criteria, optimization of plasmonic nanorod based configurations has been realized to enhance fluorescence of NV and SiV color centers in diamond. Gold and silver nanorod based configurations have been optimized to enhance excitation and emission separately, as well as both processes simultaneously, and the underlying nanophotonical phenomena have been inspected comparatively. It has been shown that considerable excitation enhancement is achieved by silver nanorods, while nanorods made of both metals are appropriate to enhance emission. More significant improvement can be achieved via silver nanorods at both wavelengths of both color centers. It has been proven that theoretical limits originating from metal dielectric properties can be approached by simultaneous optimization, which results in configurations determined by preferences corresponding to the emission. Larger emission enhancement is achieved via both metals in case of SiV center compared to the NV center. Gold and silver nanorod based configurations making possible to improve SiV centers quantum efficiency by factors of 1.18 and 5.25 are proposed, which have potential applications in quantum information processing.Comment: 20 pages, 8 figure

Evolution of shear zones in granular materials

The evolution of wide shear zones (or shear bands) was investigated experimentally and numerically for quasistatic dry granular flows in split bottom shear cells. We compare the behavior of materials consisting of beads, irregular grains (e.g. sand) and elongated particles. Shearing an initially random sample, the zone width was found to significantly decrease in the first stage of the process. The characteristic shear strain associated with this decrease is about unity and it is systematically increasing with shape anisotropy, i.e. when the grain shape changes from spherical to irregular (e.g. sand) and becomes elongated (pegs). The strongly decreasing tendency of the zone width is followed by a slight increase which is more pronounced for rod like particles than for grains with smaller shape anisotropy (beads or irregular particles). The evolution of the zone width is connected to shear induced density change and for nonspherical particles it also involves grain reorientation effects. The final zone width is significantly smaller for irregular grains than for spherical beads.Comment: 11 pages, 12 figures, submitted to Phys. Rev.

Quasiliving cationic ring-opening polymerization of 2-ethyl-2-oxazoline in benzotrifluoride, as an alternative reaction medium

Cationic ring-opening polymerization (CROP) of 2-ethyl-2-oxazoline (EtOx) was systematically investigated in benzotrifluoride (BTF), which is considered as an environmentally less harmful solvent than many conventional reaction media. Simultaneously, polymerizations in conventional solvents, such as acetonitrile, N,N-dimethylacetamide and toluene, were also carried out for comparison in the 80-100 degrees C temperature range. Kinetic experiments revealed that the monomer consumption occurs by first order kinetics and the number average molecular weights linearly increase in line with the theoretical molecular weight as a function of monomer conversion. These findings indicate that the polymerization takes place by quasiliving CROP in all the investigated solvents, including BTF as well, resulting in PEtOx with prederminded molecular weights and polydispersities of 1.3-15. The highest polymerization rates were obtained in BTF, resulting in high conversions in short reaction times at 100 degrees C reaction temperature. The Arrhenius parameters of the polymerization of EtOx in BTF indicates relatively high activation energy in comparison with other applied solvents, however, a compensation effect between the activation energies and frequency factor is observed for such polymerization in a variety of solvents. Our findings are expected to enable the convenient synthesis of polyoxazolines and polyoxazoline-based well-defined polymer architectures in BTF, an environmentally advantageous alternative solvent to harmful polymerization media, with high polymerization rates in short reaction times without the need for any special conditions or equipment.Peer reviewe

Multiple Benefits of Plasmid-Mediated Quinolone Resistance Determinants in Klebsiella pneumoniae ST11 High-Risk Clone and Recently Emerging ST307 Clone

International high-risk clones of Klebsiella pneumoniae are among the most common nosocomial pathogens. Increased diversity of plasmid-encoded antimicrobial resistance genes facilitates spread of these clones causing significant therapeutic difficulties. The purpose of our study was to investigate fluoroquinolone resistance in extended-spectrum beta-lactamase (ESBL)-producing strains, including four K. pneumoniae and a single K. oxytoca, isolated from blood cultures in Hungary. Whole-genome sequencing and molecular typing including multilocus sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE) were performed in selected strains. Gene expression of plasmid-mediated quinolone resistance determinants (PMQR) was investigated by quantitative-PCR. MLST revealed that three K. pneumoniae strains belonged to ST11 and one to ST307 whereas K. oxytoca belonged to ST52. The isolates harbored different β-lactamase genes, however, all K. pneumoniae uniformly carried blaCTX-M-15. The K. pneumoniae isolates exhibited resistance to fluoroquinolones and carried various PMQR genes namely, two ST11 strains harbored qnrB4, the ST307 strain harbored qnrB1 and all K. pneumoniae harbored oqxAB efflux pump. Levofloxacin and moxifloxacin MIC values of K. pneumoniae ST11 and ST307 clones correlated with qnr and oqxAB expression levels. The qnrA1 carrying K. oxytoca ST52 exhibited reduced susceptibility to fluoroquinolones. The maintained expression of qnr genes in parallel with chromosomal mutations indicate an additional protective role of Qnr proteins that can support dissemination of high-risk clones. During development of high-level fluoroquinolone resistance, high-risk clones retain fitness thus, enabling them for dissemination in hospital environment. Based on our knowledge this is the first report of ST307 clone in Hungary, that is emerging as a potential high-risk clone worldwide. High-level fluoroquinolone resistance in parallel with upregulated PMQR gene expression are linked to high-risk K. pneumoniae clones

A Cloud-based Machine Learning Pipeline for the Efficient Extraction of Insights from Customer Reviews

The efficiency of natural language processing has improved dramatically with the advent of machine learning models, particularly neural network-based solutions. However, some tasks are still challenging, especially when considering specific domains. In this paper, we present a cloud-based system that can extract insights from customer reviews using machine learning methods integrated into a pipeline. For topic modeling, our composite model uses transformer-based neural networks designed for natural language processing, vector embedding-based keyword extraction, and clustering. The elements of our model have been integrated and further developed to meet better the requirements of efficient information extraction, topic modeling of the extracted information, and user needs. Furthermore, our system can achieve better results than this task's existing topic modeling and keyword extraction solutions. Our approach is validated and compared with other state-of-the-art methods using publicly available datasets for benchmarking