Probing the Promise of Dual-Language Books

Because dual-language books (DLBs) are written entirely in two languages, they have the potential to help readers develop multilingual literacy skills while acting as cultural and/or linguistic windows and mirrors. However, the ways in which publishers choose words when translating, format languages, and represent cultures have implications for readers in terms of identity, readability, and language learning. This content analysis of 69 U.S. Spanish–English dual-language picturebooks published from 2013–2016 investigated trends in DLBs’ cultural, linguistic, formatting, and readability factors. It also determined these trends’ relationships with publisher types, original publication language, and author and character ethnicity. Findings include that publishers specializing in multilingual or Latinx literature tend to create more DLBs featuring Latinx characters and with more diverse portrayals than in the past. However, regardless of publisher type, original language, or author/character ethnicity, DLBs’ formatting generally privileges English. The implicit marginalization of Spanish and the need to seek out smaller, lesser-known publishers for diverse Latinx portrayals can have implications for readers’ identity and biliteracy development

Query Expansion Techniques for Enterprise Search

Although web search remains an active research area, interest in enterprise search has waned. This is despite the fact that the market for enterprise search applications is expected to triple within the next six years, and that knowledge workers spend an average of 1.6 to 2.5 hours each day searching for information. To improve search relevancy, and hence reduce this time, an enterprise- focused application must be able to handle the unique queries and constraints of the enterprise environment. The goal of this thesis research was to develop, implement, and study query expansion techniques that are most effective at improving relevancy in enterprise search. The case-study instrument used in this investigation was a custom Apache Solr-based search application deployed at a local medium-sized manufacturing company. It was hypothesized that techniques specifically tailored to the enterprise search environment would prove most effective. Query expansion techniques leveraging entity recognition, alphanumeric term identification, intent classification, collection enrichment, and word vectors were implemented and studied using real enterprise data. They were evaluated against a test set of queries developed using relevance survey results from multiple users, using standard relevancy metrics such as normalized discounted cumulative gain (nDCG). Comprehensive analysis revealed that the current implementation of the collection enrichment and word vector query expansion modules did not demonstrate meaningful improvements over the baseline methods. However, the entity recognition, alphanumeric term identification, and query intent classification modules produced meaningful and statistically significant improvements in relevancy, allowing us to accept the hypothesis

The Beam Conditions Monitor of the LHCb Experiment

The LHCb experiment at the European Organization for Nuclear Research (CERN) is dedicated to precision measurements of CP violation and rare decays of B hadrons. Its most sensitive components are protected by means of a Beam Conditions Monitor (BCM), based on polycrystalline CVD diamond sensors. Its configuration, operation and decision logics to issue or remove the beam permit signal for the Large Hadron Collider (LHC) are described in this paper.Comment: Index Terms: Accelerator measurement systems, CVD, Diamond, Radiation detector

Elevated O-GlcNAc levels activate epigenetically repressed genes and delay mouse ES cell differentiation without affecting naive to primed cell transition

The differentiation of mouse embryonic stem (ES) cells is controlled by the interaction of multiple signaling pathways, typically mediated by post-translational protein modifications. The addition of O-linked N-acetylglucosamine (O-GlcNAc) to serine and threonine residues of nuclear and cytoplasmic proteins is one such modification (O-GlcNAcylation), whose function in ES cells is only now beginning to be elucidated. Here we demonstrate that the specific inhibition of O-GlcNAc hydrolase (Oga) causes increased levels of protein O-GlcNAcylation and impairs differentiation of mouse ES cells both in serum-free monolayer and in embryoid bodies (EBs). Use of reporter cell lines demonstrates that Oga inhibition leads to a reduction in the number of Sox1-expressing neural progenitors generated following induction of neural differentiation, as well as maintained expression of the ES cell marker Oct4 (Pou5f1). In EBs expression of mesodermal and endodermal markers is also delayed. However, the transition of naïve cells to primed pluripotency indicated by Rex1 (Zfp42), Nanog, Esrrb and Dppa3 downregulation and Fgf5 upregulation remains unchanged. Finally, we demonstrate that increased O-GlcNAcylation results in upregulation of genes normally epigenetically silenced in ES cells, supporting the emerging role for this protein modification in the regulation of histone modifications and DNA methylation. Stem Cells 2014

Revisiting loss-specific training of filter-based MRFs for image restoration

It is now well known that Markov random fields (MRFs) are particularly effective for modeling image priors in low-level vision. Recent years have seen the emergence of two main approaches for learning the parameters in MRFs: (1) probabilistic learning using sampling-based algorithms and (2) loss-specific training based on MAP estimate. After investigating existing training approaches, it turns out that the performance of the loss-specific training has been significantly underestimated in existing work. In this paper, we revisit this approach and use techniques from bi-level optimization to solve it. We show that we can get a substantial gain in the final performance by solving the lower-level problem in the bi-level framework with high accuracy using our newly proposed algorithm. As a result, our trained model is on par with highly specialized image denoising algorithms and clearly outperforms probabilistically trained MRF models. Our findings suggest that for the loss-specific training scheme, solving the lower-level problem with higher accuracy is beneficial. Our trained model comes along with the additional advantage, that inference is extremely efficient. Our GPU-based implementation takes less than 1s to produce state-of-the-art performance.Comment: 10 pages, 2 figures, appear at 35th German Conference, GCPR 2013, Saarbr\"ucken, Germany, September 3-6, 2013. Proceeding

Intermanifold similarities in partial photoionization cross sections of helium

Using the eigenchannel R-matrix method we calculate partial photoionization cross sections from the ground state of the helium atom for incident photon energies up to the N=9 manifold. The wide energy range covered by our calculations permits a thorough investigation of general patterns in the cross sections which were first discussed by Menzel and co-workers [Phys. Rev. A {\bf 54}, 2080 (1996)]. The existence of these patterns can easily be understood in terms of propensity rules for autoionization. As the photon energy is increased the regular patterns are locally interrupted by perturber states until they fade out indicating the progressive break-down of the propensity rules and the underlying approximate quantum numbers. We demonstrate that the destructive influence of isolated perturbers can be compensated with an energy-dependent quantum defect.Comment: 10 pages, 10 figures, replacement with some typos correcte

Shifts in dominant tree mycorrhizal associations in response to anthropogenic impacts

Plant-fungal symbioses play critical roles in vegetation dynamics and nutrient cycling, modulating the impacts of global changes on ecosystem functioning. Here, we used forest inventory data consisting of more than 3 million trees to develop a spatially resolved “mycorrhizal tree map” of the contiguous United States. We show that abundances of the two dominant mycorrhizal tree groups—arbuscular mycorrhizal (AM) and ectomycorrhizal trees—are associated primarily with climate. Further, we show that anthropogenic influences, primarily nitrogen (N) deposition and fire suppression, in concert with climate change, have increased AM tree dominance during the past three decades in the eastern United States. Given that most AM-dominated forests in this region are underlain by soils with high N availability, our results suggest that the increasing abundance of AM trees has the potential to induce nutrient acceleration, with critical consequences for forest productivity, ecosystem carbon and nutrient retention, and feedbacks to climate change

Superpixel Convolutional Networks using Bilateral Inceptions

In this paper we propose a CNN architecture for semantic image segmentation. We introduce a new 'bilateral inception' module that can be inserted in existing CNN architectures and performs bilateral filtering, at multiple feature-scales, between superpixels in an image. The feature spaces for bilateral filtering and other parameters of the module are learned end-to-end using standard backpropagation techniques. The bilateral inception module addresses two issues that arise with general CNN segmentation architectures. First, this module propagates information between (super) pixels while respecting image edges, thus using the structured information of the problem for improved results. Second, the layer recovers a full resolution segmentation result from the lower resolution solution of a CNN. In the experiments, we modify several existing CNN architectures by inserting our inception module between the last CNN (1x1 convolution) layers. Empirical results on three different datasets show reliable improvements not only in comparison to the baseline networks, but also in comparison to several dense-pixel prediction techniques such as CRFs, while being competitive in time.Comment: European Conference on Computer Vision (ECCV), 201

Hanle effect in the solar Ba II D2 line: a diagnostic tool for chromospheric weak magnetic fields

The physics of the solar chromosphere depends in a crucial way on its magnetic structure. However there are presently very few direct magnetic field diagnostics available for this region. Here we investigate the diagnostic potential of the Hanle effect on the Ba II D2 line resonance polarization for the determination of weak chromospheric turbulent magnetic fields......Comment: In press in astronomy and astrophysic