Investigation of the development of cracks in solder joints

Study consisted of an analytical approach, in which a mathematical model of existing printed circuit board component mounting techniques was analyzed, and an empirical investigation was performed to determine the extent of damage caused by temperature cycling of the printed circuit boards

Theoretical optical and x-ray spectra of liquid and solid H_2O

Theoretical optical and x-ray spectra of model structures of water and ice are calculated using a many-body perturbation theory, Bethe-Salpeter equation (BSE) approach implemented in the valence- and core-excitation codes AI2NBSE and OCEAN. These codes use ab initio density functional theory wave functions from a plane-wave, pseudopotential code, quasi-particle self energy corrections, and a BSE treatment of particle-hole interactions. The approach improves upon independent-particle methods through the inclusion of a complex, energy-dependent self energy and screened particle-hole interactions to account for inelastic losses and excitonic effects. These many-body effects are found to be crucial for quantitative calculations of ice and water spectra

Bethe-Salpeter Equation Calculations of Core Excitation Spectra

We present a hybrid approach for GW/Bethe-Salpeter Equation (BSE) calculations of core excitation spectra, including x-ray absorption (XAS), electron energy loss spectra (EELS), and non-resonant inelastic x-ray scattering (NRIXS). The method is based on {\it ab initio} wavefunctions from the plane-wave pseudopotential code ABINIT; atomic core-level states and projector augmented wave (PAW) transition matrix elements; the NIST core-level BSE solver; and a many-pole GW self-energy model to account for final-state broadening and self-energy shifts. Multiplet effects are also accounted for. The approach is implemented using an interface dubbed OCEAN (Obtaining Core Excitations using ABINIT and NBSE). To demonstrate the utility of the code we present results for the K-edges in LiF as probed by XAS and NRIXS, the K-edges of KCl as probed by XAS, the Ti L_2,3-edge in SrTiO_3 as probed by XAS, and the Mg L_2,3-edge in MgO as probed by XAS. We compare the results to experiments and results obtained using other theoretical approaches

Compressing Word Embeddings

Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic regularities using vector arithmetic. However, these vector space representations (created through large-scale text analysis) are typically stored verbatim, since their internal structure is opaque. Using word-analogy tests to monitor the level of detail stored in compressed re-representations of the same vector space, the trade-offs between the reduction in memory usage and expressiveness are investigated. A simple scheme is outlined that can reduce the memory footprint of a state-of-the-art embedding by a factor of 10, with only minimal impact on performance. Then, using the same `bit budget', a binary (approximate) factorisation of the same space is also explored, with the aim of creating an equivalent representation with better interpretability.Comment: 10 pages, 0 figures, submitted to ICONIP-2016. Previous experimental results were submitted to ICLR-2016, but the paper has been significantly updated, since a new experimental set-up worked much bette

Exploring individual perceptions of school competence

poster abstractThe project explores school competence and endeavors to define and assess ways of measuring persons’ abilities to successfully complete school-related tasks. The current study also examines factors in the realm of the school-to-prison pipeline. Current research is necessary to further explore individual perceptions of school competence. A school competency instrument was developed and is being pilot tested. The instrument assesses the influence of teachers, parents, peers, and students’ perceptions on their level school competence

Deriving Contextualised Semantic Features from BERT (and Other Transformer Model) Embeddings

Models based on the transformer architecture, such as BERT, have marked a crucial step for- ward in the field of Natural Language Pro- cessing. Importantly, they allow the creation of word embeddings that capture important semantic information about words in context. However, as single entities, these embeddings are difficult to interpret and the models used to create them have been described as opaque. Binder and colleagues proposed an intuitive embedding space where each dimension is based on one of 65 core semantic features. Un- fortunately, the space only exists for a small data-set of 535 words, limiting its uses. Pre- vious work (Utsumi, 2018, 2020; Turton et al., 2020) has shown that Binder features can be derived from static embeddings and success- fully extrapolated to a large new vocabulary. Taking the next step, this paper demonstrates that Binder features can be derived from the BERT embedding space. This provides two things; (1) semantic feature values derived from contextualised word embeddings and (2) insights into how semantic features are repre- sented across the different layers of the BERT model

Trait Anxiety Effects on Late Phase Threatening Speech Processing: Evidence from Electroencephalography

The effects of threatening stimuli, including threatening language, on trait anxiety have been widely studied. However, whether anxiety levels have a direct effect on language processing has not been so consistently explored. The present study focuses on event-related potential (ERP) patterns resulting from electroencephalographic (EEG) measurement of participants' (n = 36) brain activity while they perform a dichotic listening task. Participants' anxiety level was measured via a behavioural inhibition system scale (BIS). Later, participants listened to dichotically paired sentences, one neutral and the other threatening, and indicated at which ear they heard the threatening stimulus. Threatening sentences expressed threat semantically-only, prosodically-only, or both combined (congruent threat). ERPs showed a late positivity, interpreted as a late positive complex (LPC). Results from Bayesian hierarchical models provided strong support for an association between LPC and BIS score. This was interpreted as an effect of trait anxiety on deliberation processes. We discuss two possible interpretations. On the one hand, verbal repetitive thinking, as associated with anxious rumination and worry, can be the mechanism disrupting late phase deliberation processes. Instantiated by inner speech, verbal repetitive thinking might be the vehicle of anxiety-related reappraisal and/or rehearsal. On the other hand, increased BIS could be simply affecting an extended evaluation stage as proposed by multistep models, maybe due to over-engagement with threat or to task-related effects