The Perception of Word Juncture in English and Arabic

Abstract: In this study the perception of word juncture in English and Arabic is investigated. Word juncture is taken as the allophonic, or phonetic, variation at word boundary that is contrastive. It is hypothesized that minimal pairs differentiated by means of juncture ( or boundary features) cannot be identified when heard in isolation and that the sentential context helps identifying the phrases of the pair. Corpuses of English and Arabic minimal pairs of juncture phrases were collected and native speakers of English and Arabic were asked to pronounce these phrases in isolation and then to use them in sentences. Three groups of subjects (a group of 13 Undergraduate students of English, a group of 11 MA students of English and a group of 9 Lecturers, all being native speakers of Arabic) were chosen to carry out the experimental part of the study. Four perception tests were carried out: two on English and two on Arabic. These tests were designated to examine the subjects' precision in the identification of the juncture phrases when used in isolation and in sentences. The subjects' reliance on the phonetic cues to identify the juncture phrases when used in isolation was low and rather fluctuant between the groups and the two languages. The sentential context, on the other hand, has shown a significant influence on the identification responses of the subjects in the three groups and in both English and Arabic

Expectation of having consumed caffeine can improve performance and mood

We explored whether caffeine, and expectation of having consumed caffeine, affects attention, reward responsivity and mood using double-blinded methodology. 88 participants were randomly allocated to ‘drink-type’ (caffeinated/decaffeinated coffee) and ‘expectancy’ (told caffeinated/told decaffeinated coffee) manipulations. Both caffeine and expectation of having consumed caffeine improved attention and psychomotor speed. Expectation enhanced self-reported vigour and reward responsivity. Self-reported depression increased at post-drink for all participants, but less in those receiving or expecting caffeine. These results suggest caffeine expectation can affect mood and performance but do not support a synergistic effect

Use of artificial intelligence on electroencephalogram (EEG) waveforms to predict failure in early school grades in children from a rural cohort in Pakistan

Universal primary education is critical for individual academic growth and overall adult productivity of nations. Estimates indicate that 25% of 59 million primary age out of school children drop out and early grade failure is one of the factors. An objective and feasible screening measure to identify at-risk children in the early grades can help to design appropriate interventions. The objective of this study was to use a Machine Learning algorithm to evaluate the power of Electroencephalogram (EEG) data collected at age 4 in predicting academic achievement at age 8 among rural children in Pakistan. Demographic and EEG data from 96 children of a cohort along with their academic achievement in grade 1-2 measured using an academic achievement test of Math and language at the age of 7-8 years was used to develop the machine learning algorithm. K- Nearest Neighbor (KNN) classifier was used on different model combinations of EEG, sociodemographic and home environment variables. KNN model was evaluated using 5 Stratified Folds based on the sensitivity and specificity. In the current dataset, 55% and 74% failed in the mathematics and language test respectively. On testing data across each fold, the mean sensitivity and specificity was calculated. Sensitivity was similar when EEG variables were combined with sociodemographic, and home environment (Math = 58.7%, Language = 66.3%) variables but specificity improved (Math = 43.4% to 50.6% and Language = 32% to 60%). The model requires further validation for EEG to be used as a screening measure with adequate sensitivity and specificity to identify children in their preschool age who may be at high risk of failure in early grades

Biomechanical Measurement Error Can Be Caused by Fujifilm Thickness: A Theoretical, Experimental, and Computational Analysis

© 2017 Ahmed Sarwar et al. This is the first study to quantify the measurement error due to the physical thickness of Fujifilm for several material combinations relevant to orthopaedics. Theoretical and experimental analyses were conducted for cylinder-on-flat indentation over a series of forces (750 and 3000 N), cylinder diameters (0 to 80 mm), and material combinations (metal-on-metal, MOM; metal-on-polymer, MOP; metal-on-bone, MOB). For the scenario without Fujifilm, classic Hertzian theory predicted the true line-type contact width as WO={(8FDcyl)/(πLcyl)[(1-cyl2)/Ecyl+(1-flat2)/Eflat]}1/2, where F is compressive force, Dcyl is cylinder diameter, Lcyl is cylinder length, cyl and flat are cylinder and flat Poisson\u27s ratios, and Ecyl and Eflat are cylinder and flat elastic moduli. For the scenario with Fujifilm, experimental measurements resulted in contact widths of WF=0.1778×F0.2273×D0.2936 for MOM tests, WF=0.0449×F0.4664×D0.4201 for MOP tests, and WF=0.1647×F0.2397×D0.3394 for MOB tests, where F is compressive force and D is cylinder diameter. Fujifilm thickness error ratio WF/WO showed a nonlinear decrease versus cylinder diameter, whilst error graphs shifted down as force increased. Computational finite element analysis for several test cases agreed with theoretical and experimental data, respectively, to within 3.3% and 1.4%. Despite its wide use, Fujifilm\u27s measurement errors must be kept in mind when employed in orthopaedic biomechanics research