This study investigated the influence of multiliteracy in opaque orthographies on phonological awareness. Using a visual rhyme judgement task in English, we assessed phonological processing in three multilingual and multiliterate populations who were distinguished by the transparency of the orthographies they can read in (N = 135; ages 18-40). The first group consisted of 45 multilinguals literate in English and a transparent Latin orthography like Malay; the second group consisted of 45 multilinguals literate in English and transparent orthographies like Malay and Arabic; and the third group consisted of 45 multilinguals literate in English, transparent orthographies, and Mandarin Chinese, an opaque orthography. Results showed that all groups had poorer performance in the two opaque conditions: rhyming pairs with different orthographic endings and non-rhyming pairs with similar orthographic endings, with the latter posing the greatest difficulty. Subjects whose languages consisted of half or more opaque orthographies performed significantly better than subjects who knew more transparent orthographies than opaque orthographies. The findings are consistent with past studies that used the visual rhyme judgement paradigm and suggest that literacy experience acquired over time relating to orthographic transparency may influence performance on phonological awareness tasks.
The aim of this study was to characterize multiscale interactions between high intensity focused ultrasound (HIFU) and dentin collagen and associated matrix-metalloproteinases, in addition to the analysis of the effect of HIFU on bacterial biofilms and biological properties. Dentin specimens were subjected to 5, 10 or 20 s HIFU. XPS spectra were acquired and TEM was performed on dentin slabs. Collagen orientation was performed using Raman spectroscopy. Calcium measurements in human dental pulpal cells (hDPCs) were carried out after 7 and 14 days. For macrophages, CD36+ and CD163+ were analysed. Biofilms were analyzed using CLSM. Tandem mass spectroscopy was performed for the detection of hydroxyproline sequences along with human MMP-2 quantification. Phosphorus, calcium, and nitrogen were detected in HIFU specimens. TEM images demonstrated the collagen network appearing to be fused together in the HIFU 10 and 20 s specimens. The band associated with 960 cm-1 corresponds to the stretching ν1 PO43-. The control specimens showed intensive calcium staining followed by HIFU 20 s > HIFU 10 s > HIFU 5 s specimens. Macrophages in the HIFU specimens co-expressed CD80+ and CD163+ cells. CLSM images showed the HIFU treatment inhibiting bacterial growth. SiteScore propensity determined the effect of HIFU on the binding site with a higher DScore representing better site exposure on MMPs. Multiscale mapping of dentin collagen after HIFU treatment showed no deleterious alterations on the organic structure of dentin.
The Machine Learning Model (MLM) has garnered popularity in rehabilitation, ranging from developing algorithms in outcome prediction, prognostication, and training artificial intelligence. High-quality data plays a critical role in algorithm development. Limited studies have explored factors that may influence the MLM algorithm performance in predicting spasticity severity level. The objectives of this study were to train and validate a MLM algorithm for spasticity assessment and determine the algorithm's prediction performance in predicting ambiguous spasticity datasets. Forty-seven persons with central nervous system pathology that fulfilled the inclusion and exclusion criteria were recruited. Four biomechanical properties of spasticity were obtained using off-the-shelf wearable sensors. The data were analyzed individually, and ambiguous datasets were separated. The acceptable inertial data were used to train and validate MLM in predicting spasticity. The trained and validated MLM algorithm was later deployed to predict the ambiguous spasticity datasets. A series of MLM were applied, including Support Vector Machine, Decision Tree, and Random Forest. The MLM's performance accuracy of the validation data was 96%, 52%, and 72%, respectively. The validated MLM accuracy performance level predicting ambiguous datasets reduces to 20%, 23%, and 23%, respectively. This study elucidates data biases and variances of disease background, pathophysiological and anatomical factors that have to be considered in MLM training.
Marine harbours are the focus of a diverse range of activities and subject to multiple anthropogenically induced pressures. Support for environmental management options aimed at improving degraded harbours depends on understanding the factors which influence people's perceptions of harbour environments. We used an online survey, across 12 harbours, to assess sources of variation people's perceptions of harbour health and ecological engineering. We tested the hypotheses: 1) people living near impacted harbours would consider their environment to be more unhealthy and degraded, be more concerned about the environment and supportive of and willing to pay for ecological engineering relative to those living by less impacted harbours, and 2) people with greater connectedness to the harbour would be more concerned about and have greater perceived knowledge of the environment, and be more supportive of, knowledgeable about and willing to pay for ecological engineering, than those with less connectedness. Across twelve locations, the levels of degradation and modification by artificial structures were lower and the concern and knowledge about the environment and ecological engineering were greater in the six Australasian and American than the six European and Asian harbours surveyed. We found that people's perception of harbours as healthy or degraded, but not their concern for the environment, reflected the degree to which harbours were impacted. There was a positive relationship between the percentage of shoreline modified and the extent of support for and people's willingness to pay indirect costs for ecological engineering. At the individual level, measures of connectedness to the harbour environment were good predictors of concern for and perceived knowledge about the environment but not support for and perceived knowledge about ecological engineering. To make informed decisions, it is important that people are empowered with sufficient knowledge of the environmental issues facing their harbour and ecological engineering options.