Vocabulary size influences spontaneous speech in native language users: Validating the use of automatic speech recognition in individual differences research

Previous research has shown that vocabulary size affects performance on laboratory word production tasks. Individuals who know many words show faster lexical access and retrieve more words belonging to pre-specified categories than individuals who know fewer words. The present study examined the relationship between receptive vocabulary size and speaking skills as assessed in a natural sentence production task. We asked whether measures derived from spontaneous responses to every-day questions correlate with the size of participants’ vocabulary. Moreover, we assessed the suitability of automatic speech recognition for the analysis of participants’ responses in complex language production data. We found that vocabulary size predicted indices of spontaneous speech: Individuals with a larger vocabulary produced more words and had a higher speech-silence ratio compared to individuals with a smaller vocabulary. Importantly, these relationships were reliably identified using manual and automated transcription methods. Taken together, our results suggest that spontaneous speech elicitation is a useful method to investigate natural language production and that automatic speech recognition can alleviate the burden of labor-intensive speech transcription

Supporting Coastal Resiliency by Investigating Tidal Reach and Inter-Connected Factors in Coastal Georgia

The South Carolina Water Resources Conference (SCWRC) provides an integrated forum for discussion of water policies, research projects and water management in order to prepare for and meet the growing challenge of providing water resources to sustain and grow South Carolina’s economy, while preserving our natural resources

The KD Sr/Ca in cultured massive Porites spp. corals are reduced at low seawater pCO2

This work was supported by the UK Natural Environment Research Council (award NE/I022973/1) to AAF and NA.Coral skeletal Sr/Ca has valuable potential as a proxy of sea surface temperatures (SSTs). However seawater pCO2 can influence skeletal Sr incorporation and Sr/Ca-SST calibrations derived from present day corals may not be applicable to ancient specimens or older sections of modern corals deposited under lower seawater pCO2 than the present day. In this study we analysed skeletal Sr/Ca in multiple genotypes of massive Porites spp. cultured over a range of seawater pCO2 (from 180 to 750 μatm) and temperature (25°C and 28°C). Multiple linear regression analysis indicates that the Sr/Ca aragonite partition coefficient, KD Sr/Ca is inversely related to seawater temperature and positively related to seawater pCO2 (equivalent to changes in skeletal Sr/Ca of 0.046 mmol mol-1 °C-1 and 0.0002 mmol mol–1 µatm-1 respectively). Applying present day Sr/Ca-SST equations to older coral skeletons growing at lower pCO2 could underestimate seawater temperatures. However KD Sr/Ca vary significantly between some coral genotypes cultured at the same seawater pCO2 indicating that other unidentified processes also influence skeletal Sr/Ca and it is unknown how these processes varied when ancient corals were deposited. We do not observe a significant relationship between KD Sr/Ca and coral calcification rate after combining all coral genotypes to allow identification of the correct KD Sr/Ca to apply to coral records.PostprintPeer reviewe

Local Binary Patterns on Hexagonal Image Structure

Local binary pattern (LBP) was designed and widely used for efficient texture classification. It has been used for face recognition and has potential applications in many other research areas such as human detection. LBP provides a simple and effective way to represent patterns. Uniform LBPs play an important role for LBP-based pattern /object recognition as they include majority of LBPs. In this paper, we present LBP codes on hexagonal image structure. We show that LBPs defined on hexagonal structure have higher percentages of uniform LBPs that will lead to a more efficient and accurate recognition scheme for image classification

Two novel mitoviruses from a Canadian isolate of the Dutch elm pathogen Ophiostoma novo-ulmi (93–1224)

BACKGROUND: Ophiostoma novo-ulmi is the causative agent of Dutch elm disease (DED). It is an ascomycetous filamentous fungus that ranks as the third most devastating fungal pathogen in Canada. The disease front has spread eastward and westward from the epicentre in Ontario and Quebec and is threatening elm populations across the country. Numerous mitigation strategies have been tried to eradicate this pathogen, but success has thus far been limited. An alternative approach might utilize double-stranded RNA (dsRNA) mycoviruses which have been reported to induce hypovirulence in other fungi. METHODS: Using a modified single primer amplification technique (SPAT) in combination with chromosomal walking, we have determined the genome sequence of two RdRp encoding dsRNA viruses from an O. novo-ulmi isolate (93–1224) collected from the disease front in Winnipeg. RESULTS: We propose that these viruses, which we have named OnuMV1c and OnuMV7 based on sequence similarity to other Ophiostoma mitoviruses, are two new members of the genus Mitovirus in the family Narnaviridae. CONCLUSIONS: The discovery of such dsRNA elements raises the potential for engineering these viruses to include other genetic elements, such as anti-sense or interfering RNAs, to create novel and highly specific biological controls. Naïve fungal hosts could be infected with both the engineered molecule and a helper mitovirus encoding an RdRp which would provide replication capacity for both molecules

Modeling Diel Vertical Migration with Membrane Computing

Diel vertical migration (DVM) is an important ecological phenomenon in which zooplankton migrate vertically to deal with trade-offs associated with greater food availability in shallow waters and lower predator risk in deep waters due to lower light availability. Because of these trade-offs, DVM dynamics are particularly sensitive to changes in light intensity at the water surface. Therefore, changes in the proportion of cloudy and sunny days have the potential to disrupt DVM dynamics. We propose a new membrane computing model that captures the effect of cloud cover on DVM in Daphnia, and we use it to explore the impacts of an increased proportion of cloudy days that are predicted to occur with climate change. Our 2-dimensional, spatially explicit model integrates multiple trophic levels from abiotic nutrients to Daphnia predators. We analyzed the effect that different proportions of cloudy and sunny days throughout the summer have on our model. The model simulations suggest that an increase in sunny days promotes a high phytoplankton concentration near the surface but does not necessarily promote an increased abundance of Daphnia. Our model also suggests that a higher proportion of cloudy days would increase Daphnia abundance due to a shift in the vertical distribution of Daphnia populations towards superficial waters. Our results highlight that climate changes in multiple regions will affect animal migrations leading to altered food web dynamics in freshwater ecosystems, and emphasize the potential of membrane computing as a modeling framework for spatially and temporally explicit ecological processes

Restricting digital sites of dissent: commercial social media and free expression

The widespread use of commercial social media platforms by protesters and activists has enhanced protest mobilisation and reporting but it has placed social media providers in the intermediary role as facilitators of dissent and has thereby created new challenges. Companies like Google and Facebook are increasingly restricting content that is published on or distributed through their platforms; they have been subject to obstruction by governments; and their services have been at the core of large-scale data collection and surveillance. This article analyses and categorises forms of infrastructure-based restrictions on free expression and dissent. It shows how private intermediaries have been incorporated into state-led content policies; how they set their own standards for legitimate online communication and intervene accordingly; and how state-based actions and commercial self-regulation intersect in the specific area of online surveillance. Based on a broad review of cases, it situates the role of social media in the wider trend of the privatisation of communications policy and the complex interplay between state-based regulation and commercial rule-making

High Spin States in the (p,t) Reaction

This research was sponsored by the National Science Foundation Grant NSF PHY-931478