An exploration of the integration of speech with co-speech gesture with non-invasive brain stimulation

The current PhD project focuses on the integration of gesture with their co-occurring speech with the use of non-invasive brain stimulation. The project investigated ‘where’ and ‘when’ gesture-speech integration takes place. Building on the paradigm of Kelly et al., (2010) which provides a reaction time index of automatic gesture-speech integration, it was tested whether left middle temporal gyrus (pMTG) as well as left Inferior frontal gyrus (LIFG) are causally involved in gesture-speech integration. A follow-up study investigated the time window for this integration of gesture and speech in pMTG. This study found that gesture has a priming effect on the semantic retrieval of speech. This effect only manifested itself after gesture had been clearly understood and before the semantic analysis of speech. Based on the common coding hypothesis, this finding was interpreted in terms of gesture and speech originating from a common coding system, with both LIFG and pMTG as its neural underpining, enabling bi-directional influences between both domains

An Evolution Roadmap for Community Cyber Security Information Sharing Maturity Model

Cyber security has become one of the most important challenges, which is especially true for communities. A community generally consists of all of the entities within a geographical region, including both public and private infrastructures. Cyber attacks and other cyber threats can result in disruption and destruction of critical services and cause potentially devastating impacts in a community. \ \ An effective information collection, sharing and incident collaboration and coordination process is needed in communities to detect potential risks, prevent cyber attacks at an early stage, and facilitate incident response and preparedness activities. In this paper, an expanded collaborative information sharing framework that aims to improve community cyber security is presented. An Information Sharing Maturity Model is developed as a roadmap with evolutionary procedures and incremental steps for community organizations to advance in information sharing maturity

How many keywords do authors assign to research articles – a multi-disciplinary analysis?

Author keywords are one important data source for co-word analysis. The distri-bution of author keywords in papers has not been investigated at the discipline level. We analyzed six research fields from soft science to hard science to reveal the underlying quantitative patterns of author keywords. Normal distribution, Poisson distribution, and Weibull distribution were fitted by applying Maximum Likelihood Estimation. Chi-Square tests and Kolmogorov-Smirnov tests were used to evaluate the goodness of fit. The results show that a large portion of pa-pers have no keyword or only one keyword in all these fields. The author key-word distributions of the six fields are represented. It’s shown that Weibull dis-tribution is the best fitted. This study provides practical implications for keyword selection in co-word analysis

Discovering collective narratives shifts in online discussions

Narrative is a foundation of human cognition and decision making. Because narratives play a crucial role in societal discourses and spread of misinformation and because of the pervasive use of social media, the narrative dynamics on social media can have profound societal impact. Yet, systematic and computational understanding of online narratives faces critical challenge of the scale and dynamics; how can we reliably and automatically extract narratives from massive amount of texts? How do narratives emerge, spread, and die? Here, we propose a systematic narrative discovery framework that fill this gap by combining change point detection, semantic role labeling (SRL), and automatic aggregation of narrative fragments into narrative networks. We evaluate our model with synthetic and empirical data two-Twitter corpora about COVID-19 and 2017 French Election. Results demonstrate that our approach can recover major narrative shifts that correspond to the major events

Code-switching costs from Chinese-English relative clauses processing

IntroductionThe source of costs is a primary concern in code-switching, yet a consensus has not yet been reached. This study investigates whether code-switching during syntactic processing in Chinese-English dual languages results in a cost.MethodsWe use Chinese and English relative clauses in either object (Experiment 1) or subject (Experiment 2, which has a more complex structure) positions to test the costs in syntactic processing. Forty-seven Chinese-English bilinguals and 17 English-Chinese bilinguals participated in acceptability judgment tests and self-paced reading experiments.ResultsThe statistical findings indicate that syntactic processing is a source of the costs incurred in code-switching, as evidenced by the code-switching costs observed in the head movement during relative clause comprehension.DiscussionThe outcomes are consistent with the implications of the 4-Morpheme Model and the Matrix Language Framework. Additionally, the experiment shows that the processing of relative clauses depends on the underlying structures, which is consistent with the Dependency Locality Theory

A gate-programmable van der Waals metal-ferroelectric-semiconductor memory

Ferroelecticity, one of the keys to realize nonvolatile memories owing to the remanent electric polarization, has been an emerging phenomenon in the two-dimensional (2D) limit. Yet the demonstrations of van der Waals (vdW) memories using 2D ferroelectric materials as an ingredient are very limited. Especially, gate-tunable ferroelectric vdW memristive device, which holds promises in future neuromorphic applications, remains challenging. Here, we show a prototype gate-programmable memory by vertically assembling graphite, CuInP2S6, and MoS2 layers into a metal-ferroelectric-semiconductor architecture. The resulted devices exhibit two-terminal switchable electro-resistance with on-off ratios exceeding 105 and long-term retention, akin to a conventional memristor but strongly coupled to the ferroelectric characteristics of the CuInP2S6 layer. By controlling the top gate, Fermi level of MoS2 can be set inside (outside) of its band gap to quench (enable) the memristive behaviour, yielding a three-terminal gate programmable nonvolatile vdW memory. Our findings pave the way for the engineering of ferroelectric-mediated memories in future implementations of nanoelectronics

Optimizing single-mode collection from pointlike sources of single photons with adaptive optics

Army Research Office MURI on Hybrid Quantum Interactions Program W911NF09104.The collection efficiency of light from a point-like emitter may be extremely poor due to aberrations induced by collection optics and the emission distribution of the source. Analyzing the aberrant wavefront (e.g., with a Shack-Hartmann sensor) and correcting accordingly can be infeasible on the single-photon level. We present a technique that uses a genetic algorithm to control a deformable mirror for correcting wavefront aberrations in single-photon signals from point emitters. We apply our technique to both a simulated point source and a real InAs quantum dot, achieving coupling increases of up to 50x00025; and automatic reduction of system drift.PostprintPeer reviewe

A Multi-Platform Collection of Social Media Posts about the 2022 U.S. Midterm Elections

Social media are utilized by millions of citizens to discuss important political issues. Politicians use these platforms to connect with the public and broadcast policy positions. Therefore, data from social media has enabled many studies of political discussion. While most analyses are limited to data from individual platforms, people are embedded in a larger information ecosystem spanning multiple social networks. Here we describe and provide access to the Indiana University 2022 U.S. Midterms Multi-Platform Social Media Dataset (MEIU22), a collection of social media posts from Twitter, Facebook, Instagram, Reddit, and 4chan. MEIU22 links to posts about the midterm elections based on a comprehensive list of keywords and tracks the social media accounts of 1,011 candidates from October 1 to December 25, 2022. We also publish the source code of our pipeline to enable similar multi-platform research projects.Comment: 8 pages, 3 figures, forthcoming in ICWSM2