Assessing English Writing in Multilingual Writers in Higher Education: A Longitudinal Study

English writing skills are important components of multilingual students’ successful academic performance in English-medium higher education. However, little research has been conducted on how multilingual writers develop their English writing skills over time in higher education. Thus, the purpose of the dissertation was to investigate the longitudinal development of English writing for multilingual students in higher education in relation to language skills and knowledge (vocabulary and reading), cognitive skills and knowledge (attention, working memory, and general knowledge), and language features (academic word use and language burst lengths [i.e., the number of characters produced between pauses]). Seventy-seven multilingual undergraduates at a US university participated in two sessions with an at least five-month interval. They were from various countries including China, India, Mexico, and Zimbabwe. The students produced persuasive essays in English and took English reading and vocabulary tests on two occasions. They also completed an attention task, a working memory capacity task, and general knowledge test at the initial time of measurement. A writing process feature was captured by mean burst lengths. A written product feature was characterized by the production of academic words. Latent change score models were used. Four main findings are reported. First, multilingual students’ gains in English writing scores tended to rise as a function of lower initial levels of English writing scores, English reading scores, general knowledge scores, and academic words found in essays. This supports a “poor get richer” scenario rather than “rich get richer,” such that initial lower levels may leave greater potential for gains in writing scores. Second, gains in English writing scores co-occurred with increases in academic words and gains in English reading scores. This indicates the positive longitudinal relationships of writing with reading and vocabulary use. Third, greater gains in writing scores were related to higher levels of working memory capacity, which suggests that working memory capacity is important in learning-to-write processes. Lastly, the presence of a latent variable of English literacy indicated by English writing, reading, and vocabulary was supported over time, providing a parsimonious understanding of English-literacy related variables. Theoretical and pedagogical implications are discussed

Fabrication of three-dimensional suspended, interlayered and hierarchical nanostructures by accuracy-improved electron beam lithography overlay

Nanofabrication techniques are essential for exploring nanoscience and many closely related research fields such as materials, electronics, optics and photonics. Recently, three-dimensional (3D) nanofabrication techniques have been actively investigated through many different ways, however, it is still challenging to make elaborate and complex 3D nanostructures that many researchers want to realize for further interesting physics studies and device applications. Electron beam lithography, one of the two-dimensional (2D) nanofabrication techniques, is also feasible to realize elaborate 3D nanostructures by stacking each 2D nanostructures. However, alignment errors among the individual 2D nanostructures have been difficult to control due to some practical issues. In this work, we introduce a straightforward approach to drastically increase the overlay accuracy of sub-20 nm based on carefully designed alignmarks and calibrators. Three different types of 3D nanostructures whose designs are motivated from metamaterials and plasmonic structures have been demonstrated to verify the feasibility of the method, and the desired result has been achieved. We believe our work can provide a useful approach for building more advanced and complex 3D nanostructures.114sciescopu

Aggregating Credences into Beliefs: Agenda Conditions for Impossibility Results

Binarizing belief aggregation addresses how to rationally aggregate individual probabilistic beliefs into collective binary beliefs. Similar to the development of judgment aggregation theory, formulating axiomatic requirements, proving impossibility theorems, and identifying exact agenda conditions of impossibility theorems are natural and important research topics in binarizing belief aggregation. Building on our previous research on impossibility theorems, we use an agenda-theoretic approach to generalize the results and to determine the necessary and sufficient level of logical interconnection between the issues in an agenda for the impossibility theorems to arise. We demonstrate that (1) path-connectedness and even-negatability constitute the exact agenda condition for the oligarchy result stating that binarizing belief aggregation satisfying proposition-wise independence and deductive closure of collective beliefs yields the oligarchies under minor conditions; (2) negation-connectedness is the condition for the triviality result obtained by adding anonymity to the oligarchy result; and (3) blockedness is the condition for the impossibility result, which follows by adding completeness and consistency of collective beliefs. Moreover, we compare these novel findings with existing agenda-theoretic characterization theorems in judgment aggregation and belief binarization.Comment: In Proceedings TARK 2023, arXiv:2307.0400

Relationship of topology, multiscale phase synchronization, and state transitions in human brain networks

How the brain reconstitutes consciousness and cognition after a major perturbation like general anesthesia is an important question with significant neuroscientific and clinical implications. Recent empirical studies in animals and humans suggest that the recovery of consciousness after anesthesia is not random but ordered. Emergence patterns have been classified as progressive and abrupt transitions from anesthesia to consciousness, with associated differences in duration and electroencephalogram(EEG) properties. We hypothesized that the progressive and abrupt emergence patterns from the unconscious state are associated with, respectively, continuous and discontinuous synchronization transitions in functional brain networks. The discontinuous transition is explainable with the concept of explosive synchronization, which has been studied almost exclusively in network science. We used the Kuramato model, a simple oscillatory network model, to simulate progressive and abrupt transitions in anatomical human brain networks acquired from diffusion tensor imaging (DTI) of 82 brain regions. To facilitate explosive synchronization, distinct frequencies for hub nodes with a large frequency disassortativity (i.e., higher frequency nodes linking with lower frequency nodes, or vice versa) were applied to the brain network. In this simulation study, we demonstrated that both progressive and abrupt transitions follow distinct synchronization processes at the individual node, cluster, and global network levels. The characteristic synchronization patterns of brain regions that are ��progressive and earlier�� or ��abrupt but delayed�� account for previously reported behavioral responses of gradual and abrupt emergence from the unconscious state. The characteristic network synchronization processes observed at different scales provide new insights into how regional brain functions are reconstituted during progressive and abrupt emergence from the unconscious state. This theoretical approach also offers a principled explanation of how the brain reconstitutes consciousness and cognitive functions after physiologic (sleep), pharmacologic (anesthesia), and pathologic (coma) perturbations. ? 2017 Kim, Kim, Mashour and Lee.115sciescopu

Deep sub-wavelength nanofocusing of UV-visible light by hyperbolic metamaterials

Confining light into a sub-wavelength area has been challenging due to the natural phenomenon of diffraction. In this paper, we report deep sub-wavelength focusing via dispersion engineering based on hyperbolic metamaterials. Hyperbolic metamaterials, which can be realized by alternating layers of metal and dielectric, are materials showing opposite signs of effective permittivity along the radial and the tangential direction. They can be designed to exhibit a nearly-flat open isofrequency curve originated from the large-negative permittivity in the radial direction and small-positive one in the tangential direction. Thanks to the ultraflat dispersion relation and curved geometry of the multilayer stack, hyperlens can magnify or demagnify an incident beam without diffraction depending on the incident direction. We numerically show that hyperlens-based nanofocusing device can compress a Gaussian beam down to tens-of-nanometers of spot size in the ultraviolet (UV) and visible frequency range. We also report four types of hyperlenses using different material combinations to span the entire range of visible frequencies. The nanofocusing device based on the hyperlens, unlike conventional lithography, works under ordinary light source without complex optics system, giving rise to practical applications including truly nanoscale lithography and deep sub-wavelength scale confinement.1165Nsciescopu

Fast-Rate Capable Electrode Material with Higher Energy Density than LiFePO4: 4.2V LiVPO4F Synthesized by Scalable Single-Step Solid-State Reaction

Use of compounds that contain fluorine (F) as electrode materials in lithium ion batteries has been considered, but synthesizing single-phase samples of these compounds is a difficult task. Here, it is demonstrated that a simple scalable single-step solid-state process with additional fluorine source can obtain highly pure LiVPO4F. The resulting material with submicron particles achieves very high rate capability approximate to 100 mAh g(-1) at 60 C-rate (1-min discharge) and even at 200 C-rate (18 s discharge). It retains superior capacity, approximate to 120 mAh g(-1) at 10 C charge/10 C discharge rate (6-min) for 500 cycles with >95% retention efficiency. Furthermore, LiVPO4F shows low polarization even at high rates leading to higher operating potential >3.45 V (approximate to 3.6 V at 60 C-rate), so it achieves high energy density. It is demonstrated for the first time that highly pure LiVPO4F can achieve high power capability comparable to LiFePO4 and much higher energy density (approximate to 521 Wh g(-1) at 20 C-rate) than LiFePO4 even without nanostructured particles. LiVPO4F can be a real substitute of LiFePO4.1114Ysciescopu

Attribute Sentiment Scoring With Online Text Reviews : Accounting for Language Structure and Attribute Self-Selection

The authors address two novel and significant challenges in using online text reviews to obtain attribute level ratings. First, they introduce the problem of inferring attribute level sentiment from text data to the marketing literature and develop a deep learning model to address it. While extant bag of words based topic models are fairly good at attribute discovery based on frequency of word or phrase occurrences, associating sentiments to attributes requires exploiting the spatial and sequential structure of language. Second, they illustrate how to correct for attribute self-selection—reviewers choose the subset of attributes to write about—in metrics of attribute level restaurant performance. Using Yelp.com reviews for empirical illustration, they find that a hybrid deep learning (CNN-LSTM) model, where CNN and LSTM exploit the spatial and sequential structure of language respectively provide the best performance in accuracy, training speed and training data size requirements. The model does particularly well on the “hard” sentiment classification problems. Further, accounting for attribute self-selection significantly impacts sentiment scores, especially on attributes that are frequently missing