Spin-Polarized to Valley-Polarized Transition in Graphene Bilayers at ν=0\nu=0 in High Magnetic Fields

We investigate the transverse electric field ($E$) dependence of the $\nu$=0 quantum Hall state (QHS) in dual-gated graphene bilayers in high magnetic fields. The longitudinal resistivity ($\rho_{xx}$) measured at $\nu$=0 shows an insulating behavior which is strongest in the vicinity of $E$=0, and at large $E$-fields. At a fixed perpendicular magnetic field ($B$), the $\nu$=0 QHS undergoes a transition as a function of $E$, marked by a minimum, temperature-independent $\rho_{xx}$. This observation is explained by a transition from a spin polarized $\nu$=0 QHS at small $E$-fields, to a valley (layer) polarized $\nu$=0 QHS at large $E$-fields. The $E$-field value at which the transition occurs has a linear dependence on $B$Comment: 5 pages, 5 figure

English Word Segmentation in Korean-English Biliterates: A Hangul Orthographic Structure Effect

It has been claimed that skilled readers of English syllabify written words using morphological and orthographic knowledge (e.g., the Basic Orthographic Syllable Structure, or BOSS) rather than phonological considerations (e.g., the Maximal Onset Principle, or MOP). However, biliterate English readers whose first language is phonologically transparent have been found to rely on a MOP-based segmentation preference. Little is known about the specific contribution of first language orthographic knowledge on second language word parsing, particularly when the two languages differ in orthographies. The present research investigated how first learned orthographic knowledge in Korean Hangul may affect word segmentation of a later learned script (English). A split-view lexical decision task was administered in which visually presented stimuli included gaps at junctures corresponding to three different segmentation strategies: a MOP-based strategy, a BOSS-based strategy, and a strategy based on Hangul orthographic structure (HOS). It was hypothesized that lexical decision would be faster and more accurate for stimuli segmented based on a MOP or a HOS analysis than on a BOSS analysis. Of additional interest was whether reliance on a HOS strategy would be greater for readers with greater proficiency in Hangul and for English words that have been borrowed into Korean as loanwords (with a Hangul written counterpart) than for non-borrowed words. Participants in Experiment 1 were native readers of Korean (n = 48) with low English proficiency; Experiment 2 compared Korean-dominant (n = 48) with English-dominant biliterate readers (n = 49). Stimuli in both experiments included 60 borrowed words and 60 non-borrowed words. Results from Experiment 1 found evidence for a Hangul orthography-based segmentation strategy, particularly for loanwords. Experiment 2 found a HOS effect among Korean-dominant readers for loanwords and a weaker HOS effect for non-borrowed words. By contrast, English-dominant readers did not show a differential HOS preference as a function of loanword status. Furthermore, across experiments, all groups demonstrated a MOP effect in response time and accuracy. Taken together, the findings are discussed in terms of transfer effects of L1 alphasyllabic Hangul writing system characteristics to the reading of words in an L2 alphabetic writing system

Quantum Hall Effect in Bernal Stacked and Twisted Bilayer Graphene Grown on Cu by Chemical Vapor Deposition

We examine the quantum Hall effect in bilayer graphene grown on Cu substrates by chemical vapor deposition. Spatially resolved Raman spectroscopy suggests a mixture of Bernal (A-B) stacked and rotationally faulted (twisted) domains. Magnetotransport measurements performed on bilayer domains with a wide 2D band reveal quantum Hall states (QHSs) at filling factors $\nu=4, 8, 12$ consistent with a Bernal stacked bilayer, while magnetotransport measurements in bilayer domains defined by a narrow 2D band show a superposition of QHSs of two independent monolayers. The analysis of the Shubnikov-de Haas oscillations measured in twisted graphene bilayers provides the carrier density in each layer as a function of the gate bias and the inter-layer capacitance.Comment: 5 pages, 4 figure

Synthesis and Characterization of Polymeric Gas Sensing Materials for Detection of Agriculture Lagoon Off-Gas

With increasing food demand, agriculture and farming industry have grown. This led to an increase in production of agricultural waste. The waste is converted into manure via anaerobic fermentation which continuously produces biogas. Every year, a large volume of biogas-containing pollutants, including greenhouse gases (GHG), are released from manure fermentation. To monitor the progress of manure fermentation and control gas pollutants released into the atmosphere, a sensor that can detect components of biogas in a continuous and reliable manner is necessary. For a more economic system, the sensor should be able to operate at room temperature (roughly, 22-25℃ range) and specifically detect certain gas analytes. Methane and ammonia are selected as the target gases for detection because of their significance. Methane is a small molecule hydrocarbon and very potent greenhouse gas. At high concentrations, there is a possibility of combustion and asphyxiation, thus monitoring its presence and concentration is essential. Ammonia is the main source of odor from manure fermentation and can be toxic at a low concentration. As both target gases are toxic and reactive, formaldehyde was used as a “simulant” or “surrogate” gas (a less hazardous gas) for preliminary in-lab testing of sensing material sensitivity with the gas chromatography (GC) set-up. Any sensor requires a sensing material that responds to one specific gas analyte. Polyaniline (PANI), polypyrrole (PPy), and polydimethylsiloxane (PDMS) have been indicated in the literature to exhibit affinity for ammonia and/or methane. They were tested first with gas chromatography (GC) using formaldehyde. Out of the three, PANI showed better sensing capabilities. Tin (IV) oxide, zinc oxide, sodium dodecyl sulphate, titanium (IV) oxide and hydrochloric acid were selected as the top 5 dopants for polyaniline. PANI was synthesized in the lab with varying dopant levels for GC testing. Scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and ultraviolet-visible (UV-Vis) spectroscopy were used to further characterize the synthesized materials for their physical and chemical properties. PANI doped with 2.5% ZnO-sodium dodecyl sulfate (SDS) showed higher sensitivity for sensing formaldehyde as it had the greatest response (sorption) at a low concentration. ZnO incorporation into PANI was poor. When SDS was added, ZnO incorporation improved, which led to higher gas sorption. The notable interaction of SDS and ZnO could be scrutinized further if the formulation needs to be optimized for best ZnO incorporation without sacrificing the PANI structure. When tested with the actual micro-electrical-mechanical system (MEMS) sensor at 50 ppm methane source (test chamber in System Design Engineering), both PANI with 5% SnO2 and 5% ZnO sorbed methane at room temperature. PANI-5% ZnO was proven to be the most suitable sensing material for methane detection, showing the highest signal at 50 ppm methane levels

Residual Control Chart for Binary Response with Multicollinearity Covariates by Neural Network Model

Quality control studies have dealt with symmetrical data having the same shape with respect to left and right. In this research, we propose the residual (r) control chart for binary asymmetrical (non-symmetric) data with multicollinearity between input variables via combining principal component analysis (PCA), functional PCA (FPCA) and the generalized linear model with probit and logit link functions, and neural network regression model. The motivation in this research is that the proposed control chart method can deal with both high-dimensional correlated multivariate data and high frequency functional multivariate data by neural network model and FPCA. We show that the neural network r control chart is relatively efficient to monitor the simulated and real binary response data with the narrow length of control limits

パワーアシスト車椅子のモーションコントロールとその実用化 : 安全性・移動性・便宜性向上のための人間親和型制御システム

学位の種別: 課程博士審査委員会委員 : (主査)東京大学教授 堀 洋一, 東京大学教授 池内 克史, 東京大学教授 大崎 博之, 東京大学教授 古関 隆章, 東京大学准教授 馬場 旬平, 東京大学准教授 藤本 博志University of Tokyo(東京大学

DeeLeMa: Missing information search with Deep Learning for Mass estimation

We present DeeLeMa, a deep learning network to analyze energies and momenta in particle collisions at high energy colliders, especially DeeLeMa is constructed based on symmetric event topology, and the generated mass distributions show robust peaks at the physical masses after the combinatoric uncertainties, and detector smearing effects are taken into account. DeeLeMa can be widely used in different event topologies by adopting the corresponding kinematic symmetries

Insulin modulates the frequency of Ca2+ oscillations in mouse pancreatic islets

Pancreatic islets can adapt to oscillatory glucose to produce synchronous insulin pulses. Can islets adapt to other oscillatory stimuli, specifically insulin? To answer this question, we stimulated islets with pulses of exogenous insulin and measured their Ca2+ oscillations. We observed that sufficiently high insulin (>500 nM) with an optimal pulse period (similar to 4 min) could make islets to produce synchronous Ca2+ oscillations. Glucose and insulin, which are key stimulatory factors of islets, modulate islet Ca2+ oscillations differently. Glucose increases the active-to-silent ratio of phases, whereas insulin increases the period of the oscillation. To examine the dual modulation, we adopted a phase oscillator model that incorporated the phase and frequency modulations. This mathematical model showed that out-of-phase oscillations of glucose and insulin were more effective at synchronizing islet Ca2+ oscillations than in-phase stimuli. This finding suggests that a phase shift in glucose and insulin oscillations can enhance inter-islet synchronization.111Ysciescopu