10,851 research outputs found

    The quantum solvation, adiabatic versus nonadiabatic, and Markovian versus non-Markovian nature of electron transfer rate processes

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    In this work, we revisit the electron transfer rate theory, with particular interests in the distinct quantum solvation effect, and the characterizations of adiabatic/nonadiabatic and Markovian/non-Markovian rate processes. We first present a full account for the quantum solvation effect on the electron transfer in Debye solvents, addressed previously in J. Theore. & Comput. Chem. {\bf 5}, 685 (2006). Distinct reaction mechanisms, including the quantum solvation-induced transitions from barrier-crossing to tunneling, and from barrierless to quantum barrier-crossing rate processes, are shown in the fast modulation or low viscosity regime. This regime is also found in favor of nonadiabatic rate processes. We further propose to use Kubo's motional narrowing line shape function to describe the Markovian character of the reaction. It is found that a non-Markovian rate process is most likely to occur in a symmetric system in the fast modulation regime, where the electron transfer is dominant by tunneling due to the Fermi resonance.Comment: 13 pages, 10 figures, submitted to J. Phys. Chem.

    Topological quantum memory interfacing atomic and superconducting qubits

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    We propose a scheme to manipulate a topological spin qubit which is realized with cold atoms in a one-dimensional optical lattice. In particular, by introducing a quantum opto-electro-mechanical interface, we are able to first transfer a superconducting qubit state to an atomic qubit state and then to store it into the topological spin qubit. In this way, an efficient topological quantum memory could be constructed for the superconducting qubit. Therefore, we can consolidate the advantages of both the noise resistance of the topological qubits and the scalability of the superconducting qubits in this hybrid architecture.Comment: v2: Accepted for publication in Science China-Physics, Mechanics & Astronom

    Effects of Pharmacological Block of GABAA Receptors on Pallidal Neurons in Normal and Parkinsonian State

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    The globus pallidus plays a central integrative role in the basal ganglia circuitry. Morphological studies have revealed a high level of GABA and GABAA receptors in the globus pallidus. To further investigate the effects of endogenous GABAA neurotransmission in the globus pallidus of normal and parkinsonian rats, in vivo extracellular recording and behavioral tests were performed in the present studies. In normal rats, micro-pressure ejection of GABAA receptor antagonist gabazine (0.1 mM) increased the spontaneous firing rate of pallidal neurons by 28.3%. Furthermore, in 6-hydroxydopamine parkinsonian rats, gabazine increased the firing rate by 46.0% on the lesioned side, which was significantly greater than that on the unlesioned side (21.5%, P < 0.05), as well as that in normal rats (P < 0.05). In the behaving rats, unilateral microinjection of gabazine (0.1 mM) evoked consistent contralateral rotation in normal rats, and significantly potentiated the number of apomorphine-induced contralateral rotations in parkinsonian rats. The present electrophysiological and behavioral findings may provide a rational for further investigations into the potential of pallidal endogenous GABAA neurotransmission in the treatment of Parkinson's disease

    Learn-to-Decompose: Cascaded Decomposition Network for Cross-Domain Few-Shot Facial Expression Recognition

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    Most existing compound facial expression recognition (FER) methods rely on large-scale labeled compound expression data for training. However, collecting such data is labor-intensive and time-consuming. In this paper, we address the compound FER task in the cross-domain few-shot learning (FSL) setting, which requires only a few samples of compound expressions in the target domain. Specifically, we propose a novel cascaded decomposition network (CDNet), which cascades several learn-to-decompose modules with shared parameters based on a sequential decomposition mechanism, to obtain a transferable feature space. To alleviate the overfitting problem caused by limited base classes in our task, a partial regularization strategy is designed to effectively exploit the best of both episodic training and batch training. By training across similar tasks on multiple basic expression datasets, CDNet learns the ability of learn-to-decompose that can be easily adapted to identify unseen compound expressions. Extensive experiments on both in-the-lab and in-the-wild compound expression datasets demonstrate the superiority of our proposed CDNet against several state-of-the-art FSL methods

    Tunable Unidirectional Sound Propagation through a Sonic-Crystal-Based Acoustic Diode

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    Nonreciprocal wave propagation typically requires strong nonlinear materials to break time reversal symmetry. Here, we utilized a sonic-crystal-based acoustic diode that had broken spatial inversion symmetry and experimentally realized sound unidirectional transmission in this acoustic diode. These novel phenomena are attributed to different mode transitions as well as their associated different energy conversion efficiencies among different diffraction orders at two sides of the diode. This nonreciprocal sound transmission could be systematically controlled by simply mechanically rotating the square rods of the sonic crystal. Different from nonreciprocity due to the nonlinear acoustic effect and broken time reversal symmetry, this new model leads to a one-way effect with higher efficiency, broader bandwidth, and much less power consumption, showing promising applications in various sound devices

    Investigating the Dialogic Interaction Between Multilingual Students and a Writing Instructor in Higher Education

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    Dialogic teaching has significant implications in the field of educational science that deem to provoke in-depth exploratory learning and respectful classroom relations. The aim of this study is to shed light on the reciprocal and collaborative dialogic interactions–how do students influence instructor's pedagogies and teaching practices–within the context of an ESL academic writing class at UIUC. Qualitative data was periodically collected through naturalistic classroom observations over the course of one semester and reflective interviews with the students and instructor. The results suggest that students play a crucial role in impacting the instructor’s teaching pedagogies and practices, but the effects are only acknowledged to a limited extent because of the complexity of the roles of students and teacher.Office of Undergraduate Research UIUCOpe
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