Modeling the AgInSbTe Memristor

The AgInSbTe memristor shows gradual resistance tuning characteristics, which makes it a potential candidate to emulate biological plastic synapses. The working mechanism of the device is complex, and both intrinsic charge-trapping mechanism and extrinsic electrochemical metallization effect are confirmed in the AgInSbTe memristor. Mathematical model of the AgInSbTe memristor has not been given before. We propose the flux-voltage controlled memristor model. With piecewise linear approximation technique, we deliver the flux-voltage controlled memristor model of the AgInSbTe memristor based on the experiment data. Our model fits the data well. The flux-voltage controlled memristor model and the piecewise linear approximation method are also suitable for modeling other kinds of memristor devices based on experiment data

Entangling a series of trapped ions by moving cavity bus

Entangling multiple qubits is one of the central tasks for quantum information processings. Here, we propose an approach to entangle a number of cold ions (individually trapped in a string of microtraps) by a moved cavity. The cavity is pushed to include the ions one by one with an uniform velocity, and thus the information stored in former ions could be transferred to the latter ones by such a moving cavity bus. Since the positions of the trapped ions are precisely located, the strengths and durations of the ion-cavity interactions can be exactly controlled. As a consequence, by properly setting the relevant parameters typical multi-ion entangled states, e.g., $W$ state for 10 ions, could be deterministically generated. The feasibility of the proposal is also discussed.Comment: 8 pages, 2 figures, 1 tabl

Up-regulation of CNDP2 facilitates the proliferation of colon cancer

BACKGROUND: Cytosolic nonspecific dipetidase (CN2) belongs to the family of M20 metallopeptidases. It was stated in previous articles that higher expression levels of CN2 were observed in renal cell carcinoma and breast cancer. Our study explored the correlation between CN2 and colon carcinogenesis. METHODS: We analysed the relationship between 183 patients clinicopathological characteristics and its CN2 expression. To detect the levels of CN2 in colon cancer cell lines and colon cancer tissues by western blot. To verify cell proliferation in colon cancer cells with knockdown of CNDP2 and explore the causes of these phenomena. RESULTS: The expression levels of CN2 in clinical colon tumors and colon cancer cell lines were significantly higher than that in normal colon mucosa and colon cell lines. The difference in CN2 levels was associated with tumor location (right- and left-sided colon cancer), but there was no significant association with age, gender, tumor size, tumor grade, tumor stage or serum carcinoembryonic antigen (CEA). Knockdown of CNDP2 inhibited cell proliferation, blocked cell cycle progression and retarded carcinogenesis in an animal model. The signaling pathway through which knockdown of CNDP2 inhibited cell proliferation and tumorigenesis involved in EGFR, cyclin B1 and cyclin E. CONCLUSIONS: Knockdown of CNDP2 can inhibit the proliferation of colon cancer in vitro and retarded carcinogenesis in vivo

Neural network encoded variational quantum algorithms

We introduce a general framework called neural network (NN) encoded variational quantum algorithms (VQAs), or NN-VQA for short, to address the challenges of implementing VQAs on noisy intermediate-scale quantum (NISQ) computers. Specifically, NN-VQA feeds input (such as parameters of a Hamiltonian) from a given problem to a neural network and uses its outputs to parameterize an ansatz circuit for the standard VQA. Combining the strengths of NN and parameterized quantum circuits, NN-VQA can dramatically accelerate the training process of VQAs and handle a broad family of related problems with varying input parameters with the pre-trained NN. To concretely illustrate the merits of NN-VQA, we present results on NN-variational quantum eigensolver (VQE) for solving the ground state of parameterized XXZ spin models. Our results demonstrate that NN-VQE is able to estimate the ground-state energies of parameterized Hamiltonians with high precision without fine-tuning, and significantly reduce the overall training cost to estimate ground-state properties across the phases of XXZ Hamiltonian. We also employ an active-learning strategy to further increase the training efficiency while maintaining prediction accuracy. These encouraging results demonstrate that NN-VQAs offer a new hybrid quantum-classical paradigm to utilize NISQ resources for solving more realistic and challenging computational problems.Comment: 4.4 pages, 5 figures, with supplemental material

The Core Values of Principals in School Management under Chinese Education Reform

The values of principals in school management play a pivotal role in shaping school leadership, teacher behaviours, and student performance. However, research studies focusing on principals’ values are relatively abundant in Western countries, yet still limited in the Chinese context. To fill this gap, this paper adopts a qualitative research approach to investigate the fundamental values of Chinese principals in leading and managing primary schools within the current education reform landscape. The findings reveal that the principals in the study emphasised nine core values: equity, fairness, openness, respect, empowerment, encouragement, recognition, trust, and democracy. These values were found to contribute to a positive school climate that promoted the growth of teachers, students, and the school. The results have significant implications for policy makers and principals in China, suggesting the necessity to foster ethical and relational skills among principals and to acknowledge the invaluable contributions of teacher leaders and teachers in school development. Keywords: principals, values, school management, education reform DOI: 10.7176/JEP/14-24-09 Publication date:August 31st 202

Effects of laser fluence on silicon modification by four-beam laser interference

This paper discusses the effects of laser fluence on silicon modification by four-beam laser interference. In this work, four-beam laser interference was used to pattern single crystal silicon wafers for the fabrication of surface structures, and the number of laser pulses was applied to the process in air. By controlling the parameters of laser irradiation, different shapes of silicon structures were fabricated. The results were obtained with the single laser fluence of 354 mJ/cm, 495 mJ/cm, and 637 mJ/cm, the pulse repetition rate of 10 Hz, the laser exposure pulses of 30, 100, and 300, the laser wavelength of 1064 nm, and the pulse duration of 7-9 ns. The effects of the heat transfer and the radiation of laser interference plasma on silicon wafer surfaces were investigated. The equations of heat flow and radiation effects of laser plasma of interfering patterns in a four-beam laser interference distribution were proposed to describe their impacts on silicon wafer surfaces. The experimental results have shown that the laser fluence has to be properly selected for the fabrication of well-defined surface structures in a four-beam laser interference process. Laser interference patterns can directly fabricate different shape structures for their corresponding applications