MoS2 Dual-Gate MOSFET with Atomic-Layer-Deposited Al2O3 as Top-Gate Dielectric

We demonstrate atomic-layer-deposited (ALD) high-k dielectric integration on two-dimensional (2D) layer-structured molybdenum disulfide (MoS2) crystals and MoS2 dual-gate n-channel MOSFETs with ALD Al2O3 as top-gate dielectric. Our C-V study of MOSFET structures shows good interface between 2D MoS2 crystal and ALD Al2O3. Maximum drain currents using back-gates and top-gates are measured to be 7.07mA/mm and 6.42mA/mm at Vds=2V with a channel width of 3 {\mu}m, a channel length of 9 {\mu}m, and a top-gate length of 3 {\mu}m. We achieve the highest field-effect mobility of electrons using back-gate control to be 517 cm^2/Vs. The highest current on/off ratio is over 10^8.Comment: submitted to IEEE Electron Device Letter

The Inuence of Misspecified Covariance on False Discovery Control when Using Posterior Probabilities

This paper focuses on the influence of a misspecified covariance structure on false discovery rate for the large scale multiple testing problem. Specifically, we evaluate the influence on the marginal distribution of local fdr statistics, which are used in many multiple testing procedures and related to Bayesian posterior probabilities. Explicit forms of the marginal distributions under both correctly specified and incorrectly specified models are derived. The Kullback-Leibler divergence is used to quantify the influence caused by a misspecification. Several numerical examples are provided to illustrate the influence. A real spatio-temporal data on soil humidity is discussed.Comment: 22 pages, 5 figure

A Critical Review of Recent Progress on Negative Capacitance Field-Effect Transistors

The elegant simplicity of the device concept and the urgent need for a new "transistor" at the twilight of Moore's law have inspired many researchers in industry and academia to explore the physics and technology of negative capacitance field effect transistor (NC-FET). Although hundreds of papers have been published, the validity of quasi-static NC and the frequency-reliability limits of NC-FET are still being debated. The concept of NC - if conclusively demonstrated - will have broad impacts on device physics and technology development. Here, the authors provide a critical review of recent progress on NC-FETs research and some starting points for a coherent discussion.Comment: 19 pages, 2 figure

Atomic-Layer-Deposited Al2O3 on Bi2Te3 for Topological Insulator Field-Effect Transistors

We report dual-gate modulation of topological insulator field-effect transistors (TI FETs) made on Bi2Te3 thin flakes with integration of atomic-layer-deposited (ALD) Al2O3 high-k dielectric. Atomic force microscopy study shows that ALD Al2O3 is uniformly grown on this layer-structured channel material. Electrical characterization reveals that the right selection of ALD precursors and the related surface chemistry play a critical role in device performance of Bi2Te3 based TI FETs. We realize both top-gate and bottom-gate control on these devices, and the highest modulation rate of 76.1% is achieved by using simultaneous dual gate control.Comment: 4 pages, 3 figure

Progress in strain monitoring of tapestries

This paper reports interdisciplinary research between conservators and engineers designed to enhance the long-term conservation of tapestries (tapestry-weave hangings) on longterm display. The aim is to monitor, measure and document the strain experienced by different areas of a tapestry while it is hanging on display. Initial research has established that damage can be identified in the early stages of its inception, i.e., before it is visible to the naked eye. The paper also reports initial results of strain data visualisation that allows curators and conservators to examine how strain develops, thereby facilitating predictions about the changes in the form or condition of the tapestry. Strain data visualisation also allows the strain process to be recorded, thereby facilitating the effective documentation of display methods and conservation interventions. The paper reports the use of point measurements (using silica optical fibre sensors) and full-field monitoring (using 3-D photogrammetry with digital image correlation (DIC))

Optimizing the management of financial flows based on assessment of regional multiplier effects

This article examines the issues of improving the effectiveness in the management of regional financial flows. As their main hypothesis, the authors provide a rationale for the argument that the management of regional financial flows must be optimized on the basis of multiplier economic effects that allow to better assess the performance of regional socio-economic policy. The article presents a multifactor model for managing the financial flows at the regional level, or the matrix of financial flows based on the principles of general economic equilibrium theory, Input—Output balancing method and methodology of national accounts system. The consolidated budgetary balance sheet of the region is presented as an important structural element of the model. A methodology has been developed for integrating the consolidated budgetary balance sheet of the region in the matrix of financial flows. By using the example of individual subjects of the Russian Federation, the authors calculated the matrix multipliers of consolidated budgetary balance sheet that allow to simulate the multiplier economic effects resulting from the impact of different types of exogenous economic factors on the development of regions, and to forecast the impact of changes in the fiscal reallocation on GRP and household income, assess the impact of external investment on the economic growth of the regions and study the effectiveness of federal tax policy at the regional level. The article demonstrates that the value of multiplier effect depends on several factors, including the external trade relations of the region, its dependence on imports, the share of value added in gross output, as well as the propensity of households to savings. The approach proposed by the authors can be used by the government authorities at different levels in the development of their strategies of socio-economic development, assessment of the extent and areas of impact made by various exogenous factors on the economy of the region, as well as in the analysis of the investment initiatives of the private sector seeking the financial support for its projects from the state. The authors propose the areas for improving the management of financial flows based on maximizing the multiplier economic effects in the short and medium term for the regions with a different level of fiscal capacity.The article has been prepared with the support of the Grant of the Russian Foundation for Humanities (project №15–02–00587)

Complex Unitary Recurrent Neural Networks using Scaled Cayley Transform

Recurrent neural networks (RNNs) have been successfully used on a wide range of sequential data problems. A well known difficulty in using RNNs is the \textit{vanishing or exploding gradient} problem. Recently, there have been several different RNN architectures that try to mitigate this issue by maintaining an orthogonal or unitary recurrent weight matrix. One such architecture is the scaled Cayley orthogonal recurrent neural network (scoRNN) which parameterizes the orthogonal recurrent weight matrix through a scaled Cayley transform. This parametrization contains a diagonal scaling matrix consisting of positive or negative one entries that can not be optimized by gradient descent. Thus the scaling matrix is fixed before training and a hyperparameter is introduced to tune the matrix for each particular task. In this paper, we develop a unitary RNN architecture based on a complex scaled Cayley transform. Unlike the real orthogonal case, the transformation uses a diagonal scaling matrix consisting of entries on the complex unit circle which can be optimized using gradient descent and no longer requires the tuning of a hyperparameter. We also provide an analysis of a potential issue of the modReLU activiation function which is used in our work and several other unitary RNNs. In the experiments conducted, the scaled Cayley unitary recurrent neural network (scuRNN) achieves comparable or better results than scoRNN and other unitary RNNs without fixing the scaling matrix