PUZZLE - A program for computer-aided design of printed circuit artwork

Program assists in solving spacing problems encountered in printed circuit /PC/ design. It is intended to have maximum use for two-sided PC boards carrying integrated circuits, and also aids design of discrete component circuits

Spin polarization contrast observed in GaAs by force-detected nuclear magnetic resonance

We applied the recently developed technique of force-detected nuclear magnetic resonance (NMR) to observe 71Ga, 69Ga, and 75As in GaAs. The nuclear spin-lattice relaxation time is 21$\pm$5 min for 69Ga at $\sim 5$ K and 4.6 Tesla. We have exploited this long relaxation time to first create and then observe spatially varying nuclear spin polarization within the sample, demonstrating a new form of contrast for magnetic resonance force microscopy (MRFM). Such nuclear spin contrast could be used to indirectly image electron spin polarization in GaAs-based spintronic devices.Comment: 3 pages, 2 figure

Temperature measurement at the end of a cantilever using oxygen paramagnetism in solid air

We demonstrate temperature measurement of a sample attached to the end of a cantilever using cantilever magnetometry of solid air ``contamination'' of the sample surface. In experiments like our Magnetic Resonance Force Microscopy (MRFM), the sample is mounted at the end of a thin cantilever with small thermal conductance. Thus, the sample can be at a significantly different temperature than the bulk of the instrument. Using cantilever magnetometry of the oxygen paramagnetism in solid air provides the temperature of the sample, without any modifications to our MRFM (Magnetic Resonance Force Microscopy) apparatus.Comment: Submitted to J of Applied Physic

Evaluation of Adult Cottonwood Leaf Beetle, \u3ci\u3eChrysomela Scripta\u3c/i\u3e (Coleoptera: Chrysomelidae), Feeding Preference for Hybrid Poplars

Foliage from the Leuce section of Populus was rejected for feeding by Chrysomela scripta adults in a choice test involving 12 hybrid poplar clones. Adults showed a feeding preference for the foliage from the Tacamahaca clones when compared to the Aigeiros clones

Perturbation expansions for a class of singular potentials

Harrell's modified perturbation theory [Ann. Phys. 105, 379-406 (1977)] is applied and extended to obtain non-power perturbation expansions for a class of singular Hamiltonians H = -D^2 + x^2 + A/x^2 + lambda/x^alpha, (A\geq 0, alpha > 2), known as generalized spiked harmonic oscillators. The perturbation expansions developed here are valid for small values of the coupling lambda > 0, and they extend the results which Harrell obtained for the spiked harmonic oscillator A = 0. Formulas for the the excited-states are also developed.Comment: 23 page

Variational analysis for a generalized spiked harmonic oscillator

A variational analysis is presented for the generalized spiked harmonic oscillator Hamiltonian operator H, where H = -(d/dx)^2 + Bx^2+ A/x^2 + lambda/x^alpha, and alpha and lambda are real positive parameters. The formalism makes use of a basis provided by exact solutions of Schroedinger's equation for the Gol'dman and Krivchenkov Hamiltonian (alpha = 2), and the corresponding matrix elements that were previously found. For all the discrete eigenvalues the method provides bounds which improve as the dimension of the basis set is increased. Extension to the N-dimensional case in arbitrary angular-momentum subspaces is also presented. By minimizing over the free parameter A, we are able to reduce substantially the number of basis functions needed for a given accuracy.Comment: 15 pages, 1 figur

A Recurrent Neural Network Survival Model: Predicting Web User Return Time

The size of a website's active user base directly affects its value. Thus, it is important to monitor and influence a user's likelihood to return to a site. Essential to this is predicting when a user will return. Current state of the art approaches to solve this problem come in two flavors: (1) Recurrent Neural Network (RNN) based solutions and (2) survival analysis methods. We observe that both techniques are severely limited when applied to this problem. Survival models can only incorporate aggregate representations of users instead of automatically learning a representation directly from a raw time series of user actions. RNNs can automatically learn features, but can not be directly trained with examples of non-returning users who have no target value for their return time. We develop a novel RNN survival model that removes the limitations of the state of the art methods. We demonstrate that this model can successfully be applied to return time prediction on a large e-commerce dataset with a superior ability to discriminate between returning and non-returning users than either method applied in isolation.Comment: Accepted into ECML PKDD 2018; 8 figures and 1 tabl

Asymptotic iteration method for eigenvalue problems

An asymptotic interation method for solving second-order homogeneous linear differential equations of the form y'' = lambda(x) y' + s(x) y is introduced, where lambda(x) \neq 0 and s(x) are C-infinity functions. Applications to Schroedinger type problems, including some with highly singular potentials, are presented.Comment: 14 page

170 Nanometer Nuclear Magnetic Resonance Imaging using Magnetic Resonance Force Microscopy

We demonstrate one-dimensional nuclear magnetic resonance imaging of the semiconductor GaAs with 170 nanometer slice separation and resolve two regions of reduced nuclear spin polarization density separated by only 500 nanometers. This is achieved by force detection of the magnetic resonance, Magnetic Resonance Force Microscopy (MRFM), in combination with optical pumping to increase the nuclear spin polarization. Optical pumping of the GaAs creates spin polarization up to 12 times larger than the thermal nuclear spin polarization at 5 K and 4 T. The experiment is sensitive to sample volumes containing $\sim 4 \times 10^{11}$ $^{71}$Ga$/\sqrt{Hz}$. These results demonstrate the ability of force-detected magnetic resonance to apply magnetic resonance imaging to semiconductor devices and other nanostructures.Comment: Submitted to J of Magnetic Resonanc

Study of Digital Competence of the Students and Teachers in Ukraine

Professional fulfillment of the personality at the conditions of the digital economy requires the high level of digital competency. One of the ways to develop these competencies is education. However, to provide the implementation of digital education at a high level, the digital competency of the teachers and students is a must. This paper presents explanations on the level determination of the digital competencies for teachers and students in Ukraine according to the DigComp recommendations. We tried to identify the main factors that reflect the degree of readiness teachers and students for digital education based on their self-evaluation. We also attempted to estimate the level of digital competencies based on the analysis of Case-Studies execution results. The complex analysis let us assess the connection between respondents’ self-evaluation and their real competencies. Here we provide a methodology and a model of level competencies determination by means of a survey, expert case rating and the results of the statistical analysis. On the basis of the obtained results, this paper suggests further research prospects and recommendations on the digital competency development in educational institutions in Ukraine