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Exploring Technology Evolution in the Solar Cell Field: An Aspect from Patent Analysis

.e., patent or literature citation) for each of the retrieved patents were then downloaded. 2.2 Step 2. Build a Patent Network Using Text Similarities This study utilized text-based document analysis to measure similarities among documents. Documents with a significant impact were identified through the following steps: collecting the titles and abstracts of a patent set, extracting the term vectors of each document through lower case conversion, removing numbers and punctuation, singularizing and synonymizing the text, eliminating stop words, and forming l -level

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Systematic Review and Meta-Analysis on Proximal-to-Distal Sequencing in Team Handball: Prospects for Talent Detection?

kinematic variables exist ( Serrien et al., 2015 ), the timing seems again to be relatively equal between male and female players ( van den Tillaar and Cabri, 2012 ). The sequence is not always strictly proximal-to-distal (elbow before shoulder; for a review see Marshall and Elliot, 2000 ) and task specific adaptations occur. However, overall, the evidence seems to point towards the proximal-to-distal sequence being a relatively invariant characteristic of throwing motions in experienced players. Therefore, talent identification programs may potentially benefit from

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Nonlinear waves in a simple model of high-grade glioma

\mathscr{W}(\mathscr{V}_{m}) \lt 0. \end{array}$$ (17) Therefore, as 𝓦(1) > 0, the existence of a value 𝓥 – in the interval (𝓥 m , 1), such that 𝓦(𝓥 – ) = 0, follows from a direct application of Bolzano’s Intermediate Value Theorem. Moreover, it is straightforward to verify that no orbits can cross the triangle T , given by 0 ≤ V ≤ 1 , β ( V − 1 ) ≤ W ≤ 0 , $$\begin{array}{} \displaystyle 0\leq \mathscr{V}\leq 1,\quad \beta(\mathscr{V}-1) \leq\mathscr{W}\leq 0, \end{array}$$ (18) from the outside. Therefore, T is a negative invariant region. Thus

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Deterministic chaos in pendulum systems with delay

based on analysis and processing of spectrum of Lyapunov characteristic exponents [ 5 , 8 ]. Where necessary, for more accurate determination of steady-state regime of the system, we study other characteristics of attractors: phase portraits, Poincare sections and maps, Fourier spectrums and distributions of the invariant measure. Let us consider the behavior of the systems (4) and (5) when the parameters are C = ‒ 0 :1, D = ‒ 0 :53, E = ‒ 0 :59, F = ‒ 0 :4. The map of dynamical regimes in fig. 1 (a) was built for three-dimensional model (4) and the

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Analysis of crack propagation in a “pull-out” test

compression test performed on the same samples. Photograph from these tests are shown in Fig. 4 . On the left side, the displacement sensor is visible, which measures the vertical deformations, and on the right side, there is the extensometer that measures the horizontal deformations. It is mounted on steel plates glued to the opposite sides of samples. Figure 4 Compression with extensometer test. The Young modulus was calculated from the below equation: (3.1) E = h ⋅ κ A $$E=\frac{h\cdot \kappa }{A}$$ where, h is the

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Parents with an Unemployed Adult Child: Consumption, Income, and Savings Effects

distribution of insurance in an economy. In this paper, we directly approach the potential costs, inefficiencies, and inequities of aiding family members. We examine parental behavior in the year that an adult, non-residential child experiences an unemployment spell. Using the 1985-2013 waves ofthe Panel Study on Income Dynamics, a longitudinal dataset that allows for parent-child linkages across households within the same wave of the survey, we measure the concurrent changes to the parent’s consumption, income, and savings during child’s unemployment. Due to quality

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Three-dimensional pulmonary monitoring using focused electrical impedance measurements

not related to either human or animals use. Focusing of Tetrapolar Impedance Measurements In bioimpedance measurements, a tetrapolar electrode setup is typically used to measure an electrical impedance. In this setup, two electrodes are used to inject a small, alternating current into the body while two separate electrodes are measuring the resulting voltage drop across those electrodes. In contrast to impedance-based imaging techniques such as Electrical Impedance Tomography, where multiple measurements are performed at different electrode locations, single

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Operations of Nanostructures via SDD, ABC 4 and GA 5 indices

T 1 ( G ) are adjacent if and only if ( i ) they are adjacent edges of G or ( ii ) one is a vertex of G and the other is an edge of G incident to that vertex (see also [ 19 ]). The idea of a topological index first appears in the work of H. Wiener in 1947, [ 27 ], in which he was working on boiling points of paraffins. He called this index as path number, and later it was called as Wiener index. Since then, the theory of topological indices has begun to have great importance as the topological indices are the mathematical measures which correspond to the

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Magnetic induction pneumography: a planar coil system for continuous monitoring of lung function via contactless measurements

pneumography (MIP). In MIP, the data are acquired by successively exciting each coil in order to induce an eddy-current density within the dorsal tissues and measuring the corresponding response magnetic field strength by the remaining coils. The recorded set of data is then used to reconstruct the internal conductivity distribution by means of algorithms that minimize the residual norm of the difference between the estimated and measured data [ 9 ]. Regularization methods are typically applied to stabilize the image reconstruction process [ 10 ]. To simulate the

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Global Attractor for Nonlinear Wave Equations with Critical Exponent on Unbounded Domain

\end{array}$ . Definition 3 Let F be a semiflow on X . A set 𝒜 ⊂ X is called a global attractor for Φ, if the following conditions are satisfied: (i) 𝒜 is a compact and invariant set in the sense that Φ( t, 𝒜 ) = 𝒜 , for all t ≥ 0. (iii) 𝒜 attracts every bounded set B in X , lim t → ∞ d i s t X ( Φ ( t , B ) , A ) = 0 , $$\begin{array}{} \displaystyle \mathop {\lim }\limits_{t \to \infty } dis{t_X}(\Phi (t,B),{\mathscr A}) = 0, \end{array}$$ where dist X ( ·,· ) is the Hausdorff semi-distance with respect to the X -norm

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