13,122 research outputs found
The effect of cigarette price increase on the cigarette consumption in Taiwan: evidence from the National Health Interview Surveys on cigarette consumption
BACKGROUND: This study uses cigarette price elasticity to evaluate the effect of a new excise tax increase on cigarette consumption and to investigate responses from various types of smokers. METHODS: Our sample consisted of current smokers between 17 and 69 years old interviewed during an annual face-to-face survey conducted by Taiwan National Health Research Institutes between 2000 to 2003. We used Ordinary Least Squares (OLS) procedure to estimate double logarithmic function of cigarette demand and cigarette price elasticity. RESULTS: In 2002, after Taiwan had enacted the new tax scheme, cigarette price elasticity in Taiwan was found to be -0.5274. The new tax scheme brought about an average annual 13.27 packs/person (10.5%) reduction in cigarette consumption. Using the cigarette price elasticity estimate from -0.309 in 2003, we calculated that if the Health and Welfare Tax were increased by another NT$ 3 per pack and cigarette producers shifted this increase to the consumers, cigarette consumption would be reduced by 2.47 packs/person (2.2%). The value of the estimated cigarette price elasticity is smaller than one, meaning that the tax will not only reduce cigarette consumption but it will also generate additional tax revenues. Male smokers who had no income or who smoked light cigarettes were found to be more responsive to changes in cigarette price. CONCLUSIONS: An additional tax added to the cost of cigarettes would bring about a reduction in cigarette consumption and increased tax revenues. It would also help reduce incidents smoking-related illnesses. The additional tax revenues generated by the tax increase could be used to offset the current financial deficiency of Taiwan's National Health Insurance program and provide better public services
A probability density function generator based on neural networks
© 2019 Elsevier B.V. In order to generate a probability density function (PDF) for fitting the probability distributions of practical data, this study proposes a deep learning method which consists of two stages: (1) a training stage for estimating the cumulative distribution function (CDF) and (2) a performing stage for predicting the corresponding PDF. The CDFs of common probability distributions can be utilised as activation functions in the hidden layers of the proposed deep learning model for learning actual cumulative probabilities, and the differential equation of the trained deep learning model can be used to estimate the PDF. Numerical experiments with single and mixed distributions are conducted to evaluate the performance of the proposed method. The experimental results show that the values of both CDF and PDF can be precisely estimated by the proposed method
A note on Makeev's conjectures
A counterexample is given for the Knaster-like conjecture of Makeev for
functions on . Some particular cases of another conjecture of Makeev, on
inscribing a quadrangle into a smooth simple closed curve, are solved
positively
Introduction to the special issue: Applications of internet of things
© 2018 by the authors. This editorial introduces the special issue, entitled "Applications of Internet of Things", of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. Four papers on sensing techniques and applications are included as follows: (1) "Reliability of improved cooperative communication over wireless sensor networks", by Chen et al.; (2) "User classification in crowdsourcing-based cooperative spectrum sensing", by Zhai andWang; (3) "IoT's tiny steps towards 5G: Telco's perspective", by Cero et al.; and (4) "An Internet of things area coverage analyzer (ITHACA) for complex topographical scenarios", by Parada et al. One paper on data science techniques and applications is as follows: "Internet of things: a scientometric review", by Ruiz-Rosero et al. Two papers on smart transportation are as follows: (1) "An Internet of things approach for extracting featured data using an AIS database: an application based on the viewpoint of connected ships", by He et al.; and (2) "The development of key technologies in applications of vessels connected to the Internet", by Tian et al. Two papers on smart home are as follows: (1) "A novel approach based on time cluster for activity recognition of daily living in smart homes", by Liu et al.; and (2) "IoT-based image recognition system for smart home-delivered meal services", by Tseng et al
Towards direct laser writing of actively tuneable three-dimensional photonic crystals
3D printing and actively switchable redox‐active oligo(aniline)‐based materials are combined to create novel tuneable 3D photonic materials. By a direct laser writing process, switchable functional structures with submicrometer features are fabricated. Reversible changes in the refractive index of the written materials are generated with negligible size changes
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Imaging the lithosphere beneath NE Tibet: Teleseismic P and S body wave tomography incorporating surface wave starting models
The northeastern margin of the Tibetan Plateau, which includes the Qiangtang and Songpan-Ganzi terranes as well as the Kunlun Shan and the Qaidam Basin, continues to deform in response to the ongoing India–Eurasia collision. To test competing hypotheses concerning the mechanisms for this deformation, we assembled a high-quality data set of approximately 14 000 P- and 4000 S-wave arrival times from earthquakes at teleseismic distances from the International Deep Profiling of Tibet and the Himalaya, Phase IV broad-band seismometer deployments. We analyse these arrival times to determine tomographic images of P- and S-wave velocities in the upper mantle beneath this part of the plateau. To account for the effects of major heterogeneity in crustal and uppermost mantle wave velocities in Tibet, we use recent surface wave models to construct a starting model for our teleseismic body wave inversion. We compare the results from our model with those from simpler starting models, and find that while the reduction in residuals and results for deep structure are similar between models, the results for shallow structure are different. Checkerboard tests indicate that features of ~125km length scale are reliably imaged throughout the study region. Using synthetic tests, we show that the best recovery is below ~300km, and that broad variations in shallow structure can also be recovered. We also find that significant smearing can occur, especially at the edges of the model. We observe a shallow dipping seismically fast structure at depths of ~140–240km, which dies out gradually between 33°N and 35°N. Based on the lateral continuity of this structure (from the surface waves) we interpret it as Indian lithosphere. Alternatively, the entire area could be thickened by pure shear, or the northern part could be an underthrust Lhasa Terrane lithospheric slab with only the southern part from India. We see a deep fast wave velocity anomaly (below 300?km), that is consistent with receiver function observations of a thickened transition zone and could be a fragment of oceanic lithosphere. In NE Tibet, it appears to be disconnected from faster wave velocities above (i.e. it is not downwelling or subducting here). Our models corroborate results of previous work which imaged a relatively slow wave velocity region below the Kunlun Shan and northern Songpan-Ganzi Terrane, which is difficult to reconcile with the hypothesis of southward-directed continental subduction at the northern margin. Wave velocities in the shallow mantle beneath the Qaidam Basin are faster than normal, and more so in the east than the west.This work was supported by a Natural Environment Research Council studentship
(grant NE/H52449X/1)This version of record of this article can be found in Geophysical Journal International (March, 2014) 196 (3): 1724-1741. doi: 10.1093/gji/ggt47
Structural and magnetic phase diagram of CeFeAsO1-xFx and its relationship to high-temperature superconductivity
We use neutron scattering to study the structural and magnetic phase
transitions in the iron pnictides CeFeAsO1-xFx as the system is tuned from a
semimetal to a high-transition-temperature (high-Tc) superconductor through
Fluorine (F) doping x. In the undoped state, CeFeAsO develops a structural
lattice distortion followed by a stripe like commensurate antiferromagnetic
order with decreasing temperature. With increasing Fluorine doping, the
structural phase transition decreases gradually while the antiferromagnetic
order is suppressed before the appearance of superconductivity, resulting an
electronic phase diagram remarkably similar to that of the high-Tc copper
oxides. Comparison of the structural evolution of CeFeAsO1-xFx with other
Fe-based superconductors reveals that the effective electronic band width
decreases systematically for materials with higher Tc. The results suggest that
electron correlation effects are important for the mechanism of high-Tc
superconductivity in these Fe pnictides.Comment: 19 pages, 5 figure
Limit points of eigenvalues of (di)graphs
The study on limit points of eigenvalues of undirected graphs was initiated by A. J. Hoffman in 1972. Now we extend the study to digraphs. We prove: 1. Every real number is a limit point of eigenvalues of graphs. Every complex number is a limit point of eigenvalues of digraphs. 2. For a digraph D, the set of limit points of eigenvalues of iterated subdivision digraphs of D is the unit circle in the complex plane if and only if D has a directed cycle. 3. Every limit point of eigenvalues of a set D of digraphs (graphs) is a limit point of eigenvalues of a set of bipartite digraphs (graphs), where consists of the double covers of the members in D. 4. Every limit point of eigenvalues of a set D of digraphs is a limit point of eigenvalues of line digraphs of the digraphs in D. 5. If M is a limit point of the largest eigenvalues of graphs, then -M is a limit point of the smallest eigenvalues of graphs
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