Modelling the Volatility in Short and Long Haul Japanese Tourist Arrivals to New Zealand and Taiwan

This paper estimates the effects of short and long haul volatility (or risk) in monthly Japanese tourist arrivals to Taiwan and New Zealand, respectively. In order to model appropriately the volatilities of international tourist arrivals, we use symmetric and asymmetric conditional volatility models that are commonly used in financial econometrics, namely the GARCH (1,1), GJR (1,1) and EGARCH (1,1) models. The data series are for the period January 1997 to December 2007. The volatility estimates for the monthly growth in Japanese tourists to New Zealand and Taiwan are different, and indicate that the former has an asymmetric effect on risk from positive and negative shocks of equal magnitude, while the latter has no asymmetric effect. Moreover, there is a leverage effect in the monthly growth rate of Japanese tourists to New Zealand, whereby negative shocks increase volatility but positive shocks of similar magnitude decrease volatility. These empirical results seem to be similar to a wide range of financial stock market prices, so that the models used in financial economics, and hence the issues related to risk and leverage effects, are also applicable to international tourism flows

Graph inductive biases in transformers without message passing

Transformers for graph data are increasingly widely studied and successful in numerous learning tasks. Graph inductive biases are crucial for Graph Transformers, and previous works incorporate them using message-passing modules and/or positional encodings. However, Graph Transformers that use message-passing inherit known issues of message-passing, and differ significantly from Transformers used in other domains, thus making transfer of research advances more difficult. On the other hand, Graph Transformers without message-passing often perform poorly on smaller datasets, where inductive biases are more important. To bridge this gap, we propose the Graph Inductive bias Transformer (GRIT) — a new Graph Transformer that incorporates graph inductive biases without using message passing. GRIT is based on several architectural changes that are each theoretically and empirically justified, including: learned relative positional encodings initialized with random walk probabilities, a flexible attention mechanism that updates node and node-pair representations, and injection of degree information in each layer. We prove that GRIT is expressive — it can express shortest path distances and various graph propagation matrices. GRIT achieves state-of-the-art empirical performance across a variety of graph datasets, thus showing the power that Graph Transformers without message-passing can deliver

Polarimetric clutter modeling: Theory and application

The two-layer anisotropic random medium model is used to investigate fully polarimetric scattering properties of earth terrain media. The polarization covariance matrices for the untilted and tilted uniaxial random medium are evaluated using the strong fluctuation theory and distorted Born approximation. In order to account for the azimuthal randomness in the growth direction of leaves in tree and grass fields, an averaging scheme over the azimuthal direction is also applied. It is found that characteristics of terrain clutter can be identified through the analysis of each element of the covariance matrix. Theoretical results are illustrated by the comparison with experimental data provided by MIT Lincoln Laboratory for tree and grass fields

Influence of the Fermi Surface Morphology on the Magnetic Field-Driven Vortex Lattice Structure Transitions in YBa2_{2}Cu3_{3}O7−δ:δ=_{7-\delta}:\delta=0, 0.15

We report small-angle neutron scattering measurements of the vortex lattice (VL) structure in single crystals of the lightly underdoped cuprate superconductor YBa2Cu3O6.85. At 2 K, and for fields of up to 16 T applied parallel to the crystal c-axis, we observe a sequence of field-driven and first-order transitions between different VL structures. By rotating the field away from the c-axis, we observe each structure transition to shift to either higher or lower field dependent on whether the field is rotated towards the [100] or [010] direction. We use this latter observation to argue that the Fermi surface morphology must play a key role in the mechanisms that drive the VL structure transitions. Furthermore, we show this interpretation is compatible with analogous results obtained previously on lightly overdoped YBa2Cu3O7. In that material, it has long-been suggested that the high field VL structure transition is driven by the nodal gap anisotropy. In contrast, the results and discussion presented here bring into question the role, if any, of a nodal gap anisotropy on the VL structure transitions in both YBa2Cu3O6.85 and YBa2Cu3O7

Additive and multiplicative hazards modeling for recurrent event data analysis

<p>Abstract</p> <p>Background</p> <p>Sequentially ordered multivariate failure time or recurrent event duration data are commonly observed in biomedical longitudinal studies. In general, standard hazard regression methods cannot be applied because of correlation between recurrent failure times within a subject and induced dependent censoring. Multiplicative and additive hazards models provide the two principal frameworks for studying the association between risk factors and recurrent event durations for the analysis of multivariate failure time data.</p> <p>Methods</p> <p>Using emergency department visits data, we illustrated and compared the additive and multiplicative hazards models for analysis of recurrent event durations under (i) a varying baseline with a common coefficient effect and (ii) a varying baseline with an order-specific coefficient effect.</p> <p>Results</p> <p>The analysis showed that both additive and multiplicative hazards models, with varying baseline and common coefficient effects, gave similar results with regard to covariates selected to remain in the model of our real dataset. The confidence intervals of the multiplicative hazards model were wider than the additive hazards model for each of the recurrent events. In addition, in both models, the confidence interval gets wider as the revisit order increased because the risk set decreased as the order of visit increased.</p> <p>Conclusions</p> <p>Due to the frequency of multiple failure times or recurrent event duration data in clinical and epidemiologic studies, the multiplicative and additive hazards models are widely applicable and present different information. Hence, it seems desirable to use them, not as alternatives to each other, but together as complementary methods, to provide a more comprehensive understanding of data.</p

Scalloped channels enhance tear mixing under hydrogel contact lenses.

PurposeTear exchange under a soft contact lens is directly related to the amount of lateral and transverse lens motion. Hydrodynamic modeling suggests that channels placed on the back surface of a soft lens will reduce fluid resistance and increase transverse lens movement. This study measured the effect of posterior lens surface scalloped channels on tear exchange.MethodsTear exchange in the postlens tear film (PoLTF) was estimated using a fluorometer to measure the exponential depletion of high-MW fluorescein under the lens expressed as the time to deplete 95% of dye (T95). A total of 32 subjects wore two pairs of identical lenses except that the experimental lens had 12 scalloped channels placed radially in the midperiphery of the posterior lens surface, whereas lenses without channels served as controls.ResultsThe mean +/- standard error T95 values for the channel lenses was 28 +/- 2 minutes compared with 32 +/- 2 minutes for the control lenses (p = 0.107). There was a marginally significant difference in T95 between two lens groups in Asian eyes (p = 0.054).ConclusionPlacing scallop-shaped channels on high-H2O content soft lenses improved the postlens tear pumping in Asian eyes

Relativistic quantum effects of Dirac particles simulated by ultracold atoms

Quantum simulation is a powerful tool to study a variety of problems in physics, ranging from high-energy physics to condensed-matter physics. In this article, we review the recent theoretical and experimental progress in quantum simulation of Dirac equation with tunable parameters by using ultracold neutral atoms trapped in optical lattices or subject to light-induced synthetic gauge fields. The effective theories for the quasiparticles become relativistic under certain conditions in these systems, making them ideal platforms for studying the exotic relativistic effects. We focus on the realization of one, two, and three dimensional Dirac equations as well as the detection of some relativistic effects, including particularly the well-known Zitterbewegung effect and Klein tunneling. The realization of quantum anomalous Hall effects is also briefly discussed.Comment: 22 pages, review article in Frontiers of Physics: Proceedings on Quantum Dynamics of Ultracold Atom

Phase I/II study of S 49076, a MET/AXL/FGFR inhibitor, in combination with gefitinib in EGFR-mutated NSCLC patients who progress on EGFR tyrosine kinase inhibitor

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Observation of Bose-Einstein Condensation in a Strong Synthetic Magnetic Field

Extensions of Berry's phase and the quantum Hall effect have led to the discovery of new states of matter with topological properties. Traditionally, this has been achieved using gauge fields created by magnetic fields or spin orbit interactions which couple only to charged particles. For neutral ultracold atoms, synthetic magnetic fields have been created which are strong enough to realize the Harper-Hofstadter model. Despite many proposals and major experimental efforts, so far it has not been possible to prepare the ground state of this system. Here we report the observation of Bose-Einstein condensation for the Harper-Hofstadter Hamiltonian with one-half flux quantum per lattice unit cell. The diffraction pattern of the superfluid state directly shows the momentum distribution on the wavefuction, which is gauge-dependent. It reveals both the reduced symmetry of the vector potential and the twofold degeneracy of the ground state. We explore an adiabatic many-body state preparation protocol via the Mott insulating phase and observe the superfluid ground state in a three-dimensional lattice with strong interactions.Comment: 6 pages, 5 figures. Supplement: 6 pages, 4 figure

Architectural and biochemical adaptations in skeletal muscle and bone following rotator cuff injury in a rat model

BACKGROUND: Injury to the rotator cuff can cause irreversible changes to the structure and function of the associated muscles and bones. The temporal progression and pathomechanisms associated with these adaptations are unclear. The purpose of this study was to investigate the time course of structural muscle and osseous changes in a rat model of a massive rotator cuff tear. METHODS: Supraspinatus and infraspinatus muscle architecture and biochemistry and humeral and scapular morphological parameters were measured three days, eight weeks, and sixteen weeks after dual tenotomy with and without chemical paralysis via botulinum toxin A (BTX). RESULTS: Muscle mass and physiological cross-sectional area increased over time in the age-matched control animals, decreased over time in the tenotomy+BTX group, and remained nearly the same in the tenotomy-alone group. Tenotomy+BTX led to increased extracellular collagen in the muscle. Changes in scapular bone morphology were observed in both experimental groups, consistent with reductions in load transmission across the joint. CONCLUSIONS: These data suggest that tenotomy alone interferes with normal age-related muscle growth. The addition of chemical paralysis yielded profound structural changes to the muscle and bone, potentially leading to impaired muscle function, increased muscle stiffness, and decreased bone strength. CLINICAL RELEVANCE: Structural musculoskeletal changes occur after tendon injury, and these changes are severely exacerbated with the addition of neuromuscular compromise