Volatility spillover between New Zealand stock market returns and exchange rate changes before and after the 1997 Asian financial crisis

Researchers in the last decade have been investigating the interdependence of stock returns and exchange rate changes within the same economy. Kanas (2000) and Yang and Doong (2004) find that for the G-7 countries, in general, the volatility of the stock market spills over to the exchange rate market but that volatility spillovers from the exchange rate market to the stock market are insignificant. Chen, Naylor, and Lu (2004) find that NZ individual firm returns are significantly exposed to exchange rate changes. This study complements their work by investigating the volatility spillover between the stock market and the foreign exchange market within the NZ economy.<br /

Part-Based Deep Hashing for Large-Scale Person Re-Identification

© 1992-2012 IEEE. Large-scale is a trend in person re-identi-fication (re-id). It is important that real-time search be performed in a large gallery. While previous methods mostly focus on discriminative learning, this paper makes the attempt in integrating deep learning and hashing into one framework to evaluate the efficiency and accuracy for large-scale person re-id. We integrate spatial information for discriminative visual representation by partitioning the pedestrian image into horizontal parts. Specifically, Part-based Deep Hashing (PDH) is proposed, in which batches of triplet samples are employed as the input of the deep hashing architecture. Each triplet sample contains two pedestrian images (or parts) with the same identity and one pedestrian image (or part) of the different identity. A triplet loss function is employed with a constraint that the Hamming distance of pedestrian images (or parts) with the same identity is smaller than ones with the different identity. In the experiment, we show that the proposed PDH method yields very competitive re-id accuracy on the large-scale Market-1501 and Market-1501+500K datasets

Structural and Magnetic Properties of Trigonal Iron

First principles calculations of the electronic structure of trigonal iron were performed using density function theory. The results are used to predict lattice spacings, magnetic moments and elastic properties; these are in good agreement with experiment for both the bcc and fcc structures. We find however, that in extracting these quantities great care must be taken in interpreting numerical fits to the calculated total energies. In addition, the results for bulk iron give insight into the properties of thin iron films. Thin films grown on substrates with mismatched lattice constants often have non-cubic symmetry. If they are thicker than a few monolayers their electronic structure is similar to a bulk material with an appropriately distorted geometry, as in our trigonal calculations. We recast our bulk results in terms of an iron film grown on the (111) surface of an fcc substrate, and find the predicted strain energies and moments accurately reflect the trends for iron growth on a variety of substrates.Comment: 11 pages, RevTeX,4 tar'd,compressed, uuencoded Postscript figure

Magnetospheric ULF waves with increasing amplitude related to solar wind dynamic pressure changes: The Time History of Events and Macroscale Interactions during Substorms (THEMIS) observations

Ultralow frequency (ULF) waves play an important role in transferring energy by buffeting the magnetosphere with solar wind pressure impulses. The amplitudes of magnetospheric ULF waves, which are induced by solar wind dynamic pressure enhancements or shocks, are thought to damp in one half a wave cycle or an entire wave cycle. We report in situ observations of solar wind dynamic pressure impulse‐induced magnetospheric ULF waves with increasing amplitudes. We found six ULF wave events induced by solar wind dynamic pressure enhancements with slow but clear wave amplitude increase. During three or four wave cycles, the amplitudes of ion velocities and electric field of these waves increased continuously by 1.3–4.4 times. Two significant events were selected to further study the characteristics of these ULF waves. We found that the wave amplitude growth is mainly contributed by the toroidal mode wave. Three possible mechanisms of causing the wave amplitude increase are discussed. First, solar wind dynamic pressure perturbations, which are observed in a duration of 20–30 min, might transfer energy to the magnetospheric ULF waves continually. Second, the wave amplitude increase in the radial electric field may be caused by superposition of two wave modes, a standing wave excited by the solar wind dynamic impulse and a propagating compressional wave directly induced by solar wind oscillations. When superposed, the two wave modes fit observations as does a calculation that superposes electric fields from two wave sources. Third, the normal of the solar wind discontinuity is at an angle to the Sun‐Earth line. Thus, the discontinuity will affect the dayside magnetopause continuously for a long time.Key PointsSix Psw enhancement‐induced ULF waves with increasing amplitudes were observedThe wave amplitude could increase four times in several wave periodsSuperposition of two wave modes could cause the wave amplitude increasePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115986/1/jgra52015_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/115986/2/jgra52015.pd

An Enhanced Tilted-Angle Acoustofluidic Chip for Cancer Cell Manipulation

In recent years, surface acoustic wave (SAW) devices have demonstrated great potentials and increasing applications in the manipulation of nano- and micro-particles including biological cells with the advantages of label-free, high sensitivity and accuracy. In this letter, we introduce a novel tilted-angle SAW devices to optimise the acoustic pressure inside a microchannel for cancer-cell manipulation. The SAW generation and acoustic radiation force are improved by seamlessly patterning electrodes in the space surrounding the microchannel. Comparisons between this novel SAW device and a conventional device show a 32% enhanced separation efficiency while the input power, manufacturing cost and fabrication effort remain the same. Effective separation of HeLa cancer cells from peripheral blood mononuclear cells is demonstrated. This novel SAW device has the advantages in minimizing device power consumption, lowering component footprint and increasing device density.This work was supported by the Natural Science Basic Research Program of Shaanxi Province (2020JQ-233); Fundamental Scientific Research of Central Universities (grant number 3102017OQD116); the Engineering and Physical Sciences Research Council (EPSRC) (EP/P002803/1 and EP/P018998/1); and the Royal Society (IEC/NSFC/170142, IE161019)

An Enhanced Tilted-Angle Acoustofluidic Chip for Cancer Cell Manipulation

In recent years, surface acoustic wave (SAW) devices have demonstrated great potentials and increasing applications in the manipulation of nano- and micro-particles including biological cells with the advantages of label-free, high sensitivity and accuracy. In this letter, we introduce a novel tilted-angle SAW devices to optimise the acoustic pressure inside a microchannel for cancer-cell manipulation. The SAW generation and acoustic radiation force are improved by seamlessly patterning electrodes in the space surrounding the microchannel. Comparisons between this novel SAW device and a conventional device show a 32% enhanced separation efficiency while the input power, manufacturing cost and fabrication effort remain the same. Effective separation of HeLa cancer cells from peripheral blood mononuclear cells is demonstrated. This novel SAW device has the advantages in minimizing device power consumption, lowering component footprint and increasing device density.This work was supported by the Natural Science Basic Research Program of Shaanxi Province (2020JQ-233); Fundamental Scientific Research of Central Universities (grant number 3102017OQD116); the Engineering and Physical Sciences Research Council (EPSRC) (EP/P002803/1 and EP/P018998/1); and the Royal Society (IEC/NSFC/170142, IE161019)

The Productions and Strong Decays of Dq(2S)D_q(2S) and Bq(2S)B_q(2S)

We study the productions of first radial excited states $D_q(2S)$ ($q=u, d, s$) and $B_q(2S)$ in exclusive semi-leptonic $B_{q'}$ ($q'=u, d s, c$) decays by the improved Bethe-Salpeter method. These 2S states can be detected through their strong decays to ground mesons, where the strong decays are calculated by the low energy approximation as well as the impulse approximation. Some channels have ratios of order $10^{-4}$: $Br(B^+\to\bar D^0(2S)\ell^+{\nu_\ell})\times Br(\bar D^0(2S)\to \bar D^{*}\pi)\approx(4.9\pm4.0)\times10^{-4}$, $Br(B^0\to D^-(2S)\ell^+{\nu_\ell})\times Br(D^-(2S)\to \bar D^{*}\pi)\approx(4.4\pm3.4)\times10^{-4}$. These channels could be measured by the current B-factories. For $D_s(2S)$, we also obtain a relative large ratio: $Br(B_s^0\to D_s^-(2S)\ell^+{\nu_\ell})\times Br(D_s^-(2S)\to \bar D^{*}\bar K)\approx (9.9\pm14.9)\times10^{-4}$. Although there are discrepancies of the full decay width between the theoretical predictions of ${D}^0(2S)$ and experimental results of $D(2550)^0$, the new detected state $D(2550)^0$ is very likely the ${D}^0(2S)$ state.Comment: 22 pages, 5 figures, 5 table

Deep learning radiomic nomogram can predict the number of lymph node metastasis in locally advanced gastric cancer: an international multi-center study.

BACKGROUND: Preoperative evaluation of the number of lymph node metastasis (LNM) is the basis of individual treatment of locally advanced gastric cancer (LAGC). However, the routinely used preoperative determination method is not accurate enough. PATIENTS AND METHODS: We enrolled 730 LAGC patients from 5 centers in China and 1 center in Italy, and divided them into 1 primary cohort, 3 external validation cohorts, and 1 international validation cohort. A deep learning radiomic nomogram (DLRN) was built based on the images from multi-phase computed tomography (CT) for preoperatively determining the number of LNM in LAGC. We comprehensively tested the DLRN and compared it with three state-of-the-art methods. Moreover, we investigated the value of the DLRN in survival analysis. RESULTS: The DLRN showed good discrimination of the number of LNM on all cohorts (overall C-indexes: 0.821, 95% CI: 0.785-0.858 in the primary cohort; 0.797, 95% CI: 0.771-0.823 in the external validation cohorts; and 0.822, 95% CI: 0.756-0.887 in the international validation cohort). The nomogram performed significantly better than the routinely used clinical N stages, tumor size, and clinical model (p<0.05). Besides, DLRN is significantly associated with the overall survival of LAGC patients (n=271). CONCLUSION: A deep learning-based radiomic nomogram had good predictive value for LNM in LAGC. In staging-oriented treatment of gastric cancer, this preoperative nomogram could provide baseline information for individual treatment of LAGC