Linear regression estimation using intraday high frequency data

Intraday high frequency data have shown important values in econometric modeling and have been extensively studied. Following this point, in this paper, we study the linear regression model for variables which have intraday high frequency data. In order to overcome the nonstationarity of the intraday data, intraday sequences are aggregated to the daily series by weighted mean. A lower bound for the trace of the asymptotic variance of model estimator is given, and a data-driven method for choosing the weight is also proposed, with the aim to obtain a smaller sum of asymptotic variance for parameter estimators. The simulation results show that the estimation accuracy of the regression coefficient can be significantly improved by using the intraday high frequency data. Empirical studies show that introducing intraday high frequency data to estimate CAPM can have a better model fitting effect

Spin polarization separation of reflected light at Brewster angle

A novel spin polarization separation of reflected light is observed, when a linearly polarized Gaussian beam impinges on an air-glass interface at Brewster angle. In the far-field zone, spins of photons are oppositely polarized in two regions along the direction perpendicular to incident plane. Spatial scale of this polarization is related to optical properties of dielectric and can be controlled by experimental configuration. We believe that this study benefits the manipulation of spins of photons and the development of methods for investigating optical properties of materials.Comment: 4 pages, 2 figure

Variation of polarization distribution of reflected beam caused by spin separation

The variation of polarization distribution of reflected beam at specular interface and far field caused by spin separation has been studied. Due to the diffraction effect, we find a distinct difference of light polarization at the two regions. The variation of polarization distribution of reflected light provides a new method to measure the spin separation displacement caused by Spin Hall Effect of light.Comment: 7 pages, 5 figure

Large anomalous Hall effect in a hexagonal ferromagnetic Fe5Sn3 single crystal

In this paper, we report an experimental observation of the large anomalous Hall effect (AHE) in a hexagonal ferromagnetic Fe5Sn3 single crystal with current along the b axis and a magnetic field normal to the bc plane. The intrinsic contribution of the anomalous Hall conductance sigma_AH^int was approximately 613 {\Omega}-1 cm-1, which was more than 3 times the maximum value in the frustrated kagome magnet Fe3Sn2 and nearly independent of the temperature over a wide range between 5 and 350 K. The analysis results revealed that the large AHE was dominated by a common, intrinsic term, while the extrinsic contribution, i.e., the skew scattering and side jump, turned out to be small. In addition to the large AHE, it was found the types of majority carriers changed at approximately 275 and 30 K, consistent with the critical temperatures of the spin reorientation. These findings suggest that the hexagonal ferromagnetic Fe5Sn3 single crystal is an excellent candidate to use for the study of the topological features in ferromagnets.Comment: accepted as a rapid communication in Phy. Rev.

Deep transfer learning of global spectra for local soil carbon monitoring

There is global interest in spectroscopy and the development of large and diverse soil spectral libraries (SSL) to model soil organic carbon (SOC) and monitor, report, and verify (MRV) its changes. The reason is that increasing SOC can improve food production and mitigate climate change. However, ‘global’ modelling of SOC with such diverse and hyperdimensional SSLs do not generalise well locally, e.g. at a field scale. To address this challenge, we propose deep transfer learning (DTL) to leverage useful information from large-scale SSLs to assist local modelling. We used one global, three country-specific SSLs and data from three local sites with DTL to improve the modelling and localise the SOC estimates in individual fields or farms in each country. With DTL, we transferred instances from the SSLs, representations from one-dimensional convolutional neural networks (1D-CNNs) trained on the SSLs, and both instances and representations to improve local modelling. Transferring instances effectively used information from the global SSL to most accurately estimate SOC in each site, reducing the root mean square error (RMSE) by 25.8% on average compared with local modelling. Our results highlight the effectiveness of DTL and the value of diverse, global SSLs for accurate local SOC predictions. Applying DTL with a global SSL one could estimate SOC anywhere in the world more accurately, rapidly, and cost-effectively, enabling MRV protocols to monitor SOC changes

Development and validation of a novel necroptosis-related gene signature for predicting prognosis and therapeutic response in Ewing sarcoma

Ewing sarcoma (ES) is the second most common malignant bone tumor in children and has a poor prognosis due to early metastasis and easy recurrence. Necroptosis is a newly discovered cell death method, and its critical role in tumor immunity and therapy has attracted widespread attention. Thus, the emergence of necroptosis may provide bright prospects for the treatment of ES and deserves our further study. Here, based on the random forest algorithm, we identified 6 key necroptosis-related genes (NRGs) and used them to construct an NRG signature with excellent predictive performance. Subsequent analysis showed that NRGs were closely associated with ES tumor immunity, and the signature was also good at predicting immunotherapy and chemotherapy response. Next, a comprehensive analysis of key genes showed that RIPK1, JAK1, and CHMP7 were potential therapeutic targets. The Cancer Dependency Map (DepMap) results showed that CHMP7 is associated with ES cell growth, and the Gene Set Cancer Analysis (GSCALite) results revealed that the JAK1 mutation frequency was the highest. The expression of 3 genes was all negatively correlated with methylation and positively with copy number variation (CNV). Finally, an accurate nomogram was constructed with this signature and clinical traits. In short, this study constructed an accurate prognostic signature and identified 3 novel therapeutic targets against ES

Spin-phonon scattering-induced low thermal conductivity in a van der Waals layered ferromagnet Cr2_2Si2_2Te6_6

Layered van der Waals (vdW) magnets are prominent playgrounds for developing magnetoelectric, magneto-optic and spintronic devices. In spintronics, particularly in spincaloritronic applications, low thermal conductivity ($\kappa$) is highly desired. Here, by combining thermal transport measurements with density functional theory calculations, we demonstrate low $\kappa$ down to 1 W m$^{-1}$ K$^{-1}$ in a typical vdW ferromagnet Cr$_2$Si$_2$Te$_6$. In the paramagnetic state, development of magnetic fluctuations way above $T_\mathrm{c}=$ 33 K strongly reduces $\kappa$ via spin-phonon scattering, leading to low $\kappa \sim$ 1 W m$^{-1}$ K$^{-1}$ over a wide temperature range, in comparable to that of amorphous silica. In the magnetically ordered state, emergence of resonant magnon-phonon scattering limits $\kappa$ below $\sim$ 2 W m$^{-1}$ K$^{-1}$, which would be three times larger if magnetic scatterings were absent. Application of magnetic fields strongly suppresses the spin-phonon scattering, giving rise to large enhancements of $\kappa$. Our calculations well capture these complex behaviours of $\kappa$ by taking the temperature- and magnetic-field-dependent spin-phonon scattering into account. Realization of low $\kappa$ which is easily tunable by magnetic fields in Cr$_2$Si$_2$Te$_6$, may further promote spincaloritronic applications of vdW magnets. Our theoretical approach may also provide a generic understanding of spin-phonon scattering, which appears to play important roles in various systems.Comment: 14 pages, 6 figures, accepted for publication in Advanced Functional Material

Large-scale genetic study in East Asians identifies six new loci associated with colorectal cancer risk

Known genetic loci explain only a small proportion of the familial relative risk of colorectal cancer (CRC). We conducted the largest genome-wide association study in East Asians with 14,963 CRC cases and 31,945 controls and identified six new loci associated with CRC risk (P = 3.42 × 10−8 to 9.22 × 10−21) at 10q22.3, 10q25.2, 11q12.2, 12p13.31, 17p13.3 and 19q13.2. Two of these loci map to genes (TCF7L2 and TGFB1) with established roles in colorectal tumorigenesis. Four other loci are located in or near genes involved in transcription regulation (ZMIZ1), genome maintenance (FEN1), fatty acid metabolism (FADS1 and FADS2), cancer cell motility and metastasis (CD9) and cell growth and differentiation (NXN). We also found suggestive evidence for three additional loci associated with CRC risk near genome-wide significance at 8q24.11, 10q21.1 and 10q24.2. Furthermore, we replicated 22 previously reported CRC loci. Our study provides insights into the genetic basis of CRC and suggests new biological pathways