Quantum Critical Spin-2 Chain with Emergent SU(3) Symmetry

We study the quantum critical phase of a SU(2) symmetric spin-2 chain obtained from spin-2 bosons in a one-dimensional lattice. We obtain the scaling of the entanglement entropy and finite-size energies by exact diagonalization and density-matrix renormalization group methods. From the numerical results of the energy spectrum, central charge, and scaling dimension we identify the conformal field theory describing the whole critical phase to be the SU(3)$_1$ Wess-Zumino-Witten model. We find that while in the whole critical phase the Hamiltonian is only SU(2) invariant, there is an emergent SU(3) symmetry in the thermodynamic limit

Field-Free Switching in Symmetry Breaking Multilayers: The Critical Role of Interlayer Chiral Exchange

It is crucial to realize field-free, deterministic, current-induced switching in spin-orbit torque magnetic random-access memory (SOT-MRAM) with perpendicular magnetic anisotropy (PMA). A tentative solution has emerged recently, which employs the interlayer chiral exchange coupling or the interlayer Dzyaloshinskii-Moriya interaction (i-DMI) to achieve symmetry breaking. We hereby investigate the interlayer DMI in a Pt/Co multilayer system with orthogonally magnetized layers, using repeatedly stacked [Pt/Co]n structure with PMA, and a thick Co layer with in-plane magnetic anisotropy (IMA). We clarify the origin and the direction of such symmetry breaking with relation to the i-DMI effective field, and show a decreasing trend of the said effective field magnitude to the stacking number (n). By comparing the current-induced field-free switching behavior for both PMA and IMA layers, we confirm the dominating role of i-DMI in such field-free switching, excluding other possible mechanisms such as tilted-anisotropy and unconventional spin currents that may have arisen from the symmetry breaking

Photocatalytic Oxidation of Gaseous Isopropanol Using Visible-Light Active Silver Vanadates/SBA-15 Composite

An environmentally friendly visible-light-driven photocatalyst, silver vanadates/SBA-15, was prepared through an incipient wetness impregnation procedure with silver vanadates (SVO) synthesized under a hydrothermal condition without a high-temperature calcination. The addition of mesoporous SBA-15 improves the formation of nanocrystalline silver vanadates. In situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) confirms the presence of Brønsted and Lewis acids on the SVO/SBA-15 composites. The results of photoluminescence spectra indicated that the electron-hole recombination rate have been effectively inhibited when SVO was loaded with mesoporous SBA-15. All the composites loaded with various amount of SVO inherit the higher adsorption capacity and larger mineralization yield than those of P-25 (commercial TiO2) and pure SVO. The sample loaded with 51% of SVO (51SVO/SBA-15) with mixed phases of Ag4V2O7 and α-Ag3VO4 exhibits the best photocatalytic activity. A favorable crystalline phase combined with high intensities of Brønsted and Lewis acids is considered the main cause of the enhanced adsorption capacity and outstanding photoactivity of the SVO/SBA-15 composites

Association of Alzhemier\u27s Disease With Hepatitis C Among Patients With Bipolar Disorder

Associations of hepatitis C virus infection with Alzheimer’s disease have not been studied among higher risk, bipolar disorder patients. This population-based case-control study investigated the risks of hepatitis C virus infection among Alzheimer’s disease patients with bipolar disorder in the years preceding their Alzheimer’s disease diagnosis. We used 2000–2013 data from the Longitudinal Health Insurance Database in Taiwan. Among patients with bipolar disorder, 73 were diagnosed with Alzheimer’s disease (cases), who were compared with 365 individuals with bipolar disorder but without Alzheimer’s disease (randomly selected controls matched on sex, age, and index year with cases). Prior claims (before the diagnosis year/index year for controls) were screened for a diagnosis of hepatitis C virus infection. Conditional logistic regression models were used for analysis. We found that 23 (31.51%) and 60 (16.44%) patients with bipolar disease were identified with a hepatitis C diagnosis among those with and without Alzheimer’s disease, respectively. Compared to controls, patients with Alzheimer’s disease showed 2.31-fold (95% confidence interval = 1.28–4.16) increased risk of hepatitis C infections adjusted for demographics and socio-economic status. Findings suggest an association of Alzheimer’s disease with a preceding diagnosis of hepatitis C infection among patients with bipolar disorder. Findings may suggest a need for increased awareness of and appropriate surveillance for Alzheimer’s disease in patients with bipolar disorder diagnosed with hepatitis C infection

The Association Between Gastro-Oesophageal Reflux Disease and Subsequent Rheumatoid Arthritis Occurrence: A Nested Case–Control Study From Taiwan

Objective Gastro-oesophageal reflux disease (GORD) is a common comorbidity among patients with rheumatoid arthritis (RA). While GORD has been attributed to the antirheumatic medications, no studies of human cohorts have investigated a link between GORD and RA. This study investigates whether GORD is associated with a subsequent RA diagnosis over a 5-year follow-up using a population-based dataset. Setting Taiwan Participants We used data from the Taiwan Longitudinal Health Insurance Database. The study group consisted of 13 645 patients with an ambulatory claim showing a GORD diagnosis. We used propensity score matching to select 13 645 comparison patients (one per study patient with GORD). Intervention We tracked each patient’s claims over a 5-year period to identify those who subsequently received a diagnosis of RA. Cox proportional hazard (PH) regression modelling was used for analysis. Results Over 5-year follow-up, RA incidence rate per 1000 person-years was 2.81 among patients with GORD and 0.84 among the comparison group. Cox PH modelling showed that GORD was independently associated with a 2.84-fold increased risk of RA (95% CI 2.09 to 3.85) over 5-year follow-up, after adjusting for the number of ambulatory care visits within the year following the index date (to mitigate surveillance bias). Conclusions We observed that GORD might associate with subsequent RA occurrence. Because current treatment guidelines for RA emphasise early diagnosis and prompt treatment, the observed association between GORD and RA may help acquaint clinicians to patients with GORD with higher RA risk and facilitate early diagnosis and treatment. Objective Gastro-oesophageal reflux disease (GORD) is a common comorbidity among patients with rheumatoid arthritis (RA). While GORD has been attributed to the antirheumatic medications, no studies of human cohorts have investigated a link between GORD and RA. This study investigates whether GORD is associated with a subsequent RA diagnosis over a 5-year follow-up using a population-based dataset. Setting Taiwan Participants We used data from the Taiwan Longitudinal Health Insurance Database. The study group consisted of 13 645 patients with an ambulatory claim showing a GORD diagnosis. We used propensity score matching to select 13 645 comparison patients (one per study patient with GORD). Intervention We tracked each patient’s claims over a 5-year period to identify those who subsequently received a diagnosis of RA. Cox proportional hazard (PH) regression modelling was used for analysis. Results Over 5-year follow-up, RA incidence rate per 1000 person-years was 2.81 among patients with GORD and 0.84 among the comparison group. Cox PH modelling showed that GORD was independently associated with a 2.84-fold increased risk of RA (95% CI 2.09 to 3.85) over 5-year follow-up, after adjusting for the number of ambulatory care visits within the year following the index date (to mitigate surveillance bias). Conclusions We observed that GORD might associate with subsequent RA occurrence. Because current treatment guidelines for RA emphasise early diagnosis and prompt treatment, the observed association between GORD and RA may help acquaint clinicians to patients with GORD with higher RA risk and facilitate early diagnosis and treatmen

DEXON: A Highly Scalable, Decentralized DAG-Based Consensus Algorithm

A blockchain system is a replicated state machine that must be fault tolerant. When designing a blockchain system, there is usually a trade-off between decentralization, scalability, and security. In this paper, we propose a novel blockchain system, DEXON, which achieves high scalability while remaining decentralized and robust in the real-world environment. We have two main contributions. First, we present a highly scalable sharding framework for blockchain. This framework takes an arbitrary number of single chains and transforms them into the \textit{blocklattice} data structure, enabling \textit{high scalability} and \textit{low transaction confirmation latency} with asymptotically optimal communication overhead. Second, we propose a single-chain protocol based on our novel verifiable random function and a new Byzantine agreement that achieves high decentralization and low latency

A Bayesian measurement error model for two-channel cell-based RNAi data with replicates

RNA interference (RNAi) is an endogenous cellular process in which small double-stranded RNAs lead to the destruction of mRNAs with complementary nucleoside sequence. With the production of RNAi libraries, large-scale RNAi screening in human cells can be conducted to identify unknown genes involved in a biological pathway. One challenge researchers face is how to deal with the multiple testing issue and the related false positive rate (FDR) and false negative rate (FNR). This paper proposes a Bayesian hierarchical measurement error model for the analysis of data from a two-channel RNAi high-throughput experiment with replicates, in which both the activity of a particular biological pathway and cell viability are monitored and the goal is to identify short hair-pin RNAs (shRNAs) that affect the pathway activity without affecting cell activity. Simulation studies demonstrate the flexibility and robustness of the Bayesian method and the benefits of having replicates in the experiment. This method is illustrated through analyzing the data from a RNAi high-throughput screening that searches for cellular factors affecting HCV replication without affecting cell viability; comparisons of the results from this HCV study and some of those reported in the literature are included.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS496 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Nonlinear dynamic responses of shell structures using vector form intrinsic finite element method

In this paper, in order to compute nonlinear dynamic responses of shell structures, formulations of the internal forces of the shell element in vector form intrinsic finite element (VFIFE) method are developed. This novel shell element is named by VFIFE-DKT element. These elements are to compute internal forces from the deformations and the motion of the shell structures. The VFIFE method is a particle-based method. They have three key VFIFE processes such as the point value description, path element and convected material frame. Thus, the shell structure is represented by finite particles. Each particle is subjected to the external forces and internal forces. The particle satisfies the Newton’s Law. A fictitious reversed rigid body motion is used to remove the rigid body motion from the deformations of the element. The internal forces of the element in deformation coordinates satify the equilibrium equations. Through the numerical examples of the benchmark structures undergo extermly-large displacements, rotation and motion, the proposed procedures using the novel element demonstrates its accuracy and efficiency

Deep Learning for Spin-Orbit Torque Characterizations with a Projected Vector Field Magnet

Spin-orbit torque characterizations on magnetic heterostructures with perpendicular anisotropy are demonstrated on a projected vector field magnet via hysteresis loop shift measurement and harmonic Hall measurement with planar Hall correction. Accurate magnetic field calibration of the vector magnet is realized with the help of deep learning models, which are able to capture the nonlinear behavior between the generated magnetic field and the currents applied to the magnet. The trained models can successfully predict the applied current combinations under the circumstances of magnetic field scans, angle scans, and hysteresis loop shift measurements. The validity of the models is further verified, complemented by the comparison of the spin-orbit torque characterization results obtained from the deep-learning-trained vector magnet system with those obtained from a conventional setup comprised of two separated electromagnets. The damping-like spin-orbit torque (DL-SOT) efficiencies (|$\xi_{DL}$|) extracted from the vector magnet and the traditional measurement configuration are consistent, where |$\xi_{DL}$| $\approx$ 0.22 for amorphous W and |$\xi_{DL}$| $\approx$ 0.02 for $\alpha$-W. Our work provides an advanced method to meticulously control a vector magnet and to conveniently perform various spin-orbit torque characterizations