Spectral Weights, d-wave Pairing Amplitudes, and Particle-hole Tunneling Asymmetry of a Strongly Correlated Superconductor

The spectral weights (SW's) for adding and removing an electron of the Gutzwiller projected d-wave superconducting (SC) state of the t-J-type models are studied numerically on finite lattices. Restrict to the uniform system but treat exactly the strong correlation between electrons, we show that the product of weights is equal to the pairing amplitude squared, same as in the weakly coupled case. In addition, we derive a rigorous relation of SW with doping in the electron doped system and obtain particle-hole asymmetry of the conductance-proportional quantity within the SC gap energy and, also, the anti-correlation between gap sizes and peak heights observed in tunneling spectroscopy on high Tc cuprates.Comment: 4 Revtex pages and 4 .eps figures. Published versio

Use of Pseudo-observations in the Goodness-of-Fit Test for Gray\u27s Time-Varying Coefficients Model

Background The Cox proportional hazards (PH) regression model is the most common method to estimate underlying survival or failure probabilities and to estimate the effects of covariates on survival times. In Cox PH models, the regression coefficients are assumed constant over time. However, if covariate effects vary over time, alternative models which do not necessarily assume proportionality are needed. Method We proposed the Gray’s time-varying coefficient (TVC) method based on pseudo-observation. By using pseudo-observations, pseudo-residuals were calculated and plotted against the estimated survival rates at each of the nine selected time points, then were used to evaluate the goodness-of-fit of the Gray’s model. We applied this method to assess the fit for a model that predicts post-transplant survival probability among children who were under the age of 12 years, had end-stage liver disease, and underwent liver transplantation between January 2005 and June 2010. Result For Gray’s TVC model, through the first time point and the sixth time point, pseudo residual plots are around zero, while pseudo residual plots show slight departure at small values of estimated survival rate through the seventh time point and the ninth time point. Since the pseudo residual plots stay around zero at each time point without any significant departure or tendency, we can conclude that Gray’s model shows a good fit in estimating survival function at each time point. The results from this real liver transplantation data demonstrate that the final Gray’s model shows a good fit in estimating post-transplant survival. Conclusion When data violate the PH assumption, the Gray TVC model or an alternative should be used to obtain unbiased estimates on survival function and give correct inference on the relationship between potential covariates and survival. The proposed goodness-of-fit test offers a tool to investigate how well the model fits the data

Variational Monte Carlo simulations using tensor-product projected states

We propose an efficient numerical method, which combines the advantages of recently developed tensor-network based methods and standard trial wave functions, to study the ground state properties of quantum many-body systems. In this approach, we apply a projector in the form of a tensor-product operator to an input wave function, such as a Jastrow-type or Hartree-Fock wave function, and optimize the tensor elements via variational Monte Carlo. The entanglement already contained in the input wave function can considerably reduce the bond dimensions compared to the regular tensor-product state representation. In particular, this allows us to also represent states that do not obey the area law of entanglement entropy. In addition, for fermionic systems, the fermion sign structure can be encoded in the input wave function. We show that the optimized states provide good approximations of the ground-state energy and correlation functions in the cases of two-dimensional bosonic and fermonic systems.Comment: 7 pages, 5 figures, published versio

A Tree-based Federated Learning Approach for Personalized Treatment Effect Estimation from Heterogeneous Data Sources

Federated learning is an appealing framework for analyzing sensitive data from distributed health data networks due to its protection of data privacy. Under this framework, data partners at local sites collaboratively build an analytical model under the orchestration of a coordinating site, while keeping the data decentralized. However, existing federated learning methods mainly assume data across sites are homogeneous samples of the global population, hence failing to properly account for the extra variability across sites in estimation and inference. Drawing on a multi-hospital electronic health records network, we develop an efficient and interpretable tree-based ensemble of personalized treatment effect estimators to join results across hospital sites, while actively modeling for the heterogeneity in data sources through site partitioning. The efficiency of our method is demonstrated by a study of causal effects of oxygen saturation on hospital mortality and backed up by comprehensive numerical results

A model of CP Violation from Extra Dimension

We construct a realistic model of CP violation in which CP is broken in the process of dimensional reduction and orbifold compactification from a five dimensional theories with $SU(3)\times SU(3) \times SU(3)$ gauge symmetry. CP violation is a result of the Hosotani type gauge configuration in the higher dimension.Comment: 5 page

Effect of Lower Extremity Bypass Surgery on Inflammatory Reaction and Endothelial Dysfunction in Type 2 Diabetic Patients

Diabetes mellitus (DM) is a metabolic disorder characterized by hyperglycemia and dyslipidemia. The abnormalities in nutrient metabolism and elevated inflammatory mediators resulting from DM lead to impairment of wound healing and vulnerability to infection and foot ulcers. Diabetic lower limb ischemia often leads to limb necrosis. Lower extremity bypass surgery (LEBS) is indicated to prevent limb loss in patients with critical leg ischemia. This study investigated the alteration of inflammatory and endothelium dysfunction markers before and after LEBS in DM patients. Twenty one type 2 DM patients with LEBS were included. Blood was drawn before and at 1 day and 7 days after surgery in the patients. Plasma soluble cellular adhesion molecule levels and blood leukocyte integrin expressions were measured. Also, plasma concentrations of endothelin-1 and nitric oxide were analyzed to evaluate the vascular endothelial function. The results showed that there were no significant differences in plasma cellular adhesion molecules, endothelin-1 and nitric oxide levels, nor did any differences in leukocyte integrin expressions before and after the operation. These results suggest that the efficacy of LEBS on alleviating inflammatory reaction and improving endothelial function in DM patients was not obvious