Spin-dependent localization of helical edge states in a non-Hermitian phononic crystal

As a distinctive feature unique to non-Hermitian systems, non-Hermitian skin effect displays fruitful exotic phenomena in one or higher dimensions, especially when conventional topological phases are involved. Among them, hybrid skin-topological effect is theoretically proposed recently, which exhibits anomalous localization of topological boundary states at lower-dimensional boundaries accompanied by extended bulk states. Here we experimentally realize the hybrid skin-topological effect in a non-Hermitian phononic crystal. The phononic crystal, before tuning to be non-Hermitian, is an ideal acoustic realization of the Kane-Mele model, which hosts gapless helical edge states at the boundaries. By introducing a staggered distribution of loss, the spin-dependent edge modes pile up to opposite corners, leading to a direct observation of the spin-dependent hybrid skin-topological effect. Our work highlights the interplay between topology and non-Hermiticity and opens new routes to non-Hermitian wave manipulations

Improving mechanical properties of wire + arc additively manufactured maraging steel through plastic deformation enhanced aging response

Maraging steel gains ultrahigh strength through aging; however, wire + arc additively manufactured maraging steel features a columnar-dendritic structure with associated segregation and shows a much less pronounced aging response. In this paper, plastic deformation was introduced through interpass cold rolling during the layer-by-layer deposition process. After aging, mechanical testing showed a substantial strength improvement from 1410MPa (unrolled) to 1750MPa (50kN rolled). Rolling induced partial recrystallisation to break the dendritic structure and form high-angle grain boundaries, which promoted the atoms diffusion to enable a more uniform solutionizing process and improved the subsequent aging response by 105-110%. The main contribution of overall strengthening of the rolled alloy was attributed to the effective aging process, accounting for more than 95% of the entire strength increase

Arbuscular mycorrhizal fungal interactions bridge the support of root-associated microbiota for slope multifunctionality in an erosion-prone ecosystem

The role of diverse soil microbiota in restoring erosion-induced degraded lands is well recognized. Yet, the facilitative interactions among symbiotic arbuscular mycorrhizal (AM) fungi, rhizobia, and heterotrophic bacteria, which underpin multiple functions in eroded ecosystems, remain unclear. Here, we utilized quantitative microbiota profiling and ecological network analyses to explore the interplay between the diversity and biotic associations of root-associated microbiota and multifunctionality across an eroded slope of a Robinia pseudoacacia plantation on the Loess Plateau. We found explicit variations in slope multifunctionality across different slope positions, associated with shifts in limiting resources, including soil phosphorus (P) and moisture. To cope with P limitation, AM fungi were recruited by R. pseudoacacia, assuming pivotal roles as keystones and connectors within cross-kingdom networks. Furthermore, AM fungi facilitated the assembly and composition of bacterial and rhizobial communities, collectively driving slope multifunctionality. The symbiotic association among R. pseudoacacia, AM fungi, and rhizobia promoted slope multifunctionality through enhanced decomposition of recalcitrant compounds, improved P mineralization potential, and optimized microbial metabolism. Overall, our findings highlight the crucial role of AM fungal-centered microbiota associated with R. pseudoacacia in functional delivery within eroded landscapes, providing valuable insights for the sustainable restoration of degraded ecosystems in erosion-prone regions

Neighborhood Deprivation and Residential Property Values Do Not Affect Weight Loss at 1 or 3 Years After Bariatric Surgery

OBJECTIVE: This study examined the association between individual- and neighborhood-level sociodemographic factors and surgical weight loss at 1 year (short term) and 3 years (long term). METHODS: Data were obtained from the baseline survey of the BELONG (Bariatric Experience Long Term) prospective longitudinal cohort study. Individual-level self-reported data on sex, race and ethnicity, education, and household income were obtained by survey. Data from the 2010 US Census were used to calculate area Neighborhood Deprivation Index score and median value of owner-occupied housing units at the census tract level. RESULTS: Patients (N = 1341) had a mean age of 43.4 (SD 11.3) years, were mostly female (86%), were mostly Black or Hispanic (52%), had some college education (83%), and had annual household incomes ≥$51,000 (55%). Percentage total weight loss was 25.8% (SD 9.0%) at year 1 and 22.2% (SD 10.5%) at year 3. Race and ethnicity and age were significant predictors of weight loss at 1 and 3 years with a small effect of self-reported household income at year 1. There were no significant associations between census tract-level Neighborhood Deprivation Index score or value of owner-occupied housing units and weight loss at either time point. CONCLUSIONS: Health systems could improve the chances of weight-loss maintenance after surgery by addressing factors related to racial and ethnic disparities and to income disparities

Differential Regulation of H3K9/H3K14 Acetylation by Small Molecules Drives Neuron-Fate-Induction of Glioma Cell

Differentiation therapy using small molecules is a promising strategy for improving the prognosis of glioblastoma (GBM). Histone acetylation plays an important role in cell fate determination. Nevertheless, whether histone acetylation in specific sites determines GBM cells fate remains to be explored. Through screening from a 349 small molecule-library, we identified that histone deacetylase inhibitor (HDACi) MS-275 synergized with 8-CPT-cAMP was able to transdifferentiate U87MG GBM cells into neuron-like cells, which were characterized by cell cycle arrest, rich neuron biomarkers, and typical neuron electrophysiology. Intriguingly, acetylation tags of histone 3 at lysine 9 (H3K9ac) were decreased in the promoter of multiple oncogenes and cell cycle genes, while ones of H3K9ac and histone 3 at lysine 14 (H3K14ac) were increased in the promoter of neuron-specific genes. We then compiled a list of genes controlled by H3K9ac and H3K14ac, and proved that it is a good predictive power for pathologic grading and survival prediction. Moreover, cAMP agonist combined with HDACi also induced glioma stem cells (GSCs) to differentiate into neuron-like cells through the regulation of H3K9ac/K14ac, indicating that combined induction has the potential for recurrence-preventive application. Furthermore, the combination of cAMP activator plus HDACi significantly repressed the tumor growth in a subcutaneous GSC-derived tumor model, and temozolomide cooperated with the differentiation-inducing combination to prolong the survival in an orthotopic GSC-derived tumor model. These findings highlight epigenetic reprogramming through H3K9ac and H3K14ac as a novel approach for driving neuron-fate-induction of GBM cells

Numerical analysis of heat transfer and fluid flow in multilayer deposition of PAW-based wire and arc additive manufacturing

A three-dimensional numerical model has been developed to investigate the fluid flow and heat transfer behaviors in multilayer deposition of plasma arc welding (PAW) based wire and arc additive manufacture (WAAM). The volume of fluid (VOF) and porosity enthalpy methods are employed to track the molten pool free surface and solidification front, respectively. A modified double ellipsoidal heat source model is utilized to ensure constant arc heat input in calculation in the case that molten pool surface dynamically changes. Transient simulations were conducted for the 1st, 2nd and 21st layer depositions. The shape and size of deposited bead and weld pool were predicted and compared with experimental results. The results show that for each layer of deposition the Marangoni force plays the most important role in affecting fluid flow, conduction is the dominant method of heat dissipation compared to convection and radiation to the air. As the layer number increases, the length and width of molten pool and the width of deposited bead increase, whilst the layer height decreases. However these dimensions remain constant when the deposited part is sufficiently high. In high layer deposition, where side support is absent, the depth of the molten pool at the rear part is almost flat in the Y direction. The profile of the deposited bead is mainly determined by static pressure caused by gravity and surface tension pressure, therefore the bead profile is nearly circular. The simulated profiles and size dimensions of deposited bead and molten pool were validated with experimental weld appearance, cross-sectional images and process camera images. The simulated results are in good agreement with experimental results

Statistical modeling and inference for spatial and spatio-temporal data

2019 Fall.Includes bibliographical references.Spatio-temporal processes with a continuous index in space and time are encountered in many scientific disciplines such as climatology, environmental sciences, and public health. A fundamental component for modeling such spatio-temporal processes is the covariance function, which is traditionally assumed to be stationary. While convenient, this stationarity assumption can be unrealistic in many situations. In the first part of this dissertation, we develop a new class of locally stationary spatio-temporal covariance functions. A novel spatio-temporal expanding distance (STED) asymptotic framework is proposed to study the properties of statistical inference. The STED asymptotic framework is established on a fixed spatio-temporal domain, aiming to characterize spatio-temporal processes that are globally nonstationary in a rescaled fixed domain and locally stationary in a distance expanding domain. The utility of STED is illustrated by establishing the asymptotic properties of the maximum likelihood estimation for a general class of spatio-temporal covariance functions, as well as a simulation study which suggests sound finite-sample properties. Then, we address the problem of simultaneous estimation of the mean and covariance functions for continuously indexed spatio-temporal processes. A flexible spatio-temporal model with partially linear regression in the mean function and local stationarity in the covariance function is proposed. We study a profile likelihood method for estimation in the presence of spatio-temporally correlated errors. Specifically, for the nonparametric component, we employ a family of bimodal kernels to alleviate bias, which may be of independent interest for semiparametric spatial statistics. The theoretical properties of our profile likelihood estimation, including consistency and asymptotic normality, are established. A simulation study is conducted and corroborates our theoretical findings, while a health hazard data example further illustrates the methodology. Maximum likelihood method for irregularly spaced spatial datasets is computationally intensive, as it involves the manipulation of sizable dense covariance matrices. Finding the exact likelihood is generally impractical, especially for large datasets. In the third part, we present an approximation to the Gaussian log-likelihood function using Krylov subspace methods. This method reduces the computational complexity from O(N³) operations to O(N²) for dense matrices and further to quasi-linear if matrices are sparse. Specifically, we implement the conjugate gradient method to solve linear systems iteratively and use Monte Carlo method and Gauss quadrature rule to obtain a stochastic estimator of the log-determinant. We give conditions to ensure consistency of the estimators. Simulation studies have been conducted to explore various important computational aspects including complexity, accuracy and efficiency. We also apply our proposed method to estimate the spatial structure of a big LiDAR dataset

Study on the fluorescence properties of the interaction between felodipine and bovine serum protein

The interaction between felodipine and bovine serum protein was studied, the optimal experimental conditions were selected, and the fluorescence quenching mechanism was discussed. The interaction between filodipine and bovine serum protein was determined by UV spectrophotometry, and the optimal experimental conditions were selected by control variable method. The mechanism of fluorescence quenching in the system was explored by fluorescence spectrophotometry. The fluorescence intensity of the system between felodipine and bovine serum protein was the most obvious under the experimental conditions of buffer solution pH 7.4, felodipine concentration 8.0*10-4mol/L, reaction time 30min and 25°C. Static fluorescence quenching caused by the formation of complex compounds